Histogram analysis for smartphone-based rapid hematocrit determination

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Jalal, Uddin M.; Kim, Sang C.; Shim, Joon S.

2017-01-01

A novel and rapid analysis technique using histogram has been proposed for the colorimetric quantification of blood hematocrits. A smartphone-based “Histogram” app for the detection of hematocrits has been developed integrating the smartphone embedded camera with a microfluidic chip via a custom-made optical platform. The developed histogram analysis shows its effectiveness in the automatic detection of sample channel including auto-calibration and can analyze the single-channel as well as multi-channel images. Furthermore, the analyzing method is advantageous to the quantification of blood-hematocrit both in the equal and varying optical conditions. The rapid determination of blood hematocrits carries enormous information regarding physiological disorders, and the use of such reproducible, cost-effective, and standard techniques may effectively help with the diagnosis and prevention of a number of human diseases. PMID:28717569

Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors.

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Wagner, Matthias W; Narayan, Anand K; Bosemani, Thangamadhan; Huisman, Thierry A G M; Poretti, Andrea

2016-05-01

Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas. Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008). The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology. Copyright © 2015 by the American Society of Neuroimaging.

Histogram based analysis of lung perfusion of children after congenital diaphragmatic hernia repair.

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Kassner, Nora; Weis, Meike; Zahn, Katrin; Schaible, Thomas; Schoenberg, Stefan O; Schad, Lothar R; Zöllner, Frank G

2018-05-01

To investigate a histogram based approach to characterize the distribution of perfusion in the whole left and right lung by descriptive statistics and to show how histograms could be used to visually explore perfusion defects in two year old children after Congenital Diaphragmatic Hernia (CDH) repair. 28 children (age of 24.2±1.7months; all left sided hernia; 9 after extracorporeal membrane oxygenation therapy) underwent quantitative DCE-MRI of the lung. Segmentations of left and right lung were manually drawn to mask the calculated pulmonary blood flow maps and then to derive histograms for each lung side. Individual and group wise analysis of histograms of left and right lung was performed. Ipsilateral and contralateral lung show significant difference in shape and descriptive statistics derived from the histogram (Wilcoxon signed-rank test, phistogram derived parameters. Histogram analysis can be a valuable tool to characterize and visualize whole lung perfusion of children after CDH repair. It allows for several possibilities to analyze the data, either describing the perfusion differences between the right and left lung but also to explore and visualize localized perfusion patterns in the 3D lung volume. Subgroup analysis will be possible given sufficient sample sizes. Copyright © 2017 Elsevier Inc. All rights reserved.

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment.

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Reiner, Caecilia S; Gordic, Sonja; Puippe, Gilbert; Morsbach, Fabian; Wurnig, Moritz; Schaefer, Niklaus; Veit-Haibach, Patrick; Pfammatter, Thomas; Alkadhi, Hatem

2016-03-01

To evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE). Sixteen patients (15 male; mean age 65 years; age range 47-80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters' ability to discriminate responders from non-responders. According to mRECIST, 8 patients (50%) were responders and 8 (50%) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min(-1) 100 mL(-1)); p 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min(-1) 100 mL(-1), therapy response could be predicted with a sensitivity of 88% (7/8) and specificity of 75% (6/8). Voxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

Correlation of histogram analysis of apparent diffusion coefficient with uterine cervical pathologic finding.

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Lin, Yuning; Li, Hui; Chen, Ziqian; Ni, Ping; Zhong, Qun; Huang, Huijuan; Sandrasegaran, Kumar

2015-05-01

The purpose of this study was to investigate the application of histogram analysis of apparent diffusion coefficient (ADC) in characterizing pathologic features of cervical cancer and benign cervical lesions. This prospective study was approved by the institutional review board, and written informed consent was obtained. Seventy-three patients with cervical cancer (33-69 years old; 35 patients with International Federation of Gynecology and Obstetrics stage IB cervical cancer) and 38 patients (38-61 years old) with normal cervix or cervical benign lesions (control group) were enrolled. All patients underwent 3-T diffusion-weighted imaging (DWI) with b values of 0 and 800 s/mm(2). ADC values of the entire tumor in the patient group and the whole cervix volume in the control group were assessed. Mean ADC, median ADC, 25th and 75th percentiles of ADC, skewness, and kurtosis were calculated. Histogram parameters were compared between different pathologic features, as well as between stage IB cervical cancer and control groups. Mean ADC, median ADC, and 25th percentile of ADC were significantly higher for adenocarcinoma (p = 0.021, 0.006, and 0.004, respectively), and skewness was significantly higher for squamous cell carcinoma (p = 0.011). Median ADC was statistically significantly higher for well or moderately differentiated tumors (p = 0.044), and skewness was statistically significantly higher for poorly differentiated tumors (p = 0.004). No statistically significant difference of ADC histogram was observed between lymphovascular space invasion subgroups. All histogram parameters differed significantly between stage IB cervical cancer and control groups (p histogram analysis may help to distinguish early-stage cervical cancer from normal cervix or cervical benign lesions and may be useful for evaluating the different pathologic features of cervical cancer.

Characterization of testicular germ cell tumors: Whole-lesion histogram analysis of the apparent diffusion coefficient at 3T.

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Min, Xiangde; Feng, Zhaoyan; Wang, Liang; Cai, Jie; Yan, Xu; Li, Basen; Ke, Zan; Zhang, Peipei; You, Huijuan

2018-01-01

To assess the values of parameters derived from whole-lesion histograms of the apparent diffusion coefficient (ADC) at 3T for the characterization of testicular germ cell tumors (TGCTs). A total of 24 men with TGCTs underwent 3T diffusion-weighted imaging. Fourteen tumors were pathologically confirmed as seminomas, and ten tumors were pathologically confirmed as nonseminomas. Whole-lesion histogram analysis of the ADC values was performed. A Mann-Whitney U test was employed to compare the differences in ADC histogram parameters between seminomas and nonseminomas. Receiver operating characteristic analysis was used to identify the cutoff values for each parameter for differentiating seminomas from nonseminomas; furthermore, the area under the curve (AUC) was calculated to evaluate the diagnostic accuracy. The median of 10th, 25th, 50th, 75th, and 90th percentiles and mean, minimum and maximum ADC values were all significantly reduced for seminomas compared with nonseminomas (phistogram analysis of ADCs might be used for preoperative characterization of TGCTs. Copyright © 2017 Elsevier B.V. All rights reserved.

Histogram analysis of apparent diffusion coefficient maps for differentiating primary CNS lymphomas from tumefactive demyelinating lesions.

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Lu, Shan Shan; Kim, Sang Joon; Kim, Namkug; Kim, Ho Sung; Choi, Choong Gon; Lim, Young Min

2015-04-01

This study intended to investigate the usefulness of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating primary CNS lymphomas (PCNSLs), especially atypical PCNSLs, from tumefactive demyelinating lesions (TDLs). Forty-seven patients with PCNSLs and 18 with TDLs were enrolled in our study. Hyperintense lesions seen on T2-weighted images were defined as ROIs after ADC maps were registered to the corresponding T2-weighted image. ADC histograms were calculated from the ROIs containing the entire lesion on every section and on a voxel-by-voxel basis. The ADC histogram parameters were compared among all PCNSLs and TDLs as well as between the subgroup of atypical PCNSLs and TDLs. ROC curves were constructed to evaluate the diagnostic performance of the histogram parameters and to determine the optimum thresholds. The differences between the PCNSLs and TDLs were found in the minimum ADC values (ADCmin) and in the 5th and 10th percentiles (ADC5% and ADC10%) of the cumulative ADC histograms. However, no statistical significance was found in the mean ADC value or in the ADC value concerning the mode, kurtosis, and skewness. The ADCmin, ADC5%, and ADC10% were also lower in atypical PCNSLs than in TDLs. ADCmin was the best indicator for discriminating atypical PCNSLs from TDLs, with a threshold of 556×10(-6) mm2/s (sensitivity, 81.3 %; specificity, 88.9%). Histogram analysis of ADC maps may help to discriminate PCNSLs from TDLs and may be particularly useful in differentiating atypical PCNSLs from TDLs.

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

International Nuclear Information System (INIS)

Reiner, Caecilia S.; Gordic, Sonja; Puippe, Gilbert; Morsbach, Fabian; Wurnig, Moritz; Schaefer, Niklaus; Veit-Haibach, Patrick; Pfammatter, Thomas; Alkadhi, Hatem

2016-01-01

PurposeTo evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).Materials and MethodsSixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.ResultsAccording to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min −1  100 mL −1 ); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min −1  100 mL −1 ; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min −1  100 mL −1 , therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).ConclusionVoxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis to differentiate benign peripheral neurogenic tumors from soft tissue sarcomas.

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Nakajo, Masanori; Fukukura, Yoshihiko; Hakamada, Hiroto; Yoneyama, Tomohide; Kamimura, Kiyohisa; Nagano, Satoshi; Nakajo, Masayuki; Yoshiura, Takashi

2018-02-22

Apparent diffusion coefficient (ADC) histogram analyses have been used to differentiate tumor grades and predict therapeutic responses in various anatomic sites with moderate success. To determine the ability of diffusion-weighted imaging (DWI) with a whole-tumor ADC histogram analysis to differentiate benign peripheral neurogenic tumors (BPNTs) from soft tissue sarcomas (STSs). Retrospective study, single institution. In all, 25 BPNTs and 31 STSs. Two-b value DWI (b-values = 0, 1000s/mm 2 ) was at 3.0T. The histogram parameters of whole-tumor for ADC were calculated by two radiologists and compared between BPNTs and STSs. Nonparametric tests were performed for comparisons between BPNTs and STSs. P histogram parameters except kurtosis and entropy differed significantly between BPNTs and STSs. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient.

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Xu, Xiao-Quan; Li, Yan; Hong, Xun-Ning; Wu, Fei-Yun; Shi, Hai-Bin

2017-02-01

To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA). Diffusion-weighted (DW) images (b = 0 and 1000 s/mm 2 ) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC mean ), median ADC (ADC median ), 10th/25th/75th/90th percentile ADC (ADC 10 , ADC 25 , ADC 75 and ADC 90 ), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter. Significant differences were found on the ADC mean , ADC median , ADC 10 , ADC 25 , ADC 75 and ADC 90 between CPAM and VS (all p values Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC 90 value was the most promising parameter for differentiating these two entities.

Gliomas: Application of Cumulative Histogram Analysis of Normalized Cerebral Blood Volume on 3 T MRI to Tumor Grading

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Kim, Hyungjin; Choi, Seung Hong; Kim, Ji-Hoon; Ryoo, Inseon; Kim, Soo Chin; Yeom, Jeong A.; Shin, Hwaseon; Jung, Seung Chai; Lee, A. Leum; Yun, Tae Jin; Park, Chul-Kee; Sohn, Chul-Ho; Park, Sung-Hye

2013-01-01

Background Glioma grading assumes significant importance in that low- and high-grade gliomas display different prognoses and are treated with dissimilar therapeutic strategies. The objective of our study was to retrospectively assess the usefulness of a cumulative normalized cerebral blood volume (nCBV) histogram for glioma grading based on 3 T MRI. Methods From February 2010 to April 2012, 63 patients with astrocytic tumors underwent 3 T MRI with dynamic susceptibility contrast perfusion-weighted imaging. Regions of interest containing the entire tumor volume were drawn on every section of the co-registered relative CBV (rCBV) maps and T2-weighted images. The percentile values from the cumulative nCBV histograms and the other histogram parameters were correlated with tumor grades. Cochran’s Q test and the McNemar test were used to compare the diagnostic accuracies of the histogram parameters after the receiver operating characteristic curve analysis. Using the parameter offering the highest diagnostic accuracy, a validation process was performed with an independent test set of nine patients. Results The 99th percentile of the cumulative nCBV histogram (nCBV C99), mean and peak height differed significantly between low- and high-grade gliomas (P = histogram analysis of nCBV using 3 T MRI can be a useful method for preoperative glioma grading. The nCBV C99 value is helpful in distinguishing high- from low-grade gliomas and grade IV from III gliomas. PMID:23704910

ADC Histogram Analysis of Cervical Cancer Aids Detecting Lymphatic Metastases-a Preliminary Study.

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Schob, Stefan; Meyer, Hans Jonas; Pazaitis, Nikolaos; Schramm, Dominik; Bremicker, Kristina; Exner, Marc; Höhn, Anne Kathrin; Garnov, Nikita; Surov, Alexey

2017-12-01

Apparent diffusion coefficient (ADC) histogram analysis has been used to some extent in cervical cancer (CC) to distinguish between low-grade and high-grade tumors. Although this differentiation is undoubtedly helpful, it would be even more crucial in the presurgical setting to determine whether a tumor already gained the potential to metastasize via the lymphatic system. So far, no studies investigated the potential of 3T ADC histogram analysis in CC to differentiate between nodal-positive and nodal-negative entities. Therefore, the principal aim of our study was to investigate the potential of 3T ADC histogram analysis to differentiate between CC with and without lymph node metastasis. The second aim was to elucidate possible differences in ADC histogram parameters between CC with limited vs. advanced tumor stages and well-differentiated vs. undifferentiated lesions. Finally, correlations of p53 expression and Ki-67 index with ADC parameters were analyzed. Eighteen female patients (mean age 55.4 years, range 32-79 years) with histopathologically confirmed cervical squamous cell carcinoma of the uterine cervix were prospectively enrolled. Tumor stages, tumor grading, status of metastatic dissemination, Ki67-index, and p53 expression were assessed in these patients. Diffusion weighted imaging (DWI) was obtained in a 3T scanner using the following b values: b0 and b1000 s/mm 2 . Group comparisons using Mann-Whitney U test revealed the following findings: nodal-positive CC had statistically significant lower ADC parameters (ADCmin, ADCmean, median ADC, Mode, p10, p25, p75, and p90) in comparison to nodal-negative CC (all p histogram analysis in 3T DWI. This information is crucial for the gynecological surgeon to identify the optimal treatment strategy for patients suffering from CC. Furthermore, ADCentropy was identified as a potential imaging biomarker for tumor heterogeneity and might be able to indicate further molecular changes like loss of p53 expression

Subtype differentiation of renal tumors using voxel-based histogram analysis of intravoxel incoherent motion parameters.

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Gaing, Byron; Sigmund, Eric E; Huang, William C; Babb, James S; Parikh, Nainesh S; Stoffel, David; Chandarana, Hersh

2015-03-01

The aim of this study was to determine if voxel-based histogram analysis of intravoxel incoherent motion imaging (IVIM) parameters can differentiate various subtypes of renal tumors, including benign and malignant lesions. A total of 44 patients with renal tumors who underwent surgery and had histopathology available were included in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, single-institution prospective study. In addition to routine renal magnetic resonance imaging examination performed on a 1.5-T system, all patients were imaged with axial diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). A biexponential model was fitted to the diffusion signal data using a segmented algorithm to extract the IVIM parameters perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) for each voxel. Mean and histogram measures of heterogeneity (standard deviation, skewness, and kurtosis) of IVIM parameters were correlated with pathology results of tumor subtype using unequal variance t tests to compare subtypes in terms of each measure. Correction for multiple comparisons was accomplished using the Tukey honestly significant difference procedure. A total of 44 renal tumors including 23 clear cell (ccRCC), 4 papillary (pRCC), 5 chromophobe, and 5 cystic renal cell carcinomas, as well as benign lesions, 4 oncocytomas (Onc) and 3 angiomyolipomas (AMLs), were included in our analysis. Mean IVIM parameters fp and Dt differentiated 8 of 15 pairs of renal tumors. Histogram analysis of IVIM parameters differentiated 9 of 15 subtype pairs. One subtype pair (ccRCC vs pRCC) was differentiated by mean analysis but not by histogram analysis. However, 2 other subtype pairs (AML vs Onc and ccRCC vs Onc) were differentiated by histogram distribution parameters exclusively. The standard deviation of Dt [σ(Dt)] differentiated ccRCC (0.362 ± 0.136 × 10 mm/s) from AML (0.199 ± 0.043 × 10 mm/s) (P = 0

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

Energy Technology Data Exchange (ETDEWEB)

Reiner, Caecilia S., E-mail: caecilia.reiner@usz.ch; Gordic, Sonja; Puippe, Gilbert; Morsbach, Fabian; Wurnig, Moritz [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology (Switzerland); Schaefer, Niklaus; Veit-Haibach, Patrick [University Hospital Zurich, Division of Nuclear Medicine (Switzerland); Pfammatter, Thomas; Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology (Switzerland)

2016-03-15

PurposeTo evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).Materials and MethodsSixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.ResultsAccording to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min{sup −1} 100 mL{sup −1}); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min{sup −1} 100 mL{sup −1}; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min{sup −1} 100 mL{sup −1}, therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).ConclusionVoxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

Incremental Prognostic Value of Apparent Diffusion Coefficient Histogram Analysis in Head and Neck Squamous Cell Carcinoma.

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Li, Xiaoxia; Yuan, Ying; Ren, Jiliang; Shi, Yiqian; Tao, Xiaofeng

2018-03-26

We aimed to investigate the incremental prognostic value of apparent diffusion coefficient (ADC) histogram analysis in patients with head and neck squamous cell carcinoma (HNSCC) and integrate it into a multivariate prognostic model. A retrospective review of magnetic resonance imaging findings was conducted in patients with pathologically confirmed HNSCC between June 2012 and December 2015. For each tumor, six histogram parameters were derived: the 10th, 50th, and 90th percentiles of ADC (ADC 10 , ADC 50 , and ADC 90 ); mean ADC values (ADC mean ); kurtosis; and skewness. The clinical variables included age, sex, smoking status, tumor volume, and tumor node metastasis stage. The association of these histogram and clinical variables with overall survival (OS) was determined. Further validation of the histogram parameters as independent biomarkers was performed using multivariate Cox proportional hazard models combined with clinical variables, which was compared to the clinical model. Models were assessed with C index and receiver operating characteristic curve analyses for the 12- and 36-month OS. Ninety-six patients were eligible for analysis. Median follow-up was 877 days (range, 54-1516 days). A total of 29 patients died during follow-up (30%). Patients with higher ADC values (ADC 10  > 0.958 × 10 -3 mm 2 /s, ADC 50  > 1.089 × 10 -3 mm 2 /s, ADC 90  > 1.152 × 10 -3 mm 2 /s, ADC mean  > 1.047 × 10 -3 mm 2 /s) and lower kurtosis (≤0.967) were significant predictors of poor OS (P histogram analysis has incremental prognostic value in patients with HNSCC and increases the performance of a multivariable prognostic model in addition to clinical variables. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps

International Nuclear Information System (INIS)

Jakab, Andras; Berenyi, Ervin; Molnar, Peter; Emri, Miklos

2011-01-01

Current endeavors in neuro-oncology include morphological validation of imaging methods by histology, including molecular and immunohistochemical techniques. Diffusion tensor imaging (DTI) is an up-to-date methodology of intracranial diagnostics that has gained importance in studies of neoplasia. Our aim was to assess the feasibility of discriminant analysis applied to histograms of preoperative diffusion tensor imaging-derived images for the prediction of glioma grade validated by histomorphology. Tumors of 40 consecutive patients included 13 grade II astrocytomas, seven oligoastrocytomas, six grade II oligodendrogliomas, three grade III oligoastrocytomas, and 11 glioblastoma multiformes. Preoperative DTI data comprised: unweighted (B 0 ) images, fractional anisotropy, longitudinal and radial diffusivity maps, directionally averaged diffusion-weighted imaging, and trace images. Sampling consisted of generating histograms for gross tumor volumes; 25 histogram bins per scalar map were calculated. The histogram bins that allowed the most precise determination of low-grade (LG) or high-grade (HG) classification were selected by multivariate discriminant analysis. Accuracy of the model was defined by the success rate of the leave-one-out cross-validation. Statistical descriptors of voxel value distribution did not differ between LG and HG tumors and did not allow classification. The histogram model had 88.5% specificity and 85.7% sensitivity in the separation of LG and HG gliomas; specificity was improved when cases with oligodendroglial components were omitted. Constructing histograms of preoperative radiological images over the tumor volume allows representation of the grade and enables discrimination of LG and HG gliomas which has been confirmed by histopathology. (orig.)

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

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Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

Unstable Periodic Orbit Analysis of Histograms of Chaotic Time Series

International Nuclear Information System (INIS)

Zoldi, S.M.

1998-01-01

Using the Lorenz equations, we have investigated whether unstable periodic orbits (UPOs) associated with a strange attractor may predict the occurrence of the robust sharp peaks in histograms of some experimental chaotic time series. Histograms with sharp peaks occur for the Lorenz parameter value r=60.0 but not for r=28.0 , and the sharp peaks for r=60.0 do not correspond to a histogram derived from any single UPO. However, we show that histograms derived from the time series of a non-Axiom-A chaotic system can be accurately predicted by an escape-time weighting of UPO histograms. copyright 1998 The American Physical Society

Detection of Local Tumor Recurrence After Definitive Treatment of Head and Neck Squamous Cell Carcinoma: Histogram Analysis of Dynamic Contrast-Enhanced T1-Weighted Perfusion MRI.

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Choi, Sang Hyun; Lee, Jeong Hyun; Choi, Young Jun; Park, Ji Eun; Sung, Yu Sub; Kim, Namkug; Baek, Jung Hwan

2017-01-01

This study aimed to explore the added value of histogram analysis of the ratio of initial to final 90-second time-signal intensity AUC (AUCR) for differentiating local tumor recurrence from contrast-enhancing scar on follow-up dynamic contrast-enhanced T1-weighted perfusion MRI of patients treated for head and neck squamous cell carcinoma (HNSCC). AUCR histogram parameters were assessed among tumor recurrence (n = 19) and contrast-enhancing scar (n = 27) at primary sites and compared using the t test. ROC analysis was used to determine the best differentiating parameters. The added value of AUCR histogram parameters was assessed when they were added to inconclusive conventional MRI results. Histogram analysis showed statistically significant differences in the 50th, 75th, and 90th percentiles of the AUCR values between the two groups (p Histogram analysis of AUCR can improve the diagnostic yield for local tumor recurrence during surveillance after treatment for HNSCC.

Clinical Utility of Blood Cell Histogram Interpretation.

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Thomas, E T Arun; Bhagya, S; Majeed, Abdul

2017-09-01

An automated haematology analyser provides blood cell histograms by plotting the sizes of different blood cells on X-axis and their relative number on Y-axis. Histogram interpretation needs careful analysis of Red Blood Cell (RBC), White Blood Cell (WBC) and platelet distribution curves. Histogram analysis is often a neglected part of the automated haemogram which if interpreted well, has significant potential to provide diagnostically relevant information even before higher level investigations are ordered.

Quantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms.

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Nam, Se Jin; Yoo, Jaeheung; Lee, Hye Sun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; Kwak, Jin Young

2016-04-01

To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules. From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated. A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms. © 2016 by the American Institute of Ultrasound in Medicine.

Bi-Histogram Equalization with Brightnes Preservation Using Contras Enhancement

OpenAIRE

A. Anitha Rani; Gowthami Rajagopal; A. Jagadeswaran

2014-01-01

Contrast enhancement is an important factor in the image preprocesing step. One of the widely acepted contrast enhancement method is the histogram equalization. Although histogram equalization achieves comparatively beter performance on almost al types of image, global histogram equalization sometimes produces excesive visual deterioration. A new extension of bi- histogram equalization caled Bi-Histogram Equalization with Neighborhod Metric (BHENM). First, large histogram bins that cause w...

Discrimination of paediatric brain tumours using apparent diffusion coefficient histograms

International Nuclear Information System (INIS)

Bull, Jonathan G.; Clark, Christopher A.; Saunders, Dawn E.

2012-01-01

To determine if histograms of apparent diffusion coefficients (ADC) can be used to differentiate paediatric brain tumours. Imaging of histologically confirmed tumours with pre-operative ADC maps were reviewed (54 cases, 32 male, mean age 6.1 years; range 0.1-15.8 years) comprising 6 groups. Whole tumour ADC histograms were calculated; normalised for volume. Stepwise logistic regression analysis was used to differentiate tumour types using histogram metrics, initially for all groups and then for specific subsets. All 6 groups (5 dysembryoplastic neuroectodermal tumours, 22 primitive neuroectodermal tumours (PNET), 5 ependymomas, 7 choroid plexus papillomas, 4 atypical teratoid rhabdoid tumours (ATRT) and 9 juvenile pilocytic astrocytomas (JPA)) were compared. 74% (40/54) were correctly classified using logistic regression of ADC histogram parameters. In the analysis of posterior fossa tumours, 80% of ependymomas, 100% of astrocytomas and 94% of PNET-medulloblastoma were classified correctly. All PNETs were discriminated from ATRTs (22 PNET and 4 supratentorial ATRTs) (100%). ADC histograms are useful in differentiating paediatric brain tumours, in particular, the common posterior fossa tumours of childhood. PNETs were differentiated from supratentorial ATRTs, in all cases, which has important implications in terms of clinical management. (orig.)

Automatic analysis of flow cytometric DNA histograms from irradiated mouse male germ cells

International Nuclear Information System (INIS)

Lampariello, F.; Mauro, F.; Uccelli, R.; Spano, M.

1989-01-01

An automatic procedure for recovering the DNA content distribution of mouse irradiated testis cells from flow cytometric histograms is presented. First, a suitable mathematical model is developed, to represent the pattern of DNA content and fluorescence distribution in the sample. Then a parameter estimation procedure, based on the maximum likelihood approach, is constructed by means of an optimization technique. This procedure has been applied to a set of DNA histograms relative to different doses of 0.4-MeV neutrons and to different time intervals after irradiation. In each case, a good agreement between the measured histograms and the corresponding fits has been obtained. The results indicate that the proposed method for the quantitative analysis of germ cell DNA histograms can be usefully applied to the study of the cytotoxic and mutagenic action of agents of toxicological interest such as ionizing radiations.18 references

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient as a marker of breast lesions characterization at 1.5 T.

Science.gov (United States)

Bougias, H; Ghiatas, A; Priovolos, D; Veliou, K; Christou, A

2017-05-01

To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Multifractal analysis of three-dimensional histogram from color images

International Nuclear Information System (INIS)

Chauveau, Julien; Rousseau, David; Richard, Paul; Chapeau-Blondeau, Francois

2010-01-01

Natural images, especially color or multicomponent images, are complex information-carrying signals. To contribute to the characterization of this complexity, we investigate the possibility of multiscale organization in the colorimetric structure of natural images. This is realized by means of a multifractal analysis applied to the three-dimensional histogram from natural color images. The observed behaviors are confronted to those of reference models with known multifractal properties. We use for this purpose synthetic random images with trivial monofractal behavior, and multidimensional multiplicative cascades known for their actual multifractal behavior. The behaviors observed on natural images exhibit similarities with those of the multifractal multiplicative cascades and display the signature of elaborate multiscale organizations stemming from the histograms of natural color images. This type of characterization of colorimetric properties can be helpful to various tasks of digital image processing, as for instance modeling, classification, indexing.

[Clinical application of MRI histogram in evaluation of muscle fatty infiltration].

Science.gov (United States)

Zheng, Y M; Du, J; Li, W Z; Wang, Z X; Zhang, W; Xiao, J X; Yuan, Y

2016-10-18

To describe a method based on analysis of the histogram of intensity values produced from the magnetic resonance imaging (MRI) for quantifying the degree of fatty infiltration. The study included 25 patients with dystrophinopathy. All the subjects underwent muscle MRI test at thigh level. The histogram M values of 250 muscles adjusted for subcutaneous fat, representing the degree of fatty infiltration, were compared with the expert visual reading using the modified Mercuri scale. There was a significant positive correlation between the histogram M values and the scores of visual reading (r=0.854, Phistogram M values was similar to that of visual reading and results in literature. The histogram M values had stronger correlations with the clinical data than the scores of visual reading as follows: the correlations with age (r=0.730, Phistogram M values analysis had better repeatability than visual reading with the interclass correlation coefficient was 0.998 (95% CI: 0.997-0.998, PHistogram M values analysis of MRI with the advantages of repeatability and objectivity can be used to evaluate the degree of muscle fatty infiltration.

TSimpleAnalysis: histogramming many trees in parallel

CERN Document Server

Giommi, Luca

2016-01-01

I worked inside the ROOT team of EP-SFT group. My project focuses on writing a ROOT class that has the aim of creating histograms from a TChain. The name of the class is TSimpleAnalysis and it is already integrated in ROOT. The work that I have done was to write the source, the header le of the class and also a python script, that allows to the user to use the class through the command line. This represents a great improvement respect to the usual user code that counts lines and lines of code to do the same thing. (Link for the class: https://root.cern.ch/doc/master/classTSimpleAnalysis.html)

Steam leak detection method in pipeline using histogram analysis

Energy Technology Data Exchange (ETDEWEB)

Kim, Se Oh; Jeon, Hyeong Seop; Son, Ki Sung; Chae, Gyung Sun [Saean Engineering Corp, Seoul (Korea, Republic of); Park, Jong Won [Dept. of Information Communications Engineering, Chungnam NationalUnversity, Daejeon (Korea, Republic of)

2015-10-15

Leak detection in a pipeline usually involves acoustic emission sensors such as contact type sensors. These contact type sensors pose difficulties for installation and cannot operate in areas having high temperature and radiation. Therefore, recently, many researchers have studied the leak detection phenomenon by using a camera. Leak detection by using a camera has the advantages of long distance monitoring and wide area surveillance. However, the conventional leak detection method by using difference images often mistakes the vibration of a structure for a leak. In this paper, we propose a method for steam leakage detection by using the moving average of difference images and histogram analysis. The proposed method can separate the leakage and the vibration of a structure. The working performance of the proposed method is verified by comparing with experimental results.

Histogram analysis of diffusion kurtosis imaging estimates for in vivo assessment of 2016 WHO glioma grades: A cross-sectional observational study.

Science.gov (United States)

Hempel, Johann-Martin; Schittenhelm, Jens; Brendle, Cornelia; Bender, Benjamin; Bier, Georg; Skardelly, Marco; Tabatabai, Ghazaleh; Castaneda Vega, Salvador; Ernemann, Ulrike; Klose, Uwe

2017-10-01

To assess the diagnostic performance of histogram analysis of diffusion kurtosis imaging (DKI) maps for in vivo assessment of the 2016 World Health Organization Classification of Tumors of the Central Nervous System (2016 CNS WHO) integrated glioma grades. Seventy-seven patients with histopathologically-confirmed glioma who provided written informed consent were retrospectively assessed between 01/2014 and 03/2017 from a prospective trial approved by the local institutional review board. Ten histogram parameters of mean kurtosis (MK) and mean diffusivity (MD) metrics from DKI were independently assessed by two blinded physicians from a volume of interest around the entire solid tumor. One-way ANOVA was used to compare MK and MD histogram parameter values between 2016 CNS WHO-based tumor grades. Receiver operating characteristic analysis was performed on MK and MD histogram parameters for significant results. The 25th, 50th, 75th, and 90th percentiles of MK and average MK showed significant differences between IDH1/2 wild-type gliomas, IDH1/2 mutated gliomas, and oligodendrogliomas with chromosome 1p/19q loss of heterozygosity and IDH1/2 mutation (pHistogram analysis of DKI can stratify gliomas according to the integrated approach of 2016 CNS WHO. The 50th (median), 75th , and the 90th percentiles showed the highest diagnostic performance. However, the average MK is also robust and feasible in routine clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models.

Science.gov (United States)

Wang, Feng; Wang, Yuxiang; Zhou, Yan; Liu, Congrong; Xie, Lizhi; Zhou, Zhenyu; Liang, Dong; Shen, Yang; Yao, Zhihang; Liu, Jianyu

2017-12-01

To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC). Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded. Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809. © 2017 International Society for Magnetic Resonance in Medicine.

Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis.

Science.gov (United States)

Hao, Yonghong; Pan, Chu; Chen, WeiWei; Li, Tao; Zhu, WenZhen; Qi, JianPin

2016-12-01

To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features. This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC. Mean ADC, median ADC, 5 th percentile ADC, 25 th percentile ADC, 75 th percentile ADC, 95 th percentile ADC (all P histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555. © 2016 International Society for Magnetic Resonance in Medicine.

Differentiating between Glioblastoma and Primary CNS Lymphoma Using Combined Whole-tumor Histogram Analysis of the Normalized Cerebral Blood Volume and the Apparent Diffusion Coefficient.

Science.gov (United States)

Bao, Shixing; Watanabe, Yoshiyuki; Takahashi, Hiroto; Tanaka, Hisashi; Arisawa, Atsuko; Matsuo, Chisato; Wu, Rongli; Fujimoto, Yasunori; Tomiyama, Noriyuki

2018-05-31

This study aimed to determine whether whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) and apparent diffusion coefficient (ADC) for contrast-enhancing lesions can be used to differentiate between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL). From 20 patients, 9 with PCNSL and 11 with GBM without any hemorrhagic lesions, underwent MRI, including diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging before surgery. Histogram analysis of nCBV and ADC from whole-tumor voxels in contrast-enhancing lesions was performed. An unpaired t-test was used to compare the mean values for each type of tumor. A multivariate logistic regression model (LRM) was performed to classify GBM and PCNSL using the best parameters of ADC and nCBV. All nCBV histogram parameters of GBMs were larger than those of PCNSLs, but only average nCBV was statistically significant after Bonferroni correction. Meanwhile, ADC histogram parameters were also larger in GBM compared to those in PCNSL, but these differences were not statistically significant. According to receiver operating characteristic curve analysis, the nCBV average and ADC 25th percentile demonstrated the largest area under the curve with values of 0.869 and 0.838, respectively. The LRM combining these two parameters differentiated between GBM and PCNSL with a higher area under the curve value (Logit (P) = -21.12 + 10.00 × ADC 25th percentile (10 -3 mm 2 /s) + 5.420 × nCBV mean, P histogram analysis of nCBV and ADC combined can be a valuable objective diagnostic method for differentiating between GBM and PCNSL.

Gamma histograms for radiotherapy plan evaluation

International Nuclear Information System (INIS)

Spezi, Emiliano; Lewis, D. Geraint

2006-01-01

Background and purpose: The technique known as the 'γ evaluation method' incorporates pass-fail criteria for both distance-to-agreement and dose difference analysis of 3D dose distributions and provides a numerical index (γ) as a measure of the agreement between two datasets. As the γ evaluation index is being adopted in more centres as part of treatment plan verification procedures for 2D and 3D dose maps, the development of methods capable of encapsulating the information provided by this technique is recommended. Patients and methods: In this work the concept of γ index was extended to create gamma histograms (GH) in order to provide a measure of the agreement between two datasets in two or three dimensions. Gamma area histogram (GAH) and gamma volume histogram (GVH) graphs were produced using one or more 2D γ maps generated for each slice of the irradiated volume. GHs were calculated for IMRT plans, evaluating the 3D dose distribution from a commercial treatment planning system (TPS) compared to a Monte Carlo (MC) calculation used as reference dataset. Results: The extent of local anatomical inhomogenities in the plans under consideration was strongly correlated with the level of difference between reference and evaluated calculations. GHs provided an immediate visual representation of the proportion of the treated volume that fulfilled the γ criterion and offered a concise method for comparative numerical evaluation of dose distributions. Conclusions: We have introduced the concept of GHs and investigated its applications to the evaluation and verification of IMRT plans. The gamma histogram concept set out in this paper can provide a valuable technique for quantitative comparison of dose distributions and could be applied as a tool for the quality assurance of treatment planning systems

Histogram analysis of noise performance on fractional anisotropy brain MR image with different diffusion gradient numbers

International Nuclear Information System (INIS)

Chang, Yong Min; Kim, Yong Sun; Kang, Duk Sik; Lee, Young Joo; Sohn, Chul Ho; Woo, Seung Koo; Suh, Kyung Jin

2005-01-01

We wished to analyze, qualitatively and quantitatively, the noise performance of fractional anisotropy brain images along with the different diffusion gradient numbers by using the histogram method. Diffusion tensor images were acquired using a 3.0 T MR scanner from ten normal volunteers who had no neurological symptoms. The single-shot spin-echo EPI with a Stejskal-Tanner type diffusion gradient scheme was employed for the diffusion tensor measurement. With a b-valuee of 1000 s/mm 2 , the diffusion tensor images were obtained for 6, 11, 23, 35 and 47 diffusion gradient directions. FA images were generated for each DTI scheme. The histograms were then obtained at selected ROIs for the anatomical structures on the FA image. At the same ROI location, the mean FA value and the standard deviation of the mean FA value were calculated. The quality of the FA image was improved as the number of diffusion gradient directions increased by showing better contrast between the WM and GM. The histogram showed that the variance of FA values was reduced as the number of diffusion gradient directions increased. This histogram analysis was in good agreement with the result obtained using quantitative analysis. The image quality of the FA map was significantly improved as the number of diffusion gradient directions increased. The histogram analysis well demonstrated that the improvement in the FA images resulted from the reduction in the variance of the FA values included in the ROI

Apparent diffusion coefficient histogram shape analysis for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Science.gov (United States)

Meng, Jie; Zhu, Lijing; Zhu, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng

2016-10-22

To explore the role of apparent diffusion coefficient (ADC) histogram shape related parameters in early assessment of treatment response during the concurrent chemo-radiotherapy (CCRT) course of advanced cervical cancers. This prospective study was approved by the local ethics committee and informed consent was obtained from all patients. Thirty-two patients with advanced cervical squamous cell carcinomas underwent diffusion weighted magnetic resonance imaging (b values, 0 and 800 s/mm 2 ) before CCRT, at the end of 2nd and 4th week during CCRT and immediately after CCRT completion. Whole lesion ADC histogram analysis generated several histogram shape related parameters including skewness, kurtosis, s-sD av , width, standard deviation, as well as first-order entropy and second-order entropies. The averaged ADC histograms of 32 patients were generated to visually observe dynamic changes of the histogram shape following CCRT. All parameters except width and standard deviation showed significant changes during CCRT (all P histogram also changed obviously following CCRT. ADC histogram shape analysis held the potential in monitoring early tumor response in patients with advanced cervical cancers undergoing CCRT.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Science.gov (United States)

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (phistogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Histogram analysis of greyscale sonograms to differentiate between the subtypes of follicular variant of papillary thyroid cancer.

Science.gov (United States)

Kwon, M-R; Shin, J H; Hahn, S Y; Oh, Y L; Kwak, J Y; Lee, E; Lim, Y

2018-06-01

To evaluate the diagnostic value of histogram analysis using ultrasound (US) to differentiate between the subtypes of follicular variant of papillary thyroid carcinoma (FVPTC). The present study included 151 patients with surgically confirmed FVPTC diagnosed between January 2014 and May 2016. Their preoperative US features were reviewed retrospectively. Histogram parameters (mean, maximum, minimum, range, root mean square, skewness, kurtosis, energy, entropy, and correlation) were obtained for each nodule. The 152 nodules in 151 patients comprised 48 non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTPs; 31.6%), 60 invasive encapsulated FVPTCs (EFVPTCs; 39.5%), and 44 infiltrative FVPTCs (28.9%). The US features differed significantly between the subtypes of FVPTC. Discrimination was achieved between NIFTPs and infiltrative FVPTC, and between invasive EFVPTC and infiltrative FVPTC using histogram parameters; however, the parameters were not significantly different between NIFTP and invasive EFVPTC. It is feasible to use greyscale histogram analysis to differentiate between NIFTP and infiltrative FVPTC, but not between NIFTP and invasive EFVPTC. Histograms can be used as a supplementary tool to differentiate the subtypes of FVPTC. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects

Science.gov (United States)

Nemmi, Federico; Saint-Aubert, Laure; Adel, Djilali; Salabert, Anne-Sophie; Pariente, Jérémie; Barbeau, Emmanuel; Payoux, Pierre; Péran, Patrice

2014-01-01

Purpose AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer’s disease (AD) but also in healthy population. This binding; thought to be of a non-specific lipophilic nature has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in healthy and pathological populations in white matter. Methods We recruited 24 patients presenting with AD at early stage and 17 matched, healthy subjects. We used an optimized PET-MRI registration method and an approach based on intensity histogram using several indexes. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matters using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. Results White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms was not decisive to discriminate groups, and indexes based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample in two clusters, showing different uptakes in grey but also in white matter. Conclusion These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using SUVr approach. Although it is not better than standard SUVr to discriminate AD patients from healthy subjects, this information could reveal white matter modifications. PMID:24573658

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects

International Nuclear Information System (INIS)

Nemmi, Federico; Saint-Aubert, Laure; Peran, Patrice; Adel, Djilali; Salabert, Anne-Sophie; Payoux, Pierre; Pariente, Jeremie; Barbeau, Emmanuel J.

2014-01-01

AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer's disease (AD), but also in the healthy population. This binding, thought to be of a non-specific lipophilic nature, has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in white matter in healthy and pathological populations. We recruited 24 patients presenting with AD at an early stage and 17 matched, healthy subjects. We used an optimized positron emission tomography-magnetic resonance imaging (PET-MRI) registration method and an approach based on an intensity histogram using several indices. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matter using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms were not decisive to discriminate groups, and indices based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample into two clusters, showing different uptakes in grey, but also in white matter. These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using the SUVr approach. Although it is not more efficient than standard SUVr in discriminating AD patients from healthy subjects, this information could reveal white matter modifications. (orig.)

Apparent diffusion coefficient histogram analysis can evaluate radiation-induced parotid damage and predict late xerostomia degree in nasopharyngeal carcinoma.

Science.gov (United States)

Zhou, Nan; Guo, Tingting; Zheng, Huanhuan; Pan, Xia; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng

2017-09-19

We investigated apparent diffusion coefficient (ADC) histogram analysis to evaluate radiation-induced parotid damage and predict xerostomia degrees in nasopharyngeal carcinoma (NPC) patients receiving radiotherapy. The imaging of bilateral parotid glands in NPC patients was conducted 2 weeks before radiotherapy (time point 1), one month after radiotherapy (time point 2), and four months after radiotherapy (time point 3). From time point 1 to 2, parotid volume, skewness, and kurtosis decreased ( P histogram parameters increased (all P histogram parameters. Early mean change rates for bilateral parotid SD and ADC max could predict late xerostomia degrees at seven months after radiotherapy (three months after time point 3) with AUC of 0.781 and 0.818 ( P = 0.014, 0.005, respectively). ADC histogram parameters were reproducible (intraclass correlation coefficient, 0.830 - 0.999). ADC histogram analysis could be used to evaluate radiation-induced parotid damage noninvasively, and predict late xerostomia degrees of NPC patients treated with radiotherapy.

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient as a marker of breast lesions characterization at 1.5 T

International Nuclear Information System (INIS)

Bougias, H.; Ghiatas, A.; Priovolos, D.; Veliou, K.; Christou, A.

2017-01-01

Introduction: To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. Methods: 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann–Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. Results: The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P < 0.0001), while skewness was significantly higher in malignant lesions P = 0.02. However, no significant difference was found between entropy and kurtosis values in malignant lesions compared with benign ones (P = 0.06 and P = 1.00, respectively). Univariate logistic regression showed that 10th and 50th percentile ADC yielded the highest AUC (0.985; 95% confidence interval [CI]: 0.902, 1.000 and 0.982; 95% confidence interval [CI]: 0.896, 1.000 respectively), whereas kurtosis value yielded the lowest AUC (0.500; 95% CI: 0.355, 0.645), indicating that 10th and 50th percentile ADC values may be more accurate for lesion discrimination. Conclusion: Whole-lesion ADC histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. - Highlights: • DWI is a noninvasive technique that allows quantification of water diffusion in tissues. • ADC histogram analysis is a useful index in the differentiation benign and malignant breast tumors. • The 10th, 50th percentile ADC values being the best discriminators between breast lesions.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps.

Science.gov (United States)

Zhang, Yujuan; Chen, Jun; Liu, Song; Shi, Hua; Guan, Wenxian; Ji, Changfeng; Guo, Tingting; Zheng, Huanhuan; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian

2017-02-01

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer. Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm 2 ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC). There were significant differences in the 5 th , 10 th , 25 th , and 50 th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P histogram parameters, including the 10 th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675. Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer. 4 J. Magn. Reson. Imaging 2017;45:440-449. © 2016 International Society for Magnetic Resonance in Medicine.

Breast lesion characterization using whole-lesion histogram analysis with stretched-exponential diffusion model.

Science.gov (United States)

Liu, Chunling; Wang, Kun; Li, Xiaodan; Zhang, Jine; Ding, Jie; Spuhler, Karl; Duong, Timothy; Liang, Changhong; Huang, Chuan

2018-06-01

Diffusion-weighted imaging (DWI) has been studied in breast imaging and can provide more information about diffusion, perfusion and other physiological interests than standard pulse sequences. The stretched-exponential model has previously been shown to be more reliable than conventional DWI techniques, but different diagnostic sensitivities were found from study to study. This work investigated the characteristics of whole-lesion histogram parameters derived from the stretched-exponential diffusion model for benign and malignant breast lesions, compared them with conventional apparent diffusion coefficient (ADC), and further determined which histogram metrics can be best used to differentiate malignant from benign lesions. This was a prospective study. Seventy females were included in the study. Multi-b value DWI was performed on a 1.5T scanner. Histogram parameters of whole lesions for distributed diffusion coefficient (DDC), heterogeneity index (α), and ADC were calculated by two radiologists and compared among benign lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma confirmed by pathology. Nonparametric tests were performed for comparisons among invasive carcinoma, DCIS, and benign lesions. Comparisons of receiver operating characteristic (ROC) curves were performed to show the ability to discriminate malignant from benign lesions. The majority of histogram parameters (mean/min/max, skewness/kurtosis, 10-90 th percentile values) from DDC, α, and ADC were significantly different among invasive carcinoma, DCIS, and benign lesions. DDC 10% (area under curve [AUC] = 0.931), ADC 10% (AUC = 0.893), and α mean (AUC = 0.787) were found to be the best metrics in differentiating benign from malignant tumors among all histogram parameters derived from ADC and α, respectively. The combination of DDC 10% and α mean , using logistic regression, yielded the highest sensitivity (90.2%) and specificity (95.5%). DDC 10% and α mean derived from

Histogram analysis derived from apparent diffusion coefficient (ADC) is more sensitive to reflect serological parameters in myositis than conventional ADC analysis.

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Meyer, Hans Jonas; Emmer, Alexander; Kornhuber, Malte; Surov, Alexey

2018-05-01

Diffusion-weighted imaging (DWI) has the potential of being able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize tissues on MRI. The aim of this study was to correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with serological parameters in myositis. 16 patients with autoimmune myositis were included in this retrospective study. DWI was obtained on a 1.5 T scanner by using the b-values of 0 and 1000 s mm - 2 . Histogram analysis was performed as a whole muscle measurement by using a custom-made Matlab-based application. The following ADC histogram parameters were estimated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, and the following percentiles ADCp10, ADCp25, ADCp75, ADCp90, as well histogram parameters kurtosis, skewness, and entropy. In all patients, the blood sample was acquired within 3 days to the MRI. The following serological parameters were estimated: alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, C-reactive protein (CRP) and myoglobin. All patients were screened for Jo1-autobodies. Kurtosis correlated inversely with CRP (p = -0.55 and 0.03). Furthermore, ADCp10 and ADCp90 values tended to correlate with creatine kinase (p = -0.43, 0.11, and p = -0.42, = 0.12 respectively). In addition, ADCmean, p10, p25, median, mode, and entropy were different between Jo1-positive and Jo1-negative patients. ADC histogram parameters are sensitive for detection of muscle alterations in myositis patients. Advances in knowledge: This study identified that kurtosis derived from ADC maps is associated with CRP in myositis patients. Furthermore, several ADC histogram parameters are statistically different between Jo1-positive and Jo1-negative patients.

Improved Steganographic Method Preserving Pixel-Value Differencing Histogram with Modulus Function

Directory of Open Access Journals (Sweden)

Heung-Kyu Lee

2010-01-01

Full Text Available We herein advance a secure steganographic algorithm that uses a turnover policy and a novel adjusting process. Although the method of Wang et al. uses Pixel-Value Differencing (PVD and their modulus function provides high capacity and good image quality, the embedding process causes a number of artifacts, such as abnormal increases and fluctuations in the PVD histogram, which may reveal the existence of the hidden message. In order to enhance the security of the algorithm, a turnover policy is used that prevents abnormal increases in the histogram values and a novel adjusting process is devised to remove the fluctuations at the border of the subrange in the PVD histogram. The proposed method therefore eliminates all the weaknesses of the PVD steganographic methods thus far proposed and guarantees secure communication. In the experiments described herein, the proposed algorithm is compared with other PVD steganographic algorithms by using well-known steganalysis techniques, such as RS-analysis, steganalysis for LSB matching, and histogram-based attacks. The results support our contention that the proposed method enhances security by keeping the PVD histogram similar to the cover, while also providing high embedding capacity and good imperceptibility to the naked eye.

Histogram analysis of apparent diffusion coefficient maps for assessing thymic epithelial tumours: correlation with world health organization classification and clinical staging.

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Kong, Ling-Yan; Zhang, Wei; Zhou, Yue; Xu, Hai; Shi, Hai-Bin; Feng, Qing; Xu, Xiao-Quan; Yu, Tong-Fu

2018-04-01

To investigate the value of apparent diffusion coefficients (ADCs) histogram analysis for assessing World Health Organization (WHO) pathological classification and Masaoka clinical stages of thymic epithelial tumours. 37 patients with histologically confirmed thymic epithelial tumours were enrolled. ADC measurements were performed using hot-spot ROI (ADC HS-ROI ) and histogram-based approach. ADC histogram parameters included mean ADC (ADC mean ), median ADC (ADC median ), 10 and 90 percentile of ADC (ADC 10 and ADC 90 ), kurtosis and skewness. One-way ANOVA, independent-sample t-test, and receiver operating characteristic were used for statistical analyses. There were significant differences in ADC mean , ADC median , ADC 10 , ADC 90 and ADC HS-ROI among low-risk thymoma (type A, AB, B1; n = 14), high-risk thymoma (type B2, B3; n = 9) and thymic carcinoma (type C, n = 14) groups (all p-values histogram analysis may assist in assessing the WHO pathological classification and Masaoka clinical stages of thymic epithelial tumours. Advances in knowledge: 1. ADC histogram analysis could help to assess WHO pathological classification of thymic epithelial tumours. 2. ADC histogram analysis could help to evaluate Masaoka clinical stages of thymic epithelial tumours. 3. ADC 10 might be a promising imaging biomarker for assessing and characterizing thymic epithelial tumours.

True progression versus pseudoprogression in the treatment of glioblastomas: a comparison study of normalized cerebral blood volume and apparent diffusion coefficient by histogram analysis.

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Song, Yong Sub; Choi, Seung Hong; Park, Chul-Kee; Yi, Kyung Sik; Lee, Woong Jae; Yun, Tae Jin; Kim, Tae Min; Lee, Se-Hoon; Kim, Ji-Hoon; Sohn, Chul-Ho; Park, Sung-Hye; Kim, Il Han; Jahng, Geon-Ho; Chang, Kee-Hyun

2013-01-01

The purpose of this study was to differentiate true progression from pseudoprogression of glioblastomas treated with concurrent chemoradiotherapy (CCRT) with temozolomide (TMZ) by using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. Twenty patients with histopathologically proven glioblastoma who had received CCRT with TMZ underwent perfusion-weighted imaging and diffusion-weighted imaging (b = 0, 1000 sec/mm(2)). The corresponding nCBV and ADC maps for the newly visible, entirely enhancing lesions were calculated after the completion of CCRT with TMZ. Two observers independently measured the histogram parameters of the nCBV and ADC maps. The histogram parameters between the true progression group (n = 10) and the pseudoprogression group (n = 10) were compared by use of an unpaired Student's t test and subsequent multivariable stepwise logistic regression analysis to determine the best predictors for the differential diagnosis between the two groups. Receiver operating characteristic analysis was employed to determine the best cutoff values for the histogram parameters that proved to be significant predictors for differentiating true progression from pseudoprogression. Intraclass correlation coefficient was used to determine the level of inter-observer reliability for the histogram parameters. The 5th percentile value (C5) of the cumulative ADC histograms was a significant predictor for the differential diagnosis between true progression and pseudoprogression (p = 0.044 for observer 1; p = 0.011 for observer 2). Optimal cutoff values of 892 × 10(-6) mm(2)/sec for observer 1 and 907 × 10(-6) mm(2)/sec for observer 2 could help differentiate between the two groups with a sensitivity of 90% and 80%, respectively, a specificity of 90% and 80%, respectively, and an area under the curve of 0.880 and 0.840, respectively. There was no other significant differentiating parameter on the nCBV histograms. Inter

Quick cytogenetic screening of breeding bulls using flow cytometric sperm DNA histogram analysis.

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Nagy, Szabolcs; Polgár, Péter J; Andersson, Magnus; Kovács, András

2016-09-01

The aim of the present study was to test the FXCycle PI/RNase kit for routine DNA analyses in order to detect breeding bulls and/or insemination doses carrying cytogenetic aberrations. In a series of experiments we first established basic DNA histogram parameters of cytogenetically healthy breeding bulls by measuring the intraspecific genome size variation of three animals, then we compared the histogram profiles of bulls carrying cytogenetic defects to the baseline values. With the exception of one case the test was able to identify bulls with cytogenetic defects. Therefore, we conclude that the assay could be incorporated into the laboratory routine where flow cytometry is applied for semen quality control.

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery.

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Qi, Xi-Xun; Shi, Da-Fa; Ren, Si-Xie; Zhang, Su-Ya; Li, Long; Li, Qing-Chang; Guan, Li-Ming

2018-04-01

To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the evaluation of glioma grading. A total of 39 glioma patients who underwent preoperative magnetic resonance imaging (MRI) were classified into low-grade (13 cases) and high-grade (26 cases) glioma groups. Parametric DKI maps were derived, and histogram metrics between low- and high-grade gliomas were analysed. The optimum diagnostic thresholds of the parameters, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were achieved using a receiver operating characteristic (ROC). Significant differences were observed not only in 12 metrics of histogram DKI parameters (PHistogram analysis of DKI may be more effective in glioma grading.

Differentiation of adrenal adenomas from nonadenomas using CT histogram analysis method: A prospective study

International Nuclear Information System (INIS)

Halefoglu, Ahmet Mesrur; Bas, Nagihan; Yasar, Ahmet; Basak, Muzaffer

2010-01-01

negative pixels yielded high correlation with mean attenuation decreases, both on unenhanced and delayed contrast-enhanced CT. Our sensitivity was 90.9% for the 10% negative pixel percentage threshold compared to 77.2% sensitivity for ≤10 HU mean attenuation threshold for unenhanced CT. Both methods gave a 100% specificity for the diagnosis of adenoma. We also obtained a 37.9% sensitivity for 5% negative pixel threshold and a slightly lower sensitivity of 28.8% for 10% negative pixel threshold compared to the 12.1% sensitivity of ≤10 HU mean attenuation threshold while maintaining 100% specificity for contrast-enhanced CT. Conclusion: The CT histogram analysis is a simple and easily applicable method which provides higher sensitivity than the commonly used 10 HU threshold mean attenuation method of unenhanced CT and can replace it for the diagnosis of an adenoma. But with contrast-enhanced CT, although 100% specificity is being maintained, the sensitivities obtained are very poor for each method and is therefore likely to limit CT histogram analysis to be used as a clinically useful adjunct in the diagnosis of adenoma.

Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

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Jizba, Petr; Korbel, Jan

2014-11-01

In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi’s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950-2013. In order to demonstrate a strength of the method proposed we compare the multifractal δ-spectrum for various bin-widths and show the robustness of the method, especially for large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the δ-spectrum and Rényi’s q parameter is also discussed and elucidated on a simple example of multiscale time series.

Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters

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Wang, Hai-yi; Su, Zi-hua; Xu, Xiao; Sun, Zhi-peng; Duan, Fei-xue; Song, Yuan-yuan; Li, Lu; Wang, Ying-wei; Ma, Xin; Guo, Ai-tao; Ma, Lin; Ye, Hui-yi

2016-01-01

Pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) have been increasingly used to evaluate the permeability of tumor vessel. Histogram metrics are a recognized promising method of quantitative MR imaging that has been recently introduced in analysis of DCE-MRI pharmacokinetic parameters in oncology due to tumor heterogeneity. In this study, 21 patients with renal cell carcinoma (RCC) underwent paired DCE-MRI studies on a 3.0 T MR system. Extended Tofts model and population-based arterial input function were used to calculate kinetic parameters of RCC tumors. Mean value and histogram metrics (Mode, Skewness and Kurtosis) of each pharmacokinetic parameter were generated automatically using ImageJ software. Intra- and inter-observer reproducibility and scan–rescan reproducibility were evaluated using intra-class correlation coefficients (ICCs) and coefficient of variation (CoV). Our results demonstrated that the histogram method (Mode, Skewness and Kurtosis) was not superior to the conventional Mean value method in reproducibility evaluation on DCE-MRI pharmacokinetic parameters (K trans & Ve) in renal cell carcinoma, especially for Skewness and Kurtosis which showed lower intra-, inter-observer and scan-rescan reproducibility than Mean value. Our findings suggest that additional studies are necessary before wide incorporation of histogram metrics in quantitative analysis of DCE-MRI pharmacokinetic parameters. PMID:27380733

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

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Dasarathy, B. V.

1976-01-01

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

Efficient Human Action and Gait Analysis Using Multiresolution Motion Energy Histogram

Directory of Open Access Journals (Sweden)

Kuo-Chin Fan

2010-01-01

Full Text Available Average Motion Energy (AME image is a good way to describe human motions. However, it has to face the computation efficiency problem with the increasing number of database templates. In this paper, we propose a histogram-based approach to improve the computation efficiency. We convert the human action/gait recognition problem to a histogram matching problem. In order to speed up the recognition process, we adopt a multiresolution structure on the Motion Energy Histogram (MEH. To utilize the multiresolution structure more efficiently, we propose an automated uneven partitioning method which is achieved by utilizing the quadtree decomposition results of MEH. In that case, the computation time is only relevant to the number of partitioned histogram bins, which is much less than the AME method. Two applications, action recognition and gait classification, are conducted in the experiments to demonstrate the feasibility and validity of the proposed approach.

The Online Histogram Presenter for the ATLAS experiment: A modular system for histogram visualization

International Nuclear Information System (INIS)

Dotti, Andrea; Adragna, Paolo; Vitillo, Roberto A

2010-01-01

The Online Histogram Presenter (OHP) is the ATLAS tool to display histograms produced by the online monitoring system. In spite of the name, the Online Histogram Presenter is much more than just a histogram display. To cope with the large amount of data, the application has been designed to minimise the network traffic; sophisticated caching, hashing and filtering algorithms reduce memory and CPU usage. The system uses Qt and ROOT for histogram visualisation and manipulation. In addition, histogram visualisation can be extensively customised through configuration files. Finally, its very modular architecture features a lightweight plug-in system, allowing extensions to accommodate specific user needs. After an architectural overview of the application, the paper is going to present in detail the solutions adopted to increase the performance and a description of the plug-in system.

The Online Histogram Presenter for the ATLAS experiment: A modular system for histogram visualization

Energy Technology Data Exchange (ETDEWEB)

Dotti, Andrea [CERN, CH-1211 Genve 23 Switzerland (Switzerland); Adragna, Paolo [Physics Department, Queen Mary, University of London Mile End Road London E1 4RP UK (United Kingdom); Vitillo, Roberto A, E-mail: andrea.dotti@cern.c [INFN Sezione di Pisa, Ed. C Largo Bruno Pontecorvo 3, 56127 Pisa (Italy)

2010-04-01

The Online Histogram Presenter (OHP) is the ATLAS tool to display histograms produced by the online monitoring system. In spite of the name, the Online Histogram Presenter is much more than just a histogram display. To cope with the large amount of data, the application has been designed to minimise the network traffic; sophisticated caching, hashing and filtering algorithms reduce memory and CPU usage. The system uses Qt and ROOT for histogram visualisation and manipulation. In addition, histogram visualisation can be extensively customised through configuration files. Finally, its very modular architecture features a lightweight plug-in system, allowing extensions to accommodate specific user needs. After an architectural overview of the application, the paper is going to present in detail the solutions adopted to increase the performance and a description of the plug-in system.

Improved Steganographic Method Preserving Pixel-Value Differencing Histogram with Modulus Function

Directory of Open Access Journals (Sweden)

Lee Hae-Yeoun

2010-01-01

Full Text Available Abstract We herein advance a secure steganographic algorithm that uses a turnover policy and a novel adjusting process. Although the method of Wang et al. uses Pixel-Value Differencing (PVD and their modulus function provides high capacity and good image quality, the embedding process causes a number of artifacts, such as abnormal increases and fluctuations in the PVD histogram, which may reveal the existence of the hidden message. In order to enhance the security of the algorithm, a turnover policy is used that prevents abnormal increases in the histogram values and a novel adjusting process is devised to remove the fluctuations at the border of the subrange in the PVD histogram. The proposed method therefore eliminates all the weaknesses of the PVD steganographic methods thus far proposed and guarantees secure communication. In the experiments described herein, the proposed algorithm is compared with other PVD steganographic algorithms by using well-known steganalysis techniques, such as RS-analysis, steganalysis for LSB matching, and histogram-based attacks. The results support our contention that the proposed method enhances security by keeping the PVD histogram similar to the cover, while also providing high embedding capacity and good imperceptibility to the naked eye.

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects

Energy Technology Data Exchange (ETDEWEB)

Nemmi, Federico; Saint-Aubert, Laure; Peran, Patrice [Inserm, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse (France); Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Adel, Djilali; Salabert, Anne-Sophie; Payoux, Pierre [Inserm, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse (France); Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Centre Hospitalier Universitaire de Toulouse, Service de Medecine Nucleaire, Pole Imagerie, Toulouse (France); Pariente, Jeremie [Inserm, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse (France); Universite de Toulouse, UPS, Imagerie Cerebrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire de Toulouse, Toulouse (France); Centre Hospitalier Universitaire de Toulouse, Service de Neurologie, Pole Neurosciences, Toulouse (France); Barbeau, Emmanuel J. [Centre Hospitalier Universitaire de Toulouse, Service de Neurologie, Pole Neurosciences, Toulouse (France); Universite de Toulouse, UPS, Centre de Recherche Cerveau et Cognition, CNRS, CerCo, Toulouse (France)

2014-07-15

AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer's disease (AD), but also in the healthy population. This binding, thought to be of a non-specific lipophilic nature, has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in white matter in healthy and pathological populations. We recruited 24 patients presenting with AD at an early stage and 17 matched, healthy subjects. We used an optimized positron emission tomography-magnetic resonance imaging (PET-MRI) registration method and an approach based on an intensity histogram using several indices. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matter using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms were not decisive to discriminate groups, and indices based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample into two clusters, showing different uptakes in grey, but also in white matter. These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using the SUVr approach. Although it is not more efficient than standard SUVr in discriminating AD patients from healthy subjects, this information could reveal white matter modifications. (orig.)

Principal component analysis of the CT density histogram to generate parametric response maps of COPD

Science.gov (United States)

Zha, N.; Capaldi, D. P. I.; Pike, D.; McCormack, D. G.; Cunningham, I. A.; Parraga, G.

2015-03-01

Pulmonary x-ray computed tomography (CT) may be used to characterize emphysema and airways disease in patients with chronic obstructive pulmonary disease (COPD). One analysis approach - parametric response mapping (PMR) utilizes registered inspiratory and expiratory CT image volumes and CT-density-histogram thresholds, but there is no consensus regarding the threshold values used, or their clinical meaning. Principal-component-analysis (PCA) of the CT density histogram can be exploited to quantify emphysema using data-driven CT-density-histogram thresholds. Thus, the objective of this proof-of-concept demonstration was to develop a PRM approach using PCA-derived thresholds in COPD patients and ex-smokers without airflow limitation. Methods: Fifteen COPD ex-smokers and 5 normal ex-smokers were evaluated. Thoracic CT images were also acquired at full inspiration and full expiration and these images were non-rigidly co-registered. PCA was performed for the CT density histograms, from which the components with the highest eigenvalues greater than one were summed. Since the values of the principal component curve correlate directly with the variability in the sample, the maximum and minimum points on the curve were used as threshold values for the PCA-adjusted PRM technique. Results: A significant correlation was determined between conventional and PCA-adjusted PRM with 3He MRI apparent diffusion coefficient (p<0.001), with CT RA950 (p<0.0001), as well as with 3He MRI ventilation defect percent, a measurement of both small airways disease (p=0.049 and p=0.06, respectively) and emphysema (p=0.02). Conclusions: PRM generated using PCA thresholds of the CT density histogram showed significant correlations with CT and 3He MRI measurements of emphysema, but not airways disease.

Tools for the analysis of dose optimization: I. Effect-volume histogram

International Nuclear Information System (INIS)

Alber, M.; Nuesslin, F.

2002-01-01

With the advent of dose optimization algorithms, predominantly for intensity-modulated radiotherapy (IMRT), computer software has progressed beyond the point of being merely a tool at the hands of an expert and has become an active, independent mediator of the dosimetric conflicts between treatment goals and risks. To understand and control the internal decision finding as well as to provide means to influence it, a tool for the analysis of the dose distribution is presented which reveals the decision-making process performed by the algorithm. The internal trade-offs between partial volumes receiving high or low doses are driven by functions which attribute a weight to each volume element. The statistics of the distribution of these weights is cast into an effect-volume histogram (EVH) in analogy to dose-volume histograms. The analysis of the EVH reveals which traits of the optimum dose distribution result from the defined objectives, and which are a random consequence of under- or misspecification of treatment goals. The EVH can further assist in the process of finding suitable objectives and balancing conflicting objectives. If biologically inspired objectives are used, the EVH shows the distribution of local dose effect relative to the prescribed level. (author)

Histogram analysis of apparent diffusion coefficient for monitoring early response in patients with advanced cervical cancers undergoing concurrent chemo-radiotherapy.

Science.gov (United States)

Meng, Jie; Zhu, Lijing; Zhu, Li; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-01

Background Apparent diffusion coefficient (ADC) histogram analysis has been widely used in determining tumor prognosis. Purpose To investigate the dynamic changes of ADC histogram parameters during concurrent chemo-radiotherapy (CCRT) in patients with advanced cervical cancers. Material and Methods This prospective study enrolled 32 patients with advanced cervical cancers undergoing CCRT who received diffusion-weighted (DW) magnetic resonance imaging (MRI) before CCRT, at the end of the second and fourth week during CCRT and one month after CCRT completion. The ADC histogram for the entire tumor volume was generated, and a series of histogram parameters was obtained. Dynamic changes of those parameters in cervical cancers were investigated as early biomarkers for treatment response. Results All histogram parameters except AUC low showed significant changes during CCRT (all P histogram parameters of cervical cancers changed significantly at the early stage of CCRT, indicating their potential in monitoring early tumor response to therapy.

The Amazing Histogram.

Science.gov (United States)

Vandermeulen, H.; DeWreede, R. E.

1983-01-01

Presents a histogram drawing program which sorts real numbers in up to 30 categories. Entered data are sorted and saved in a text file which is then used to generate the histogram. Complete Applesoft program listings are included. (JN)

Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI.

Science.gov (United States)

Li, Anqin; Xing, Wei; Li, Haojie; Hu, Yao; Hu, Daoyu; Li, Zhen; Kamel, Ihab R

2018-05-29

The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI. This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis. ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%). Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.

Histogram Analysis of Apparent Diffusion Coefficients for Occult Tonsil Cancer in Patients with Cervical Nodal Metastasis from an Unknown Primary Site at Presentation.

Science.gov (United States)

Choi, Young Jun; Lee, Jeong Hyun; Kim, Hye Ok; Kim, Dae Yoon; Yoon, Ra Gyoung; Cho, So Hyun; Koh, Myeong Ju; Kim, Namkug; Kim, Sang Yoon; Baek, Jung Hwan

2016-01-01

To explore the added value of histogram analysis of apparent diffusion coefficient (ADC) values over magnetic resonance (MR) imaging and fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) for the detection of occult palatine tonsil squamous cell carcinoma (SCC) in patients with cervical nodal metastasis from a cancer of an unknown primary site. The institutional review board approved this retrospective study, and the requirement for informed consent was waived. Differences in the bimodal histogram parameters of the ADC values were assessed among occult palatine tonsil SCC (n = 19), overt palatine tonsil SCC (n = 20), and normal palatine tonsils (n = 20). One-way analysis of variance was used to analyze differences among the three groups. Receiver operating characteristic curve analysis was used to determine the best differentiating parameters. The increased sensitivity of histogram analysis over MR imaging and (18)F-FDG PET/CT for the detection of occult palatine tonsil SCC was evaluated as added value. Histogram analysis showed statistically significant differences in the mean, standard deviation, and 50th and 90th percentile ADC values among the three groups (P histogram analysis was 52.6% over MR imaging alone and 15.8% over combined conventional MR imaging and (18)F-FDG PET/CT. Adding ADC histogram analysis to conventional MR imaging can improve the detection sensitivity for occult palatine tonsil SCC in patients with a cervical nodal metastasis originating from a cancer of an unknown primary site. © RSNA, 2015.

Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading.

Science.gov (United States)

Wu, Rongli; Watanabe, Yoshiyuki; Arisawa, Atsuko; Takahashi, Hiroto; Tanaka, Hisashi; Fujimoto, Yasunori; Watabe, Tadashi; Isohashi, Kayako; Hatazawa, Jun; Tomiyama, Noriyuki

2017-10-01

This study aimed to compare the tumor volume definition using conventional magnetic resonance (MR) and 11C-methionine positron emission tomography (MET/PET) images in the differentiation of the pre-operative glioma grade by using whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) maps. Thirty-four patients with histopathologically proven primary brain low-grade gliomas (n = 15) and high-grade gliomas (n = 19) underwent pre-operative or pre-biopsy MET/PET, fluid-attenuated inversion recovery, dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging, and contrast-enhanced T1-weighted at 3.0 T. The histogram distribution derived from the nCBV maps was obtained by co-registering the whole tumor volume delineated on conventional MR or MET/PET images, and eight histogram parameters were assessed. The mean nCBV value had the highest AUC value (0.906) based on MET/PET images. Diagnostic accuracy significantly improved when the tumor volume was measured from MET/PET images compared with conventional MR images for the parameters of mean, 50th, and 75th percentile nCBV value (p = 0.0246, 0.0223, and 0.0150, respectively). Whole-tumor histogram analysis of CBV map provides more valuable histogram parameters and increases diagnostic accuracy in the differentiation of pre-operative cerebral gliomas when the tumor volume is derived from MET/PET images.

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use

Science.gov (United States)

Toure, Sory I.; Stow, Douglas A.; Weeks, John R.; Kumar, Sunil

2013-01-01

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

Science.gov (United States)

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed

COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATION

OpenAIRE

Kanika Kapoor and Shaveta Arora

2015-01-01

Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi Histog...

Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer.

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Choi, Moon Hyung; Oh, Soon Nam; Rha, Sung Eun; Choi, Joon-Il; Lee, Sung Hak; Jang, Hong Seok; Kim, Jun-Gi; Grimm, Robert; Son, Yohan

2016-07-01

To investigate the usefulness of apparent diffusion coefficient (ADC) values derived from histogram analysis of the whole rectal cancer as a quantitative parameter to evaluate pathologic complete response (pCR) on preoperative magnetic resonance imaging (MRI). We enrolled a total of 86 consecutive patients who had undergone surgery for rectal cancer after neoadjuvant chemoradiotherapy (CRT) at our institution between July 2012 and November 2014. Two radiologists who were blinded to the final pathological results reviewed post-CRT MRI to evaluate tumor stage. Quantitative image analysis was performed using T2 -weighted and diffusion-weighted images independently by two radiologists using dedicated software that performed histogram analysis to assess the distribution of ADC in the whole tumor. After surgery, 16 patients were confirmed to have achieved pCR (18.6%). All parameters from pre- and post-CRT ADC histogram showed good or excellent agreement between two readers. The minimum, 10th, 25th, 50th, and 75th percentile and mean ADC from post-CRT ADC histogram were significantly higher in the pCR group than in the non-pCR group for both readers. The 25th percentile value from ADC histogram in post-CRT MRI had the best diagnostic performance for detecting pCR, with an area under the receiver operating characteristic curve of 0.796. Low percentile values derived from the ADC histogram analysis of rectal cancer on MRI after CRT showed a significant difference between pCR and non-pCR groups, demonstrating the utility of the ADC value as a quantitative and objective marker to evaluate complete pathologic response to preoperative CRT in rectal cancer. J. Magn. Reson. Imaging 2016;44:212-220. © 2015 Wiley Periodicals, Inc.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

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Cho, Gene Young; Moy, Linda; Kim, Sungheon G; Baete, Steven H; Moccaldi, Melanie; Babb, James S; Sodickson, Daniel K; Sigmund, Eric E

2016-08-01

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Assessment of arterial wall enhancement for differentiation of parent artery disease from small artery disease: Comparison between histogram analysis and visual analysis on 3 dimensional contrast-enhanced T1-weighted turbo spin echo MR images at 3T

International Nuclear Information System (INIS)

Jang, Jin Hee; Kim, Tae Won; Hwang, Eo Jin; Choi, Hyun Seok; Koo, Ja Seung; Shin, Yong Sam; Jung, So Lyung; Ahn, Kook Jin; Kim, Bum Soo

2017-01-01

The purpose of this study was to compare the histogram analysis and visual scores in 3T MRI assessment of middle cerebral arterial wall enhancement in patients with acute stroke, for the differentiation of parent artery disease (PAD) from small artery disease (SAD). Among the 82 consecutive patients in a tertiary hospital for one year, 25 patients with acute infarcts in middle cerebral artery (MCA) territory were included in this study including 15 patients with PAD and 10 patients with SAD. Three-dimensional contrast-enhanced T1-weighted turbo spin echo MR images with black-blood preparation at 3T were analyzed both qualitatively and quantitatively. The degree of MCA stenosis, and visual and histogram assessments on MCA wall enhancement were evaluated. A statistical analysis was performed to compare diagnostic accuracy between qualitative and quantitative metrics. The degree of stenosis, visual enhancement score, geometric mean (GM), and the 90th percentile (90P) value from the histogram analysis were significantly higher in PAD than in SAD (p = 0.006 for stenosis, < 0.001 for others). The receiver operating characteristic curve area of GM and 90P were 1 (95% confidence interval [CI], 0.86-1.00). A histogram analysis of a relevant arterial wall enhancement allows differentiation between PAD and SAD in patients with acute stroke within the MCA territory

Assessment of arterial wall enhancement for differentiation of parent artery disease from small artery disease: Comparison between histogram analysis and visual analysis on 3 dimensional contrast-enhanced T1-weighted turbo spin echo MR images at 3T

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Jang, Jin Hee; Kim, Tae Won; Hwang, Eo Jin; Choi, Hyun Seok; Koo, Ja Seung; Shin, Yong Sam; Jung, So Lyung; Ahn, Kook Jin; Kim, Bum Soo [College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of)

2017-04-15

The purpose of this study was to compare the histogram analysis and visual scores in 3T MRI assessment of middle cerebral arterial wall enhancement in patients with acute stroke, for the differentiation of parent artery disease (PAD) from small artery disease (SAD). Among the 82 consecutive patients in a tertiary hospital for one year, 25 patients with acute infarcts in middle cerebral artery (MCA) territory were included in this study including 15 patients with PAD and 10 patients with SAD. Three-dimensional contrast-enhanced T1-weighted turbo spin echo MR images with black-blood preparation at 3T were analyzed both qualitatively and quantitatively. The degree of MCA stenosis, and visual and histogram assessments on MCA wall enhancement were evaluated. A statistical analysis was performed to compare diagnostic accuracy between qualitative and quantitative metrics. The degree of stenosis, visual enhancement score, geometric mean (GM), and the 90th percentile (90P) value from the histogram analysis were significantly higher in PAD than in SAD (p = 0.006 for stenosis, < 0.001 for others). The receiver operating characteristic curve area of GM and 90P were 1 (95% confidence interval [CI], 0.86-1.00). A histogram analysis of a relevant arterial wall enhancement allows differentiation between PAD and SAD in patients with acute stroke within the MCA territory.

VHDL implementation on histogram with ADC CAMAC module

International Nuclear Information System (INIS)

Ruby Santhi, R.; Satyanarayana, V.V.V.; Ajith Kumar, B.P.

2007-01-01

Modern nuclear spectroscopy systems the data acquisition and analysis in experimental science have been undergoing major changes because of faster speed and higher resolution. The CAMAC module which is described here is FPGA based 8K x 24 bit Histogram Memory integrated with ADC on a single board has been designed and fabricated. This module accepts input from Spectroscopy Amplifier for Pulse Height Analysis and offers all features single spectra for a few selected parameters. These on line histograms are to monitor the progress of the experiments during on line experiments

Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage.

Science.gov (United States)

Xu, Xiao-Quan; Ma, Gao; Wang, Yan-Jun; Hu, Hao; Su, Guo-Yi; Shi, Hai-Bin; Wu, Fei-Yun

2017-07-18

To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC). High T-stage (T3/4) NPC showed significantly higher Kapp-mean (P = 0.018), Kapp-median (P = 0.029) and Kapp-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of Dapp and Kapp were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively. DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Science.gov (United States)

Meng, Jie; Zhu, Lijing; Zhu, Li; Xie, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; He, Jian; Ge, Yun; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-03

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm 2 ) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC mean , 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

Dose-volume histogram analysis as predictor of radiation pneumonitis in primary lung cancer patients treated with radiotherapy

International Nuclear Information System (INIS)

Fay, Michael; Tan, Alex; Fisher, Richard; Mac Manus, Michael; Wirth, Andrew; Ball, David

2005-01-01

Purpose: To determine the relationship between various parameters derived from lung dose-volume histogram analysis and the risk of symptomatic radiation pneumonitis (RP) in patients undergoing radical radiotherapy for primary lung cancer. Methods and Materials: The records of 156 patients with lung cancer who had been treated with radical radiotherapy (≥45 Gy) and for whom dose-volume histogram data were available were reviewed. The incidence of symptomatic RP was correlated with a variety of parameters derived from the dose-volume histogram data, including the volume of lung receiving 10 Gy (V 10 ) through 50 Gy (V 50 ) and the mean lung dose (MLD). Results: The rate of RP at 6 months was 15% (95% confidence interval 9-22%). On univariate analysis, only V 30 (p = 0.036) and MLD (p = 0.043) were statistically significantly related to RP. V 30 correlated highly positively with MLD (r = 0.96, p 30 and MLD can be used to predict the risk of RP in lung cancer patients undergoing radical radiotherapy

Fast analysis of molecular dynamics trajectories with graphics processing units-Radial distribution function histogramming

International Nuclear Information System (INIS)

Levine, Benjamin G.; Stone, John E.; Kohlmeyer, Axel

2011-01-01

The calculation of radial distribution functions (RDFs) from molecular dynamics trajectory data is a common and computationally expensive analysis task. The rate limiting step in the calculation of the RDF is building a histogram of the distance between atom pairs in each trajectory frame. Here we present an implementation of this histogramming scheme for multiple graphics processing units (GPUs). The algorithm features a tiling scheme to maximize the reuse of data at the fastest levels of the GPU's memory hierarchy and dynamic load balancing to allow high performance on heterogeneous configurations of GPUs. Several versions of the RDF algorithm are presented, utilizing the specific hardware features found on different generations of GPUs. We take advantage of larger shared memory and atomic memory operations available on state-of-the-art GPUs to accelerate the code significantly. The use of atomic memory operations allows the fast, limited-capacity on-chip memory to be used much more efficiently, resulting in a fivefold increase in performance compared to the version of the algorithm without atomic operations. The ultimate version of the algorithm running in parallel on four NVIDIA GeForce GTX 480 (Fermi) GPUs was found to be 92 times faster than a multithreaded implementation running on an Intel Xeon 5550 CPU. On this multi-GPU hardware, the RDF between two selections of 1,000,000 atoms each can be calculated in 26.9 s per frame. The multi-GPU RDF algorithms described here are implemented in VMD, a widely used and freely available software package for molecular dynamics visualization and analysis.

A novel JPEG steganography method based on modulus function with histogram analysis

Directory of Open Access Journals (Sweden)

V. Banoci

2012-06-01

Full Text Available In this paper, we present a novel steganographic method for embedding of secret data in still grayscale JPEG image. In order to provide large capacity of the proposed method while maintaining good visual quality of stego-image, the embedding process is performed in quantized transform coefficients of Discrete Cosine transform (DCT by modifying coefficients according to modulo function, what gives to the steganography system blind extraction predisposition. After-embedding histogram of proposed Modulo Histogram Fitting (MHF method is analyzed to secure steganography system against steganalysis attacks. In addition, AES ciphering was implemented to increase security and improve histogram after-embedding characteristics of proposed steganography system as experimental results show.

Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement

Directory of Open Access Journals (Sweden)

V. Magudeeswaran

2013-01-01

Full Text Available Fuzzy logic-based histogram equalization (FHE is proposed for image contrast enhancement. The FHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two subhistograms based on the median value of the original image and then equalizes them independently to preserve image brightness. The qualitative and quantitative analyses of proposed FHE algorithm are evaluated using two well-known parameters like average information contents (AIC and natural image quality evaluator (NIQE index for various images. From the qualitative and quantitative measures, it is interesting to see that this proposed method provides optimum results by giving better contrast enhancement and preserving the local information of the original image. Experimental result shows that the proposed method can effectively and significantly eliminate washed-out appearance and adverse artifacts induced by several existing methods. The proposed method has been tested using several images and gives better visual quality as compared to the conventional methods.

The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer.

Science.gov (United States)

Zhang, Yu-Dong; Wang, Qing; Wu, Chen-Jiang; Wang, Xiao-Ning; Zhang, Jing; Liu, Hui; Liu, Xi-Sheng; Shi, Hai-Bin

2015-04-01

To evaluate histogram analysis of intravoxel incoherent motion (IVIM) for discriminating the Gleason grade of prostate cancer (PCa). A total of 48 patients pathologically confirmed as having clinically significant PCa (size > 0.5 cm) underwent preoperative DW-MRI (b of 0-900 s/mm(2)). Data was post-processed by monoexponential and IVIM model for quantitation of apparent diffusion coefficients (ADCs), perfusion fraction f, diffusivity D and pseudo-diffusivity D*. Histogram analysis was performed by outlining entire-tumour regions of interest (ROIs) from histological-radiological correlation. The ability of imaging indices to differentiate low-grade (LG, Gleason score (GS) ≤6) from intermediate/high-grade (HG, GS > 6) PCa was analysed by ROC regression. Eleven patients had LG tumours (18 foci) and 37 patients had HG tumours (42 foci) on pathology examination. HG tumours had significantly lower ADCs and D in terms of mean, median, 10th and 75th percentiles, combined with higher histogram kurtosis and skewness for ADCs, D and f, than LG PCa (p Histogram D showed relatively higher correlations (ñ = 0.641-0.668 vs. ADCs: 0.544-0.574) with ordinal GS of PCa; and its mean, median and 10th percentile performed better than ADCs did in distinguishing LG from HG PCa. It is feasible to stratify the pathological grade of PCa by IVIM with histogram metrics. D performed better in distinguishing LG from HG tumour than conventional ADCs. • GS had relatively higher correlation with tumour D than ADCs. • Difference of histogram D among two-grade tumours was statistically significant. • D yielded better individual features in demonstrating tumour grade than ADC. • D* and f failed to determine tumour grade of PCa.

Whole brain magnetization transfer histogram analysis of pediatric acute lymphoblastic leukemia patients receiving intrathecal methotrexate therapy

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Yamamoto, Akira [Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto-shi Kyoto 606-8507 (Japan)]. E-mail: yakira@kuhp.kyoto-u.ac.jp; Miki, Yukio [Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto-shi Kyoto 606-8507 (Japan)]. E-mail: mikiy@kuhp.kyoto-u.ac.jp; Adachi, Souichi [Department of Pediatrics, Graduate School of Medicine, Kyoto University, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto-shi Kyoto 606-8507 (Japan)]. E-mail: sadachi@kuhp.kyoto-u.ac.jp (and others)

2006-03-15

Background and purpose: The purpose of this prospective study was to evaluate the hypothesis that magnetization transfer ratio (MTR) histogram analysis of the whole brain could detect early and subtle brain changes nonapparent on conventional magnetic resonance imaging (MRI) in children with acute lymphoblastic leukemia (ALL) receiving methotrexate (MTX) therapy. Materials and methods: Subjects in this prospective study comprised 10 children with ALL (mean age, 6 years; range, 0-16 years). In addition to conventional MRI, magnetization transfer images were obtained before and after intrathecal and intravenous MTX therapy. MTR values were calculated and plotted as a histogram, and peak height and location were calculated. Differences in peak height and location between pre- and post-MTX therapy scans were statistically analyzed. Conventional MRI was evaluated for abnormal signal area in white matter. Results: MTR peak height was significantly lower on post-MTX therapy scans than on pre-MTX therapy scans (p = 0.002). No significant differences in peak location were identified between pre- and post-chemotherapy imaging. No abnormal signals were noted in white matter on either pre- or post-MTX therapy conventional MRI. Conclusions: This study demonstrates that MTR histogram analysis allows better detection of early and subtle brain changes in ALL patients who receive MTX therapy than conventional MRI.

Reliability Study Regarding the Use of Histogram Similarity Methods for Damage Detection

Directory of Open Access Journals (Sweden)

Nicoleta Gillich

2013-01-01

Full Text Available The paper analyses the reliability of three dissimilarity estimators to compare histograms, as support for a frequency-based damage detection method, able to identify structural changes in beam-like structures. First a brief presentation of the own developed damage detection method is made, with focus on damage localization. It consists actually in comparing a histogram derived from measurement results, with a large series of histograms, namely the damage location indexes for all locations along the beam, obtained by calculus. We tested some dissimilarity estimators like the Minkowski-form Distances, the Kullback-Leibler Divergence and the Histogram Intersection and found the Minkowski Distance as the method providing best results. It was tested for numerous locations, using real measurement results and with results artificially debased by noise, proving its reliability.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

Science.gov (United States)

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-04-12

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

Whole-lesion histogram analysis of the apparent diffusion coefficient: Evaluation of the correlation with subtypes of mucinous breast carcinoma.

Science.gov (United States)

Guo, Yuan; Kong, Qing-Cong; Zhu, Ye-Qing; Liu, Zhen-Zhen; Peng, Ling-Rong; Tang, Wen-Jie; Yang, Rui-Meng; Xie, Jia-Jun; Liu, Chun-Ling

2018-02-01

To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25 th (P = 0.004), 50 th (P = 0.004), 75 th (P = 0.006), and 90 th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25 th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10 -3 mm 2 /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25 th (P = 0.015), and 50 th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25 th percentile of the ADC cutoff value (1.476 × 10 -3 mm 2 /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400. © 2017 International Society for Magnetic Resonance in Medicine.

Quadrant Dynamic with Automatic Plateau Limit Histogram Equalization for Image Enhancement

Directory of Open Access Journals (Sweden)

P. Jagatheeswari

2014-01-01

Full Text Available The fundamental and important preprocessing stage in image processing is the image contrast enhancement technique. Histogram equalization is an effective contrast enhancement technique. In this paper, a histogram equalization based technique called quadrant dynamic with automatic plateau limit histogram equalization (QDAPLHE is introduced. In this method, a hybrid of dynamic and clipped histogram equalization methods are used to increase the brightness preservation and to reduce the overenhancement. Initially, the proposed QDAPLHE algorithm passes the input image through a median filter to remove the noises present in the image. Then the histogram of the filtered image is divided into four subhistograms while maintaining second separated point as the mean brightness. Then the clipping process is implemented by calculating automatically the plateau limit as the clipped level. The clipped portion of the histogram is modified to reduce the loss of image intensity value. Finally the clipped portion is redistributed uniformly to the entire dynamic range and the conventional histogram equalization is executed in each subhistogram independently. Based on the qualitative and the quantitative analysis, the QDAPLHE method outperforms some existing methods in literature.

The Histogram-Area Connection

Science.gov (United States)

Gratzer, William; Carpenter, James E.

2008-01-01

This article demonstrates an alternative approach to the construction of histograms--one based on the notion of using area to represent relative density in intervals of unequal length. The resulting histograms illustrate the connection between the area of the rectangles associated with particular outcomes and the relative frequency (probability)…

Histogram analysis of apparent diffusion coefficient at 3.0 T in urinary bladder lesions: correlation with pathologic findings.

Science.gov (United States)

Suo, Shi-Teng; Chen, Xiao-Xi; Fan, Yu; Wu, Lian-Ming; Yao, Qiu-Ying; Cao, Meng-Qiu; Liu, Qiang; Xu, Jian-Rong

2014-08-01

To investigate the potential value of histogram analysis of apparent diffusion coefficient (ADC) obtained at standard (700 s/mm(2)) and high (1500 s/mm(2)) b values on a 3.0-T scanner in the differentiation of bladder cancer from benign lesions and in assessing bladder tumors of different pathologic T stages and to evaluate the diagnostic performance of ADC-based histogram parameters. In all, 52 patients with bladder lesions, including benign lesions (n = 7) and malignant tumors (n = 45; T1 stage or less, 23; T2 stage, 7; T3 stage, 8; and T4 stage, 7), were retrospectively evaluated. Magnetic resonance examination at 3.0 T and diffusion-weighted imaging were performed. ADC maps were obtained at two b values (b = 700 and 1500 s/mm(2); ie, ADC-700 and ADC-1500). Parameters of histogram analysis included mean, kurtosis, skewness, and entropy. The correlations between these parameters and pathologic results were revealed. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic value of histogram parameters. Significant differences were found in mean ADC-700, mean ADC-1500, skewness ADC-1500, and kurtosis ADC-1500 between bladder cancer and benign lesions (P = .002-.032). There were also significant differences in mean ADC-700, mean ADC-1500, and kurtosis ADC-1500 among bladder tumors of different pathologic T stages (P = .000-.046). No significant differences were observed in other parameters. Mean ADC-1500 and kurtosis ADC-1500 were significantly correlated with T stage, respectively (ρ = -0.614, P Histogram analysis of ADC-1500 at 3.0 T can be useful in evaluation of bladder lesions. A combination of mean ADC-1500 and kurtosis ADC-1500 may be more beneficial in the differentiation of benign and malignant lesions. Mean ADC-1500 was the most promising parameter for differentiating low- from high-stage bladder cancer. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region.

Science.gov (United States)

Wang, Yan-Jun; Xu, Xiao-Quan; Hu, Hao; Su, Guo-Yi; Shen, Jie; Shi, Hai-Bin; Wu, Fei-Yun

2018-06-01

Background To clarify the nature of cervical malignant lymphadenopathy is highly important for the diagnosis and differential diagnosis of head and neck tumors. Purpose To investigate the role of first-order apparent diffusion coefficient (ADC) histogram analysis for differentiating lymphoma from metastatic lymph nodes of squamous cell carcinoma (SCC) in the head and neck region. Material and Methods Diffusion-weighted imaging (DWI) data of 67 patients (lymphoma, n = 20; SCC, n = 47) with malignant lymphadenopathy were retrospectively analyzed. The SCC group was divided into nasopharyngeal SCC and non-nasopharyngeal SCC groups. The ADC histogram features (ADC 10 , ADC 25 , ADC mean , ADC median , ADC 75 , ADC 90 , skewness, and kurtosis) were derived and then compared by independent-samples t-test and one-way analysis of variance test, respectively. Receiver operating characteristic curve analyses were employed to investigate diagnostic performance of the significant parameters. Results Lymphoma showed significantly lower ADC mean , ADC median , ADC 75 , and ADC 90 than SCC (all P  0.05). Lymphoma showed significantly lower ADC 25 , ADC mean , ADC median , ADC 75 , and ADC 90 than non-nasopharyngeal SCC (all P histogram analysis is capable of differentiating lymphoma from metastatic lymph nodes of SCC, especially those of non-nasopharyngeal SCC.

Evaluation of low-grade glioma structural changes after chemotherapy using DTI-based histogram analysis and functional diffusion maps

Energy Technology Data Exchange (ETDEWEB)

Castellano, Antonella; Iadanza, Antonella; Falini, Andrea [San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Neuroradiology Unit and CERMAC, Milano (Italy); Donativi, Marina [University of Salento, Department of Mathematics and Physics ' ' Ennio De Giorgi' ' and A.D.A.M. (Advanced Data Analysis in Medicine), Lecce (Italy); Ruda, Roberta; Bertero, Luca; Soffietti, Riccardo [University of Torino, Department of Neuro-oncology, Turin (Italy); De Nunzio, Giorgio [University of Salento, Department of Mathematics and Physics ' ' Ennio De Giorgi' ' and A.D.A.M. (Advanced Data Analysis in Medicine), Lecce (Italy); INFN (National Institute of Nuclear Physics), Lecce (Italy); Riva, Marco; Bello, Lorenzo [Universita degli Studi di Milano, Milan, and Humanitas Research Hospital, Department of Medical Biotechnology and Translational Medicine, Rozzano, MI (Italy); Rucco, Matteo [University of Camerino, School of Science and Technology, Computer Science Division, Camerino, MC (Italy)

2016-05-15

To explore the role of diffusion tensor imaging (DTI)-based histogram analysis and functional diffusion maps (fDMs) in evaluating structural changes of low-grade gliomas (LGGs) receiving temozolomide (TMZ) chemotherapy. Twenty-one LGG patients underwent 3T-MR examinations before and after three and six cycles of dose-dense TMZ, including 3D-fluid-attenuated inversion recovery (FLAIR) sequences and DTI (b = 1000 s/mm{sup 2}, 32 directions). Mean diffusivity (MD), fractional anisotropy (FA), and tensor-decomposition DTI maps (p and q) were obtained. Histogram and fDM analyses were performed on co-registered baseline and post-chemotherapy maps. DTI changes were compared with modifications of tumour area and volume [according to Response Assessment in Neuro-Oncology (RANO) criteria], and seizure response. After three cycles of TMZ, 20/21 patients were stable according to RANO criteria, but DTI changes were observed in all patients (Wilcoxon test, P ≤ 0.03). After six cycles, DTI changes were more pronounced (P ≤ 0.005). Seventy-five percent of patients had early seizure response with significant improvement of DTI values, maintaining stability on FLAIR. Early changes of the 25th percentiles of p and MD predicted final volume change (R{sup 2} = 0.614 and 0.561, P < 0.0005, respectively). TMZ-related changes were located mainly at tumour borders on p and MD fDMs. DTI-based histogram and fDM analyses are useful techniques to evaluate the early effects of TMZ chemotherapy in LGG patients. (orig.)

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.

Science.gov (United States)

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-06-01

The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

Science.gov (United States)

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

Science.gov (United States)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Differentiation of orbital lymphoma and idiopathic orbital inflammatory pseudotumor: combined diagnostic value of conventional MRI and histogram analysis of ADC maps.

Science.gov (United States)

Ren, Jiliang; Yuan, Ying; Wu, Yingwei; Tao, Xiaofeng

2018-05-02

The overlap of morphological feature and mean ADC value restricted clinical application of MRI in the differential diagnosis of orbital lymphoma and idiopathic orbital inflammatory pseudotumor (IOIP). In this paper, we aimed to retrospectively evaluate the combined diagnostic value of conventional magnetic resonance imaging (MRI) and whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in the differentiation of the two lesions. In total, 18 patients with orbital lymphoma and 22 patients with IOIP were included, who underwent both conventional MRI and diffusion weighted imaging before treatment. Conventional MRI features and histogram parameters derived from ADC maps, including mean ADC (ADC mean ), median ADC (ADC median ), skewness, kurtosis, 10th, 25th, 75th and 90th percentiles of ADC (ADC 10 , ADC 25 , ADC 75 , ADC 90 ) were evaluated and compared between orbital lymphoma and IOIP. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating. Differential model was built upon the selected variables and receiver operating characteristic (ROC) analysis was also performed to determine the differential ability of the model. Multivariate logistic regression showed ADC 10 (P = 0.023) and involvement of orbit preseptal space (P = 0.029) were the most promising indexes in the discrimination of orbital lymphoma and IOIP. The logistic model defined by ADC 10 and involvement of orbit preseptal space was built, which achieved an AUC of 0.939, with sensitivity of 77.30% and specificity of 94.40%. Conventional MRI feature of involvement of orbit preseptal space and ADC histogram parameter of ADC 10 are valuable in differential diagnosis of orbital lymphoma and IOIP.

Comparative study of standard space and real space analysis of quantitative MR brain data.

Science.gov (United States)

Aribisala, Benjamin S; He, Jiabao; Blamire, Andrew M

2011-06-01

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space. Copyright © 2011 Wiley-Liss, Inc.

Curvature histogram features for retrieval of images of smooth 3D objects

International Nuclear Information System (INIS)

Zhdanov, I; Scherbakov, O; Potapov, A; Peterson, M

2014-01-01

We consider image features on the base of histograms of oriented gradients (HOG) with addition of contour curvature histogram (HOG-CH), and also compare it with results of known scale-invariant feature transform (SIFT) approach in application to retrieval of images of smooth 3D objects.

Limits of dose escalation in lung cancer: a dose-volume histogram analysis comparing coplanar and non-coplanar techniques

Energy Technology Data Exchange (ETDEWEB)

Derycke, S; Van Duyse, B; Schelfhout, J; De Neve, W

1995-12-01

To evaluate the feasibility of dose escalation in radiotherapy of inoperable lung cancer, a dose-volume histogram analysis was performed comparing standard coplanar (2D) with non-coplanar (3D) beam arrangements on a non-selected group of 20 patients planned by Sherouse`s GRATISTM 3D-planning system. Serial CT-scanning was performed and 2 Target Volumes (Tvs) were defined. Gross Tumor Volume (GTV) defined a high-dose Target Volume (TV-1). GTV plus location of node stations with > 10% probability of invasion (Minet et al.) defined an intermediate-dose Target Volume (TV-2). However, nodal regions which are incompatible with cure were excluded from TV-2. These are ATS-regions 1, 8, 9 and 14 all left and right as well as heterolateral regions. For 3D-planning, Beam`s Eye View selected (by an experienced planner) beam arrangements were optimised using Superdot, a method of target dose-gradient annihilation developed by Sherouse. A second 3D-planning was performed using 4 beam incidences with maximal angular separation. The linac`s isocenter for the optimal arrangement was located at the geometrical center of gravity of a tetraheder, the tetraheder`s comers being the consecutive positions of the virtual source. This ideal beam arrangement was approximated as close as possible, taking into account technical limitations (patient-couch-gantry collisions). Criteria for tolerance were met if no points inside the spinal cord exceeded 50 Gy and if at least 50% of the lung volume received less than 20Gy. If dose regions below 50 Gy were judged acceptable at TV-2, 2D- as well as 3D-plans allow safe escalation to 80 Gy at TV-1. When TV-2 needed to be encompassed by isodose surfaces exceeding 50Gy, 3D-plans were necessary to limit dose at the spinal cord below tolerance. For large TVs dose is limited by lung tolerance for 3D-plans. An analysis (including NTCP-TCP as cost functions) of rival 3D-plans is being performed.

Predicting the nodal status in gastric cancers: The role of apparent diffusion coefficient histogram characteristic analysis.

Science.gov (United States)

Liu, Song; Zhang, Yujuan; Xia, Jie; Chen, Ling; Guan, Wenxian; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang

2017-10-01

To explore the application of histogram analysis in preoperative T and N staging of gastric cancers, with a focus on characteristic parameters of apparent diffusion coefficient (ADC) maps. Eighty-seven patients with gastric cancers underwent diffusion weighted magnetic resonance imaging (b=0, 1000s/mm 2 ), which generated ADC maps. Whole-volume histogram analysis was performed on ADC maps and 7 characteristic parameters were obtained. All those patients underwent surgery and postoperative pathologic T and N stages were determined. Four parameters, including skew, kurtosis, s-sD av and sample number, showed significant differences among gastric cancers at different T and N stages. Most parameters correlated with T and N stages significantly and worked in differentiating gastric cancers at different T or N stages. Especially skew yielded a sensitivity of 0.758, a specificity of 0.810, and an area under the curve (AUC) of 0.802 for differentiating gastric cancers with and without lymph node metastasis (Phistogram analysis could help assessing preoperative T and N stages of gastric cancers. Copyright © 2017. Published by Elsevier Inc.

Retrospective Reconstructions of Active Bone Marrow Dose-Volume Histograms

International Nuclear Information System (INIS)

Veres, Cristina; Allodji, Rodrigue S.; Llanas, Damien; Vu Bezin, Jérémi; Chavaudra, Jean; Mège, Jean Pierre; Lefkopoulos, Dimitri; Quiniou, Eric; Deutsh, Eric; Vathaire, Florent de; Diallo, Ibrahima

2014-01-01

Purpose: To present a method for calculating dose-volume histograms (DVH's) to the active bone marrow (ABM) of patients who had undergone radiation therapy (RT) and subsequently developed leukemia. Methods and Materials: The study focuses on 15 patients treated between 1961 and 1996. Whole-body RT planning computed tomographic (CT) data were not available. We therefore generated representative whole-body CTs similar to patient anatomy. In addition, we developed a method enabling us to obtain information on the density distribution of ABM all over the skeleton. Dose could then be calculated in a series of points distributed all over the skeleton in such a way that their local density reflected age-specific data for ABM distribution. Dose to particular regions and dose-volume histograms of the entire ABM were estimated for all patients. Results: Depending on patient age, the total number of dose calculation points generated ranged from 1,190,970 to 4,108,524. The average dose to ABM ranged from 0.3 to 16.4 Gy. Dose-volume histograms analysis showed that the median doses (D 50% ) ranged from 0.06 to 12.8 Gy. We also evaluated the inhomogeneity of individual patient ABM dose distribution according to clinical situation. It was evident that the coefficient of variation of the dose for the whole ABM ranged from 1.0 to 5.7, which means that the standard deviation could be more than 5 times higher than the mean. Conclusions: For patients with available long-term follow-up data, our method provides reconstruction of dose-volume data comparable to detailed dose calculations, which have become standard in modern CT-based 3-dimensional RT planning. Our strategy of using dose-volume histograms offers new perspectives to retrospective epidemiological studies

Color Histogram Diffusion for Image Enhancement

Science.gov (United States)

Kim, Taemin

2011-01-01

Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

Improved LSB matching steganography with histogram characters reserved

Science.gov (United States)

Chen, Zhihong; Liu, Wenyao

2008-03-01

This letter bases on the researches of LSB (least significant bit, i.e. the last bit of a binary pixel value) matching steganographic method and the steganalytic method which aims at histograms of cover images, and proposes a modification to LSB matching. In the LSB matching, if the LSB of the next cover pixel matches the next bit of secret data, do nothing; otherwise, choose to add or subtract one from the cover pixel value at random. In our improved method, a steganographic information table is defined and records the changes which embedded secrete bits introduce in. Through the table, the next LSB which has the same pixel value will be judged to add or subtract one dynamically in order to ensure the histogram's change of cover image is minimized. Therefore, the modified method allows embedding the same payload as the LSB matching but with improved steganographic security and less vulnerability to attacks compared with LSB matching. The experimental results of the new method show that the histograms maintain their attributes, such as peak values and alternative trends, in an acceptable degree and have better performance than LSB matching in the respects of histogram distortion and resistance against existing steganalysis.

Motor Oil Classification using Color Histograms and Pattern Recognition Techniques.

Science.gov (United States)

Ahmadi, Shiva; Mani-Varnosfaderani, Ahmad; Habibi, Biuck

2018-04-20

Motor oil classification is important for quality control and the identification of oil adulteration. In thiswork, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histograms and their combinations were used as input for model development and then were statistically evaluated by using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and support vector machine (SVM) techniques. Here, two common solutions for solving a multiclass classification problem were applied: (1) transformation to binary classification problem using a one-against-all (OAA) approach and (2) extension from binary classifiers to a single globally optimized multilabel classification model. In the OAA strategy, LDA, QDA, and SVM reached up to 97% in terms of accuracy, sensitivity, and specificity for both the training and test sets. In extension from binary case, despite good performances by the SVM classification model, QDA and LDA provided better results up to 92% for RGB-grayscale-HSI color histograms and up to 93% for the HSI color map, respectively. In order to reduce the numbers of independent variables for modeling, a principle component analysis algorithm was used. Our results suggest that the proposed method is promising for the identification and classification of different types of motor oils.

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

Science.gov (United States)

Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu

2016-06-01

We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.

Investigating Student Understanding of Histograms

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Kaplan, Jennifer J.; Gabrosek, John G.; Curtiss, Phyllis; Malone, Chris

2014-01-01

Histograms are adept at revealing the distribution of data values, especially the shape of the distribution and any outlier values. They are included in introductory statistics texts, research methods texts, and in the popular press, yet students often have difficulty interpreting the information conveyed by a histogram. This research identifies…

Response evaluation of giant-cell tumor of bone treated by denosumab: Histogram and texture analysis of CT images.

Science.gov (United States)

Yi, Jisook; Lee, Young Han; Kim, Sang Kyum; Kim, Seung Hyun; Song, Ho-Taek; Shin, Kyoo-Ho; Suh, Jin-Suck

2018-05-01

This study aimed to compare computed tomography (CT) features, including tumor size and textural and histogram measurements, of giant-cell tumors of bone (GCTBs) before and after denosumab treatment and determine their applicability in monitoring GCTB response to denosumab treatment. This retrospective study included eight patients (male, 3; female, 5; mean age, 33.4 years) diagnosed with GCTB, who had received treatment by denosumab and had undergone pre- and post-treatment non-contrast CT between January 2010 and December 2016. This study was approved by the institutional review board. Pre- and post-treatment size, histogram, and textural parameters of GCTBs were compared by the Wilcoxon signed-rank test. Pathological findings of five patients who underwent surgery after denosumab treatment were evaluated for assessment of treatment response. Relative to the baseline values, the tumor size had decreased, while the mean attenuation, standard deviation, entropy (all, P = 0.017), and skewness (P = 0.036) of the GCTBs had significantly increased post-treatment. Although the difference was statistically insignificant, the tumors also exhibited increased kurtosis, contrast, and inverse difference moment (P = 0.123, 0.327, and 0.575, respectively) post-treatment. Histologic findings revealed new bone formation and complete depletion or decrease in the number of osteoclast-like giant cells. The histogram and textural parameters of GCTBs changed significantly after denosumab treatment. Knowledge of the tendency towards increased mean attenuation and heterogeneity but increased local homogeneity in post-treatment CT histogram and textural features of GCTBs might aid in treatment planning and tumor response evaluation during denosumab treatment. Copyright © 2018. Published by Elsevier B.V.

Histogram deconvolution - An aid to automated classifiers

Science.gov (United States)

Lorre, J. J.

1983-01-01

It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.

An alternative to γ histograms for ROI-based quantitative dose comparisons

International Nuclear Information System (INIS)

Dvorak, P

2009-01-01

An alternative to gamma (γ) histograms for ROI-based quantitative comparisons of dose distributions using the γ concept is proposed. The method provides minimum values of dose difference and distance-to-agreement such that a pre-set fraction of the region of interest passes the γ test. Compared to standard γ histograms, the method provides more information in terms of pass rate per γ calculation. This is achieved at negligible additional calculation cost and without loss of accuracy. The presented method is proposed as a useful and complementary alternative to standard γ histograms, increasing both the quantity and quality of information for use in acceptance or rejection decisions. (note)

Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

Science.gov (United States)

Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-06-14

Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong

2016-09-17

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD-based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stochastic learning framework, we have one triplet of bags, including one basic bag, one positive bag, and one negative bag. These bags are mapped to histograms using a multi-instance dictionary. We argue that the EMD between the basic histogram and the positive histogram should be smaller than that between the basic histogram and the negative histogram. Base on this condition, we design a hinge loss. By minimizing this hinge loss and some regularization terms of the dictionary, we update the dictionary instances. The experiments over multi-instance retrieval applications shows its effectiveness when compared to other dictionary learning methods over the problems of medical image retrieval and natural language relation classification. © 2016 The Natural Computing Applications Forum

Non-small cell lung cancer: Whole-lesion histogram analysis of the apparent diffusion coefficient for assessment of tumor grade, lymphovascular invasion and pleural invasion.

Science.gov (United States)

Tsuchiya, Naoko; Doai, Mariko; Usuda, Katsuo; Uramoto, Hidetaka; Tonami, Hisao

2017-01-01

Investigating the diagnostic accuracy of histogram analyses of apparent diffusion coefficient (ADC) values for determining non-small cell lung cancer (NSCLC) tumor grades, lymphovascular invasion, and pleural invasion. We studied 60 surgically diagnosed NSCLC patients. Diffusion-weighted imaging (DWI) was performed in the axial plane using a navigator-triggered single-shot, echo-planar imaging sequence with prospective acquisition correction. The ADC maps were generated, and we placed a volume-of-interest on the tumor to construct the whole-lesion histogram. Using the histogram, we calculated the mean, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC, skewness, and kurtosis. Histogram parameters were correlated with tumor grade, lymphovascular invasion, and pleural invasion. We performed a receiver operating characteristics (ROC) analysis to assess the diagnostic performance of histogram parameters for distinguishing different pathologic features. The ADC mean, 10th, 25th, 50th, 75th, 90th, and 95th percentiles showed significant differences among the tumor grades. The ADC mean, 25th, 50th, 75th, 90th, and 95th percentiles were significant histogram parameters between high- and low-grade tumors. The ROC analysis between high- and low-grade tumors showed that the 95th percentile ADC achieved the highest area under curve (AUC) at 0.74. Lymphovascular invasion was associated with the ADC mean, 50th, 75th, 90th, and 95th percentiles, skewness, and kurtosis. Kurtosis achieved the highest AUC at 0.809. Pleural invasion was only associated with skewness, with the AUC of 0.648. ADC histogram analyses on the basis of the entire tumor volume are able to stratify NSCLCs' tumor grade, lymphovascular invasion and pleural invasion.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Science.gov (United States)

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

Directory of Open Access Journals (Sweden)

Liyun Zhuang

2017-01-01

Full Text Available This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE, which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE. Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance.

Science.gov (United States)

Zhuang, Liyun; Guan, Yepeng

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image.

Measuring the apparent diffusion coefficient in primary rectal tumors: is there a benefit in performing histogram analyses?

Science.gov (United States)

van Heeswijk, Miriam M; Lambregts, Doenja M J; Maas, Monique; Lahaye, Max J; Ayas, Z; Slenter, Jos M G M; Beets, Geerard L; Bakers, Frans C H; Beets-Tan, Regina G H

2017-06-01

The apparent diffusion coefficient (ADC) is a potential prognostic imaging marker in rectal cancer. Typically, mean ADC values are used, derived from precise manual whole-volume tumor delineations by experts. The aim was first to explore whether non-precise circular delineation combined with histogram analysis can be a less cumbersome alternative to acquire similar ADC measurements and second to explore whether histogram analyses provide additional prognostic information. Thirty-seven patients who underwent a primary staging MRI including diffusion-weighted imaging (DWI; b0, 25, 50, 100, 500, 1000; 1.5 T) were included. Volumes-of-interest (VOIs) were drawn on b1000-DWI: (a) precise delineation, manually tracing tumor boundaries (2 expert readers), and (b) non-precise delineation, drawing circular VOIs with a wide margin around the tumor (2 non-experts). Mean ADC and histogram metrics (mean, min, max, median, SD, skewness, kurtosis, 5th-95th percentiles) were derived from the VOIs and delineation time was recorded. Measurements were compared between the two methods and correlated with prognostic outcome parameters. Median delineation time reduced from 47-165 s (precise) to 21-43 s (non-precise). The 45th percentile of the non-precise delineation showed the best correlation with the mean ADC from the precise delineation as the reference standard (ICC 0.71-0.75). None of the mean ADC or histogram parameters showed significant prognostic value; only the total tumor volume (VOI) was significantly larger in patients with positive clinical N stage and mesorectal fascia involvement. When performing non-precise tumor delineation, histogram analysis (in specific 45th ADC percentile) may be used as an alternative to obtain similar ADC values as with precise whole tumor delineation. Histogram analyses are not beneficial to obtain additional prognostic information.

Efficient contrast enhancement through log-power histogram modification

NARCIS (Netherlands)

Wu, T.; Toet, A.

2014-01-01

A simple power-logarithm histogram modification operator is proposed to enhance digital image contrast. First a logarithm operator reduces the effect of spikes and transforms the image histogram into a smoothed one that approximates a uniform histogram while retaining the relative size ordering of

HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo; Vestergaard, Jacob Schack; Larsen, Rasmus

2014-01-01

We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order image structure at multiple scales. Moreover, we...... datasets. Our results show that shape index histograms are superior to other popular texture descriptors for HEp-2 cell classification. Moreover, when comparing to other automated systems for HEp-2 cell classification we show that shape index histograms are very competitive; especially considering...

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

Science.gov (United States)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

Background estimation and player detection in badminton video clips using histogram of pixel values along temporal dimension

Science.gov (United States)

Peng, Yahui; Ma, Xiao; Gao, Xinyu; Zhou, Fangxu

2015-12-01

Computer vision is an important tool for sports video processing. However, its application in badminton match analysis is very limited. In this study, we proposed a straightforward but robust histogram-based background estimation and player detection methods for badminton video clips, and compared the results with the naive averaging method and the mixture of Gaussians methods, respectively. The proposed method yielded better background estimation results than the naive averaging method and more accurate player detection results than the mixture of Gaussians player detection method. The preliminary results indicated that the proposed histogram-based method could estimate the background and extract the players accurately. We conclude that the proposed method can be used for badminton player tracking and further studies are warranted for automated match analysis.

Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

Directory of Open Access Journals (Sweden)

Bineng Zhong

2008-06-01

Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram.

Science.gov (United States)

Jung, Younhyun; Kim, Jinman; Kumar, Ashnil; Feng, David Dagan; Fulham, Michael

2016-07-01

'Visibility' is a fundamental optical property that represents the observable, by users, proportion of the voxels in a volume during interactive volume rendering. The manipulation of this 'visibility' improves the volume rendering processes; for instance by ensuring the visibility of regions of interest (ROIs) or by guiding the identification of an optimal rendering view-point. The construction of visibility histograms (VHs), which represent the distribution of all the visibility of all voxels in the rendered volume, enables users to explore the volume with real-time feedback about occlusion patterns among spatially related structures during volume rendering manipulations. Volume rendered medical images have been a primary beneficiary of VH given the need to ensure that specific ROIs are visible relative to the surrounding structures, e.g. the visualisation of tumours that may otherwise be occluded by neighbouring structures. VH construction and its subsequent manipulations, however, are computationally expensive due to the histogram binning of the visibilities. This limits the real-time application of VH to medical images that have large intensity ranges and volume dimensions and require a large number of histogram bins. In this study, we introduce an efficient adaptive binned visibility histogram (AB-VH) in which a smaller number of histogram bins are used to represent the visibility distribution of the full VH. We adaptively bin medical images by using a cluster analysis algorithm that groups the voxels according to their intensity similarities into a smaller subset of bins while preserving the distribution of the intensity range of the original images. We increase efficiency by exploiting the parallel computation and multiple render targets (MRT) extension of the modern graphical processing units (GPUs) and this enables efficient computation of the histogram. We show the application of our method to single-modality computed tomography (CT), magnetic resonance

WORKER, a program for histogram manipulation

International Nuclear Information System (INIS)

Bolger, J.E.; Ellinger, H.; Moore, C.F.

1979-01-01

A set of programs is provided which may link to any user-written program, permitting dynamic creation of histograms as well as display, manipulation and transfer of histogrammed data. With wide flexibility, constants within the user's code may be set or monitored at any time during execution. (Auth.)

System for histogram entry, retrieval, and plotting

International Nuclear Information System (INIS)

Kellogg, M.; Gallup, J.M.; Shlaer, S.; Spencer, N.

1977-10-01

This manual describes the systems for producing histograms and dot plots that were designed for use in connection with the Q general-purpose data-acquisition system. These systems allow for the creation of histograms; the entry, retrieval, and plotting of data in the form of histograms; and the dynamic display of scatter plots as data are acquired. Although the systems are designed for use with Q, they can also be used as a part of other applications. 3 figures

Interpretation of erythrocyte histograms obtained from automated hematology analyzers in hematologic diseases

Directory of Open Access Journals (Sweden)

Ali Maleki

2015-12-01

Full Text Available Background: Presently, the graphical data of blood cells (histograms and cytograms or/ scattergrams that they are usually available in all modern automated hematology analyzers are an integral a part of automated complete blood count (CBC. To find incorrect results from automated hematology analyzer and establish the samples that require additional analysis, Laboratory employees will use those data for quality control of obtaining results, to assist identification of complex and troublesome cases. Methods: During this descriptive analytic study, in addition to erythrocyte graphs from variety of patients, referring from March 2013 to Feb 2014 to our clinical laboratory, Zagros Hospital, Kermanshah, Iran, are given, the papers published in relevant literature as well as available published manuals of automatic blood cell counters were used. articles related to the key words of erythrocyte graphs and relevant literature as well as available published manuals of automatic blood cell counters were searched from valid databases such as Springer Link, google scholar, Pubmed and Sciencedirect. Then, the articles related to erythrogram, erythrocyte histogram and hematology analyzer graphs are involved in diagnosis of hematological disorder were searched and selected for this study. Results: Histograms and different automated CBC parameter become abnormal in various pathologic conditions, and can present important clues for diagnosis and treatment of hematologic and non-hematologic disorders. In several instances, these histograms have characteristic appearances in an exceedingly wide range of pathological conditions. In some hematologic disorders like iron deficiency or megaloblastic anemia, a sequential histogram can clearly show the progressive treatment and management. Conclusion: These graphical data are often accompanied by other automated CBC parameter and microscopic examination of peripheral blood smears (PBS, and can help in monitoring and

Impact of the radiotherapy technique on the correlation between dose–volume histograms of the bladder wall defined on MRI imaging and dose–volume/surface histograms in prostate cancer patients

International Nuclear Information System (INIS)

Maggio, Angelo; Carillo, Viviana; Perna, Lucia; Fiorino, Claudio; Cozzarini, Cesare; Rancati, Tiziana; Valdagni, Riccardo; Gabriele, Pietro

2013-01-01

The aim of this study was to evaluate the correlation between the ‘true’ absolute and relative dose–volume histograms (DVHs) of the bladder wall, dose–wall histogram (DWH) defined on MRI imaging and other surrogates of bladder dosimetry in prostate cancer patients, planned both with 3D-conformal and intensity-modulated radiation therapy (IMRT) techniques. For 17 prostate cancer patients, previously treated with radical intent, CT and MRI scans were acquired and matched. The contours of bladder walls were drawn by using MRI images. External bladder surfaces were then used to generate artificial bladder walls by performing automatic contractions of 5, 7 and 10 mm. For each patient a 3D conformal radiotherapy (3DCRT) and an IMRT treatment plan was generated with a prescription dose of 77.4 Gy (1.8 Gy/fr) and DVH of the whole bladder of the artificial walls (DVH-5/10) and dose–surface histograms (DSHs) were calculated and compared against the DWH in absolute and relative value, for both treatment planning techniques. A specific software (VODCA v. 4.4.0, MSS Inc.) was used for calculating the dose–volume/surface histogram. Correlation was quantified for selected dose–volume/surface parameters by the Spearman correlation coefficient. The agreement between %DWH and DVH5, DVH7 and DVH10 was found to be very good (maximum average deviations below 2%, SD < 5%): DVH5 showed the best agreement. The correlation was slightly better for absolute (R = 0.80–0.94) compared to relative (R = 0.66–0.92) histograms. The DSH was also found to be highly correlated with the DWH, although slightly higher deviations were generally found. The DVH was not a good surrogate of the DWH (R < 0.7 for most of parameters). When comparing the two treatment techniques, more pronounced differences between relative histograms were seen for IMRT with respect to 3DCRT (p < 0.0001). (note)

CHILA A comprehensive histogramming language

International Nuclear Information System (INIS)

Milner, W.T.; Biggerstaff, J.A.

1985-01-01

A high level language, CHIL, has been developed for use in processing event-by-event experimental data at the Holifield Heavy Ion Research Facility (HHIRF) using PERKIN-ELMER 3230 computers. CHIL has been fully integrated into all software which supports on-line and off-line histogramming and off-line preprocessing. CHIL supports simple gates, free-form-gates (2-D regions of arbitrary shape), condition test and branch statements, bit-tests, loops, calls to up to three user supplied subroutines and histogram generating statements. Any combination of 1, 2, 3 or 4-D histograms (32 megachannels max) may be recorded at 16 or 32 bits/channel. User routines may intercept the data being processed and modify it as desired. The CPU-intensive part of the processing utilizes microcoded routines which enhance performance by about a factor of two

CHIL - a comprehensive histogramming language

International Nuclear Information System (INIS)

Milner, W.T.; Biggerstaff, J.A.

1984-01-01

A high level language, CHIL, has been developed for use in processing event-by-event experimental data at the Holifield Heavy Ion Research Facility (HHIRF) using PERKIN-ELMER 3230 computers. CHIL has been fully integrated into all software which supports on-line and off-line histogramming and off-line preprocessing. CHIL supports simple gates, free-form-gates (2-D regions of arbitrary shape), condition test and branch statements, bit-tests, loops, calls to up to three user supplied subroutines and histogram generating statements. Any combination of 1, 2, 3 or 4-D histograms (32 megachannels max) may be recorded at 16 or 32 bits/channel. User routines may intercept the data being processed and modify it as desired. The CPU-intensive part of the processing utilizes microcoded routines which enhance performance by about a factor of two

Comparison of Utility of Histogram Apparent Diffusion Coefficient and R2* for Differentiation of Low-Grade From High-Grade Clear Cell Renal Cell Carcinoma.

Science.gov (United States)

Zhang, Yu-Dong; Wu, Chen-Jiang; Wang, Qing; Zhang, Jing; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin

2015-08-01

The purpose of this study was to compare histogram analysis of apparent diffusion coefficient (ADC) and R2* for differentiating low-grade from high-grade clear cell renal cell carcinoma (RCC). Forty-six patients with pathologically confirmed clear cell RCC underwent preoperative BOLD and DWI MRI of the kidneys. ADCs based on the entire tumor volume were calculated with b value combinations of 0 and 800 s/mm(2). ROI-based R2* was calculated with eight TE combinations of 6.7-22.8 milliseconds. Histogram analysis of tumor ADCs and R2* values was performed to obtain mean; median; width; and fifth, 10th, 90th, and 95th percentiles and histogram inhomogeneity, kurtosis, and skewness for all lesions. Thirty-three low-grade and 13 high-grade clear cell RCCs were found at pathologic examination. The TNM classification and tumor volume of clear cell RCC significantly correlated with histogram ADC and R2* (ρ = -0.317 to 0.506; p histogram ADC and R2* indexes, 10th percentile ADC had the highest accuracy (91.3%) in discriminating low- from high-grade clear cell RCC. R2* in discriminating hemorrhage was achieved with a threshold of 68.95 Hz. At this threshold, high-grade clear cell RCC had a significantly higher prevalence of intratumor hemorrhage (high-grade, 76.9%; low-grade, 45.4%; p Histogram analysis of ADC and R2* allows differentiation of low- from high-grade clear cell RCC with high accuracy.

Liver fibrosis: in vivo evaluation using intravoxel incoherent motion-derived histogram metrics with histopathologic findings at 3.0 T.

Science.gov (United States)

Hu, Fubi; Yang, Ru; Huang, Zixing; Wang, Min; Zhang, Hanmei; Yan, Xu; Song, Bin

2017-12-01

To retrospectively determine the feasibility of intravoxel incoherent motion (IVIM) imaging based on histogram analysis for the staging of liver fibrosis (LF) using histopathologic findings as the reference standard. 56 consecutive patients (14 men, 42 women; age range, 15-76, years) with chronic liver diseases (CLDs) were studied using IVIM-DWI with 9 b-values (0, 25, 50, 75, 100, 150, 200, 500, 800 s/mm 2 ) at 3.0 T. Fibrosis stage was evaluated using the METAVIR scoring system. Histogram metrics including mean, standard deviation (Std), skewness, kurtosis, minimum (Min), maximum (Max), range, interquartile (Iq) range, and percentiles (10, 25, 50, 75, 90th) were extracted from apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps. All histogram metrics among different fibrosis groups were compared using one-way analysis of variance or nonparametric Kruskal-Wallis test. For significant parameters, receivers operating characteristic curve (ROC) analyses were further performed for the staging of LF. Based on their METAVIR stage, the 56 patients were reclassified into three groups as follows: F0-1 group (n = 25), F2-3 group (n = 21), and F4 group (n = 10). The mean, Iq range, percentiles (50, 75, and 90th) of D* maps between the groups were significant differences (all P histogram metrics of ADC, D, and f maps demonstrated no significant difference among the groups (all P > 0.05). Histogram analysis of D* map derived from IVIM can be used to stage liver fibrosis in patients with CLDs and provide more quantitative information beyond the mean value.

Infrared face recognition based on LBP histogram and KW feature selection

Science.gov (United States)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

Differentiating between Central Nervous System Lymphoma and High-grade Glioma Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced MR Imaging with Histogram Analysis.

Science.gov (United States)

Murayama, Kazuhiro; Nishiyama, Yuya; Hirose, Yuichi; Abe, Masato; Ohyu, Shigeharu; Ninomiya, Ayako; Fukuba, Takashi; Katada, Kazuhiro; Toyama, Hiroshi

2018-01-10

We evaluated the diagnostic performance of histogram analysis of data from a combination of dynamic susceptibility contrast (DSC)-MRI and dynamic contrast-enhanced (DCE)-MRI for quantitative differentiation between central nervous system lymphoma (CNSL) and high-grade glioma (HGG), with the aim of identifying useful perfusion parameters as objective radiological markers for differentiating between them. Eight lesions with CNSLs and 15 with HGGs who underwent MRI examination, including DCE and DSC-MRI, were enrolled in our retrospective study. DSC-MRI provides a corrected cerebral blood volume (cCBV), and DCE-MRI provides a volume transfer coefficient (K trans ) for transfer from plasma to the extravascular extracellular space. K trans and cCBV were measured from a round region-of-interest in the slice of maximum size on the contrast-enhanced lesion. The differences in t values between CNSL and HGG for determining the most appropriate percentile of K trans and cCBV were investigated. The differences in K trans , cCBV, and K trans /cCBV between CNSL and HGG were investigated using histogram analysis. Receiver operating characteristic (ROC) analysis of K trans , cCBV, and K trans /cCBV ratio was performed. The 30 th percentile (C30) in K trans and 80 th percentile (C80) in cCBV were the most appropriate percentiles for distinguishing between CNSL and HGG from the differences in t values. CNSL showed significantly lower C80 cCBV, significantly higher C30 K trans , and significantly higher C30 K trans /C80 cCBV than those of HGG. In ROC analysis, C30 K trans /C80 cCBV had the best discriminative value for differentiating between CNSL and HGG as compared to C30 K trans or C80 cCBV. The combination of K trans by DCE-MRI and cCBV by DSC-MRI was found to reveal the characteristics of vascularity and permeability of a lesion more precisely than either K trans or cCBV alone. Histogram analysis of these vascular microenvironments enabled quantitative differentiation between

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma.

Science.gov (United States)

Surov, Alexey; Meyer, Hans Jonas; Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-05-04

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADC min , ADC median , ADC mode , P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADC mean , ADC min , ADC median , and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADC mean , ADC min , ADC median , P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading.

The Research of Histogram Enhancement Technique Based on Matlab Software

Directory of Open Access Journals (Sweden)

Li Kai

2014-08-01

Full Text Available Histogram enhancement technique has been widely applied as a typical pattern in digital image processing. The paper is based on Matlab software, through the two ways of histogram equalization and histogram specification technologies to deal with the darker images, using two methods of partial equilibrium and mapping histogram to transform the original histograms, thereby enhanced the image information. The results show that these two kinds of techniques both can significantly improve the image quality and enhance the image feature.

Design and implement of BESIII online histogramming software

International Nuclear Information System (INIS)

Li Fei; Wang Liang; Liu Yingjie; Chinese Academy of Sciences, Beijing; Zhu Kejun; Zhao Jingwei

2007-01-01

The online histogramming software is an important part of the BESIII DAQ (Data Acquisition) system. This article introduces the main requirements and design of the online histogramming software and presents how to produce, transmit and gather histograms in the distributed environment in the current software implement. The article also illustrate one smart, simple and easy to expand way of setup with xml configure database. (authors)

Multispectral histogram normalization contrast enhancement

Science.gov (United States)

Soha, J. M.; Schwartz, A. A.

1979-01-01

A multispectral histogram normalization or decorrelation enhancement which achieves effective color composites by removing interband correlation is described. The enhancement procedure employs either linear or nonlinear transformations to equalize principal component variances. An additional rotation to any set of orthogonal coordinates is thus possible, while full histogram utilization is maintained by avoiding the reintroduction of correlation. For the three-dimensional case, the enhancement procedure may be implemented with a lookup table. An application of the enhancement to Landsat multispectral scanning imagery is presented.

BED-Volume histograms calculation for routine clinical dosimetry in brachytherapy

International Nuclear Information System (INIS)

Galelli, M.; Feroldi, P.

1995-01-01

The consideration of volumes is essential in Brachytherapy clinical dosimetry (I.C.R.U). Indeed, several indices, all based on dose-volume histograms (DVHs), have been designed in order to evaluate: before the therapy the volumetric quality of different possible implant geometries; during the therapy the consistency of the real and the previsional implants. Radiobiological evaluations, considering the dose deposition temporal pattern of treatment, can be usefully added to dosimetric calculations, to compare different treatment schedules. The Linear-Quadratic model is the most used: radiobiological modelisation and Biologically Effective Dose (BED) is principal related dosimetric quantity. Therefore, the consideration of BED-volume histogram (BED-VHs) is a straightforward extension of DVHs. In practice, BED-VHs can help relative comparisons and optimisations in treatment planning when combined to dose-volume histograms. Since 1994 the dosimetric calculations for all the gynecological brachytherapy treatments are performed considering also DVHs and BED-VHs. In this presentation we show the methods of BEDVHs calculation, together with some typical results

Differential diagnosis of normal pressure hydrocephalus by MRI mean diffusivity histogram analysis.

Science.gov (United States)

Ivkovic, M; Liu, B; Ahmed, F; Moore, D; Huang, C; Raj, A; Kovanlikaya, I; Heier, L; Relkin, N

2013-01-01

Accurate diagnosis of normal pressure hydrocephalus is challenging because the clinical symptoms and radiographic appearance of NPH often overlap those of other conditions, including age-related neurodegenerative disorders such as Alzheimer and Parkinson diseases. We hypothesized that radiologic differences between NPH and AD/PD can be characterized by a robust and objective MR imaging DTI technique that does not require intersubject image registration or operator-defined regions of interest, thus avoiding many pitfalls common in DTI methods. We collected 3T DTI data from 15 patients with probable NPH and 25 controls with AD, PD, or dementia with Lewy bodies. We developed a parametric model for the shape of intracranial mean diffusivity histograms that separates brain and ventricular components from a third component composed mostly of partial volume voxels. To accurately fit the shape of the third component, we constructed a parametric function named the generalized Voss-Dyke function. We then examined the use of the fitting parameters for the differential diagnosis of NPH from AD, PD, and DLB. Using parameters for the MD histogram shape, we distinguished clinically probable NPH from the 3 other disorders with 86% sensitivity and 96% specificity. The technique yielded 86% sensitivity and 88% specificity when differentiating NPH from AD only. An adequate parametric model for the shape of intracranial MD histograms can distinguish NPH from AD, PD, or DLB with high sensitivity and specificity.

ANALISA PENINGKATAN KUALITAS CITRA BAWAH AIR BERBASIS KOREKSI GAMMA dan HISTOGRAM EQUALIZATION

Directory of Open Access Journals (Sweden)

Aria Hendrawan

2016-11-01

Full Text Available Underwater image of water quality in the dark, it depends on the depth of water at the time of image acquisition or image. The results of the image quality is adversely affecting the results matching the image pairs underwater with SIFT algorithm. This research aims to use the method of image preprocessing and Histogram Equalization Gamma Correction that works to improve the quality of images underwater. The results showed 27.76% increase using image preprocessing Gamma Correction and Histogram Equalization compared with no increase in image quality. Results of paired t-test has the null hypothesis is rejected so that there is a significant difference between the application of Gamma Correction Histogram Equalization with and without image enhancement.

Subtracting and Fitting Histograms using Profile Likelihood

CERN Document Server

D'Almeida, F M L

2008-01-01

It is known that many interesting signals expected at LHC are of unknown shape and strongly contaminated by background events. These signals will be dif cult to detect during the rst years of LHC operation due to the initial low luminosity. In this work, one presents a method of subtracting histograms based on the pro le likelihood function when the background is previously estimated by Monte Carlo events and one has low statistics. Estimators for the signal in each bin of the histogram difference are calculated so as limits for the signals with 68.3% of Con dence Level in a low statistics case when one has a exponential background and a Gaussian signal. The method can also be used to t histograms when the signal shape is known. Our results show a good performance and avoid the problem of negative values when subtracting histograms.

DPAK and HPAK: a versatile display and histogramming package

International Nuclear Information System (INIS)

Logg, C.A.; Boyarski, A.M.; Cook, A.J.; Cottrell, R.L.A.; Sund, S.

1979-07-01

The features of a display and histogram package which requires a minimal number of subroutine calls in order to generate graphic output in many flavors on a variety of devices are described. Default options are preset to values that are generally most wanted, but the default values may be readily changed to the user's needs. The description falls naturally into two parts, namely, the set of routines (DPAK) for displaying data on some device, and the set of routines (HPAK) for generating histograms. HPAK provides a means of allocating memory for histograms, accumulating data into histograms, and subsequently displaying the hisotgrams via calls to the DPAK routines. Histograms and displays of either one or two independent variables can be made

Steganalytic methods for the detection of histogram shifting data-hiding schemes

OpenAIRE

Lerch Hostalot, Daniel

2011-01-01

In this paper, some steganalytic techniques designed to detect the existence of hidden messages using histogram shifting methods are presented. Firstly, some techniques to identify specific methods of histogram shifting, based on visible marks on the histogram or abnormal statistical distributions are suggested. Then, we present a general technique capable of detecting all histogram shifting techniques analyzed. This technique is based on the effect of histogram shifting methods on the "volat...

Regionally adaptive histogram equalization of the chest

International Nuclear Information System (INIS)

Sherrier, R.H.; Johnson, G.A.

1986-01-01

Advances in digital chest radiography have resulted in the acquisition of high-quality digital images of the human chest. With these advances, there arises a genuine need for image processing algorithms, specific to chest images. The author has implemented the technique of histogram equalization, noting the problems encountered when it is adapted to chest images. These problems have been successfully solved with a regionally adaptive histogram equalization method. Histograms are calculated locally and then modified according to both the mean pixel value of a given region and certain characteristics of the cumulative distribution function. The method allows certain regions of the chest radiograph to be enhanced differentially

SU-C-207A-07: Cumulative 18F-FDG Uptake Histogram Relative to Radiation Dose Volume Histogram of Lung After IMRT Or PSPT and Their Association with Radiation Pneumonitis

International Nuclear Information System (INIS)

Shusharina, N; Choi, N; Bortfeld, T; Liao, Z; Mohan, R

2016-01-01

Purpose: To determine whether the difference in cumulative 18F-FDG uptake histogram of lung treated with either IMRT or PSPT is associated with radiation pneumonitis (RP) in patients with inoperable stage II and III NSCLC. Methods: We analyzed 24 patients from a prospective randomized trial to compare IMRT (n=12) with vs. PSPT (n=12) for inoperable NSCLC. All patients underwent PET-CT imaging between 35 and 88 days post-therapy. Post-treatment PET-CT was aligned with planning 4D CT to establish a voxel-to-voxel correspondence between post-treatment PET and planning dose images. 18F-FDG uptake as a function of radiation dose to normal lung was obtained for each patient. Distribution of the standard uptake value (SUV) was analyzed using a volume histogram method. The image quantitative characteristics and DVH measures were correlated with clinical symptoms of pneumonitis. Results: Patients with RP were present in both groups: 5 in the IMRT and 6 in the PSPT. The analysis of cumulative SUV histograms showed significantly higher relative volumes of the normal lung having higher SUV uptake in the PSPT patients for both symptomatic and asymptomatic cases (VSUV=2: 10% for IMRT vs 16% for proton RT and VSUV=1: 10% for IMRT vs 23% for proton RT). In addition, the SUV histograms for symptomatic cases in PSPT patients exhibited a significantly longer tail at the highest SUV. The absolute volume of the lung receiving the dose >70 Gy was larger in the PSPT patients. Conclusion: 18F-FDG uptake – radiation dose response correlates with RP in both groups of patients by means of the linear regression slope. SUV is higher for the PSPT patients for both symptomatic and asymptomatic cases. Higher uptake after PSPT patients is explained by larger volumes of the lung receiving high radiation dose.

Histogram Equalization to Model Adaptation for Robust Speech Recognition

Directory of Open Access Journals (Sweden)

Suh Youngjoo

2010-01-01

Full Text Available We propose a new model adaptation method based on the histogram equalization technique for providing robustness in noisy environments. The trained acoustic mean models of a speech recognizer are adapted into environmentally matched conditions by using the histogram equalization algorithm on a single utterance basis. For more robust speech recognition in the heavily noisy conditions, trained acoustic covariance models are efficiently adapted by the signal-to-noise ratio-dependent linear interpolation between trained covariance models and utterance-level sample covariance models. Speech recognition experiments on both the digit-based Aurora2 task and the large vocabulary-based task showed that the proposed model adaptation approach provides significant performance improvements compared to the baseline speech recognizer trained on the clean speech data.

The equivalent Histograms in clinical practice

International Nuclear Information System (INIS)

Pizarro Trigo, F.; Teijeira Garcia, M.; Zaballos Carrera, S.

2013-01-01

Is frequently abused of The tolerances established for organ at risk [1] in diagrams of standard fractionation (2Gy/session, 5 sessions per week) when applied to Dose-Volume histograms non-standard schema. The purpose of this work is to establish when this abuse may be more important and realize a transformation of fractionation non-standard of histograms dosis-volumen. Is exposed a case that can be useful to make clinical decisions. (Author)

Hand Vein Images Enhancement Based on Local Gray-level Information Histogram

Directory of Open Access Journals (Sweden)

Jun Wang

2015-06-01

Full Text Available Based on the Histogram equalization theory, this paper presents a novel concept of histogram to realize the contrast enhancement of hand vein images, avoiding the lost of topological vein structure or importing the fake vein information. Firstly, we propose the concept of gray-level information histogram, the fundamental characteristic of which is that the amplitudes of the components can objectively reflect the contribution of the gray levels and information to the representation of image information. Then, we propose the histogram equalization method that is composed of an automatic histogram separation module and an intensity transformation module, and the histogram separation module is a combination of the proposed prompt multiple threshold procedure and an optimum peak signal-to-noise (PSNR calculation to separate the histogram into small-scale detail, the use of the intensity transformation module can enhance the vein images with vein topological structure and gray information preservation for each generated sub-histogram. Experimental results show that the proposed method can achieve extremely good contrast enhancement effect.

Value-at-risk estimation with fuzzy histograms

NARCIS (Netherlands)

Almeida, R.J.; Kaymak, U.

2008-01-01

Value at risk (VaR) is a measure for senior management that summarises the financial risk a company faces into one single number. In this paper, we consider the use of fuzzy histograms for quantifying the value-at-risk of a portfolio. It is shown that the use of fuzzy histograms provides a good

Comments on 'Reconsidering the definition of a dose-volume histogram'-dose-mass histogram (DMH) versus dose-volume histogram (DVH) for predicting radiation-induced pneumonitis

International Nuclear Information System (INIS)

Mavroidis, Panayiotis; Plataniotis, Georgios A; Gorka, Magdalena Adamus; Lind, Bengt K

2006-01-01

In a recently published paper (Nioutsikou et al 2005 Phys. Med. Biol. 50 L17) the authors showed that the use of the dose-mass histogram (DMH) concept is a more accurate descriptor of the dose delivered to lung than the traditionally used dose-volume histogram (DVH) concept. Furthermore, they state that if a functional imaging modality could also be registered to the anatomical imaging modality providing a functional weighting across the organ (functional mass) then the more general and realistic concept of the dose-functioning mass histogram (D[F]MH) could be an even more appropriate descriptor. The comments of the present letter to the editor are in line with the basic arguments of that work since their general conclusions appear to be supported by the comparison of the DMH and DVH concepts using radiobiological measures. In this study, it is examined whether the dose-mass histogram (DMH) concept deviated significantly from the widely used dose-volume histogram (DVH) concept regarding the expected lung complications and if there are clinical indications supporting these results. The problem was investigated theoretically by applying two hypothetical dose distributions (Gaussian and semi-Gaussian shaped) on two lungs of uniform and varying densities. The influence of the deviation between DVHs and DMHs on the treatment outcome was estimated by using the relative seriality and LKB models using the Gagliardi et al (2000 Int. J. Radiat. Oncol. Biol. Phys. 46 373) and Seppenwoolde et al (2003 Int. J. Radiat. Oncol. Biol. Phys. 55 724) parameter sets for radiation pneumonitis, respectively. Furthermore, the biological equivalent of their difference was estimated by the biologically effective uniform dose (D-bar) and equivalent uniform dose (EUD) concepts, respectively. It is shown that the relation between the DVHs and DMHs varies depending on the underlying cell density distribution and the applied dose distribution. However, the range of their deviation in terms of

Bin Ratio-Based Histogram Distances and Their Application to Image Classification.

Science.gov (United States)

Hu, Weiming; Xie, Nianhua; Hu, Ruiguang; Ling, Haibin; Chen, Qiang; Yan, Shuicheng; Maybank, Stephen

2014-12-01

Large variations in image background may cause partial matching and normalization problems for histogram-based representations, i.e., the histograms of the same category may have bins which are significantly different, and normalization may produce large changes in the differences between corresponding bins. In this paper, we deal with this problem by using the ratios between bin values of histograms, rather than bin values' differences which are used in the traditional histogram distances. We propose a bin ratio-based histogram distance (BRD), which is an intra-cross-bin distance, in contrast with previous bin-to-bin distances and cross-bin distances. The BRD is robust to partial matching and histogram normalization, and captures correlations between bins with only a linear computational complexity. We combine the BRD with the ℓ1 histogram distance and the χ(2) histogram distance to generate the ℓ1 BRD and the χ(2) BRD, respectively. These combinations exploit and benefit from the robustness of the BRD under partial matching and the robustness of the ℓ1 and χ(2) distances to small noise. We propose a method for assessing the robustness of histogram distances to partial matching. The BRDs and logistic regression-based histogram fusion are applied to image classification. The experimental results on synthetic data sets show the robustness of the BRDs to partial matching, and the experiments on seven benchmark data sets demonstrate promising results of the BRDs for image classification.

Interpreting Histograms. As Easy as It Seems?

Science.gov (United States)

Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim

2014-01-01

Histograms are widely used, but recent studies have shown that they are not as easy to interpret as it might seem. In this article, we report on three studies on the interpretation of histograms in which we investigated, namely, (1) whether the misinterpretation by university students can be considered to be the result of heuristic reasoning, (2)…

Histogram and gray level co-occurrence matrix on gray-scale ultrasound images for diagnosing lymphocytic thyroiditis.

Science.gov (United States)

Shin, Young Gyung; Yoo, Jaeheung; Kwon, Hyeong Ju; Hong, Jung Hwa; Lee, Hye Sun; Yoon, Jung Hyun; Kim, Eun-Kyung; Moon, Hee Jung; Han, Kyunghwa; Kwak, Jin Young

2016-08-01

The objective of the study was to evaluate whether texture analysis using histogram and gray level co-occurrence matrix (GLCM) parameters can help clinicians diagnose lymphocytic thyroiditis (LT) and differentiate LT according to pathologic grade. The background thyroid pathology of 441 patients was classified into no evidence of LT, chronic LT (CLT), and Hashimoto's thyroiditis (HT). Histogram and GLCM parameters were extracted from the regions of interest on ultrasound. The diagnostic performances of the parameters for diagnosing and differentiating LT were calculated. Of the histogram and GLCM parameters, the mean on histogram had the highest Az (0.63) and VUS (0.303). As the degrees of LT increased, the mean decreased and the standard deviation and entropy increased. The mean on histogram from gray-scale ultrasound showed the best diagnostic performance as a single parameter in differentiating LT according to pathologic grade as well as in diagnosing LT. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spline smoothing of histograms by linear programming

Science.gov (United States)

Bennett, J. O.

1972-01-01

An algorithm for an approximating function to the frequency distribution is obtained from a sample of size n. To obtain the approximating function a histogram is made from the data. Next, Euclidean space approximations to the graph of the histogram using central B-splines as basis elements are obtained by linear programming. The approximating function has area one and is nonnegative.

Using color histogram normalization for recovering chromatic illumination-changed images.

Science.gov (United States)

Pei, S C; Tseng, C L; Wu, C C

2001-11-01

We propose a novel image-recovery method using the covariance matrix of the red-green-blue (R-G-B) color histogram and tensor theories. The image-recovery method is called the color histogram normalization algorithm. It is known that the color histograms of an image taken under varied illuminations are related by a general affine transformation of the R-G-B coordinates when the illumination is changed. We propose a simplified affine model for application with illumination variation. This simplified affine model considers the effects of only three basic forms of distortion: translation, scaling, and rotation. According to this principle, we can estimate the affine transformation matrix necessary to recover images whose color distributions are varied as a result of illumination changes. We compare the normalized color histogram of the standard image with that of the tested image. By performing some operations of simple linear algebra, we can estimate the matrix of the affine transformation between two images under different illuminations. To demonstrate the performance of the proposed algorithm, we divide the experiments into two parts: computer-simulated images and real images corresponding to illumination changes. Simulation results show that the proposed algorithm is effective for both types of images. We also explain the noise-sensitive skew-rotation estimation that exists in the general affine model and demonstrate that the proposed simplified affine model without the use of skew rotation is better than the general affine model for such applications.

Histogram analysis reveals a better delineation of tumor volume from background in 18F-FET PET compared to CBV maps in a hybrid PET–MR studie in gliomas

International Nuclear Information System (INIS)

Filss, Christian P.; Stoffels, Gabriele; Galldiks, Norbert; Sabel, Michael; Wittsack, Hans J.; Coenen, Heinz H.; Shah, Nadim J.; Herzog, Hans

2014-01-01

Anatomical imaging with magnetic resonance imaging (MRI) is currently the method of first choice for diagnostic investigation of glial tumors. However, different MR sequences may over- or underestimate tumor size and thus it may not be possible to delineate tumor from adjacent brain. In order to compensate this confinement additonal MR sequences like perfusion weighted MRI (PWI) with regional cerebral blood volume (rCBV) or positron emission tomography (PET) with aminoacids are used to gain further information. Recent studies suggest that both of theses image modalities provide similar diagnostic information. For comparison tumor to brain ratios (TBR) with mean and maximum values are frequently used but results from different studies can often not be checked against each other. Furthermore, especially the maximum TBR in rCBV is at risk to be falsified by artifacts (e.g. blood vessels). These confinements are reduced by the use of histograms since all information of the VOIs are equally displayed. In this study we measured and compared the intersection of tumor and reference tissue histograms in 18 F-FET PET and rCBV maps in glioma patients. Methods: Twenty-seven glioma patients with contrast enhancing lesion on T1-weighted MR images were investigated using static 18 F-FET PET and rCBV in MRI using a PET–MR hybrid scanner. In all patients diagnosis was confirmed histologically (7 grade II gliomas, 6 grade III gliomas and 14 grade IV gliomas). We generated a set of tumor and reference tissue Volumes-of-Interest (VOIs) based on T1 weighted images in MRI with the tumor VOI defined by contrast enhancement and transferred these VOIs to the corresponding 18 F-FET PET scans and rCBV maps. From these VOIs we generated tumor and reference tissue histograms with a unity of one for each curve integral and measured the proportion of the area under the tumor curve that falls into the reference curve for 18 F-FET PET and rCBV maps for each patient. Results: The mean proportion

Live histograms in moving windows

International Nuclear Information System (INIS)

Zhil'tsov, V.E.

1989-01-01

Application of computer graphics for specific hardware testing is discussed. The hardware is position sensitive detector (multiwire proportional chamber) which is used in high energy physics experiments, and real-out electronics for it. Testing program is described (XPERT), which utilises multi-window user interface. Data are represented as histograms in windows. The windows on the screen may be moved, reordered, their sizes may be changed. Histograms may be put to any window, and hardcopy may be made. Some program internals are discussed. The computer environment is quite simple: MS-DOS IBM PC/XT, 256 KB RAM, CGA, 5.25'' FD, Epson MX. 4 refs.; 7 figs

Multiple histogram method and static Monte Carlo sampling

NARCIS (Netherlands)

Inda, M.A.; Frenkel, D.

2004-01-01

We describe an approach to use multiple-histogram methods in combination with static, biased Monte Carlo simulations. To illustrate this, we computed the force-extension curve of an athermal polymer from multiple histograms constructed in a series of static Rosenbluth Monte Carlo simulations. From

Face recognition algorithm using extended vector quantization histogram features.

Science.gov (United States)

Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

2018-01-01

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Machine assisted histogram classification

Science.gov (United States)

Benyó, B.; Gaspar, C.; Somogyi, P.

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Machine assisted histogram classification

Energy Technology Data Exchange (ETDEWEB)

Benyo, B; Somogyi, P [BME-IIT, H-1117 Budapest, Magyar tudosok koerutja 2. (Hungary); Gaspar, C, E-mail: Peter.Somogyi@cern.c [CERN-PH, CH-1211 Geneve 23 (Switzerland)

2010-04-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty or ageing components can be either done visually using instruments, such as the LHCb Histogram Presenter, or with the help of automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, we propose a graph based clustering tool combined with machine learning algorithm and demonstrate its use by processing histograms representing 2D hitmaps events. We prove the concept by detecting ion feedback events in the LHCb experiment's RICH subdetector.

Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram

Science.gov (United States)

Batra, Marion; Nägele, Thomas

2015-01-01

Purpose. The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered. Methods. Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line. Results. A consistent fitting of the histograms of all age groups was possible with the proposed model. Conclusions. This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects. PMID:26609526

Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram

Directory of Open Access Journals (Sweden)

Uwe Klose

2015-01-01

Full Text Available Purpose. The distribution of apparent diffusion coefficient (ADC values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered. Methods. Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line. Results. A consistent fitting of the histograms of all age groups was possible with the proposed model. Conclusions. This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

Histogram Estimators of Bivariate Densities

National Research Council Canada - National Science Library

Husemann, Joyce A

1986-01-01

One-dimensional fixed-interval histogram estimators of univariate probability density functions are less efficient than the analogous variable-interval estimators which are constructed from intervals...

The CEBAF test package: A symbolic and dynamic test, histogram and parameter package for on- and off-line particle physics data analysis

International Nuclear Information System (INIS)

Wood, S.A.; Abbott, S.

1995-01-01

Nuclear physics data analysis programs often use packages, such as Q, that allow parameter values, test definitions and histogram booking parameters to be controlled at run time through external files or shared memory. Data within a physics analyzer are usually referenced by indices, leading to a high use of equivalence statements and to extra bookkeeping. In the CEBAF Test Package (CTP), parameters, tests and histogram definitions defined in external files all refer to data elements by the same variable names as used in the C or Fortran source code for the analyzer. This is accomplished by requirieng the analyzer developer to open-quotes registerclose quotes each variable and array that is to be accessible by the package. Any registered variable as well as the test and histogram definitions may be dynamically read and modified by tasks that communicate via standard networking calls. As this package is implemented in C and requires only HBOOK and SUN RPC networking, it is highly portable. CTP works with the CEBAF Online Data Acquisition system (CODA), but may be used with other data acquisition systems or stand alone

Apparent diffusion coefficient histogram analysis of neonatal hypoxic-ischemic encephalopathy

International Nuclear Information System (INIS)

Cauley, Keith A.; Filippi, Christopher G.

2014-01-01

Diffusion-weighted imaging is a valuable tool in the assessment of the neonatal brain, and changes in diffusion are seen in normal development as well as in pathological states such as hypoxic-ischemic encephalopathy (HIE). Various methods of quantitative assessment of diffusion values have been reported. Global ischemic injury occurring during the time of rapid developmental changes in brain myelination can complicate the imaging diagnosis of neonatal HIE. To compare a quantitative method of histographic analysis of brain apparent coefficient (ADC) maps to the qualitative interpretation of routine brain MR imaging studies. We correlate changes in diffusion values with gestational age in radiographically normal neonates, and we investigate the sensitivity of the method as a quantitative measure of hypoxic-ischemic encephalopathy. We reviewed all brain MRI studies from the neonatal intensive care unit (NICU) at our university medical center over a 4-year period to identify cases that were radiographically normal (23 cases) and those with diffuse, global hypoxic-ischemic encephalopathy (12 cases). We histographically displayed ADC values of a single brain slice at the level of the basal ganglia and correlated peak (s-sD av ) and lowest histogram values (s-sD lowest ) with gestational age. Normative s-sD av values correlated significantly with gestational age and declined linearly through the neonatal period (r 2 = 0.477, P av and s-sD lowest ADC values than were reflected in the normative distribution; several cases of HIE fell within a 95% confidence interval for normative studies, and one case demonstrated higher-than-normal s-sD av . Single-slice histographic display of ADC values is a rapid and clinically feasible method of quantitative analysis of diffusion. In this study normative values derived from consecutive neonates without radiographic evidence of ischemic injury are correlated with gestational age, declining linearly throughout the perinatal period. This

ACTION RECOGNITION USING SALIENT NEIGHBORING HISTOGRAMS

DEFF Research Database (Denmark)

Ren, Huamin; Moeslund, Thomas B.

2013-01-01

Combining spatio-temporal interest points with Bag-of-Words models achieves state-of-the-art performance in action recognition. However, existing methods based on “bag-ofwords” models either are too local to capture the variance in space/time or fail to solve the ambiguity problem in spatial...... and temporal dimensions. Instead, we propose a salient vocabulary construction algorithm to select visual words from a global point of view, and form compact descriptors to represent discriminative histograms in the neighborhoods. Those salient neighboring histograms are then trained to model different actions...

Modeling Early Postnatal Brain Growth and Development with CT: Changes in the Brain Radiodensity Histogram from Birth to 2 Years.

Science.gov (United States)

Cauley, K A; Hu, Y; Och, J; Yorks, P J; Fielden, S W

2018-04-01

The majority of brain growth and development occur in the first 2 years of life. This study investigated these changes by analysis of the brain radiodensity histogram of head CT scans from the clinical population, 0-2 years of age. One hundred twenty consecutive head CTs with normal findings meeting the inclusion criteria from children from birth to 2 years were retrospectively identified from 3 different CT scan platforms. Histogram analysis was performed on brain-extracted images, and histogram mean, mode, full width at half maximum, skewness, kurtosis, and SD were correlated with subject age. The effects of scan platform were investigated. Normative curves were fitted by polynomial regression analysis. Average total brain volume was 360 cm 3 at birth, 948 cm 3 at 1 year, and 1072 cm 3 at 2 years. Total brain tissue density showed an 11% increase in mean density at 1 year and 19% at 2 years. Brain radiodensity histogram skewness was positive at birth, declining logarithmically in the first 200 days of life. The histogram kurtosis also decreased in the first 200 days to approach a normal distribution. Direct segmentation of CT images showed that changes in brain radiodensity histogram skewness correlated with, and can be explained by, a relative increase in gray matter volume and an increase in gray and white matter tissue density that occurs during this period of brain maturation. Normative metrics of the brain radiodensity histogram derived from routine clinical head CT images can be used to develop a model of normal brain development. © 2018 by American Journal of Neuroradiology.

Measuring kinetics of complex single ion channel data using mean-variance histograms.

Science.gov (United States)

Patlak, J B

1993-07-01

The measurement of single ion channel kinetics is difficult when those channels exhibit subconductance events. When the kinetics are fast, and when the current magnitudes are small, as is the case for Na+, Ca2+, and some K+ channels, these difficulties can lead to serious errors in the estimation of channel kinetics. I present here a method, based on the construction and analysis of mean-variance histograms, that can overcome these problems. A mean-variance histogram is constructed by calculating the mean current and the current variance within a brief "window" (a set of N consecutive data samples) superimposed on the digitized raw channel data. Systematic movement of this window over the data produces large numbers of mean-variance pairs which can be assembled into a two-dimensional histogram. Defined current levels (open, closed, or sublevel) appear in such plots as low variance regions. The total number of events in such low variance regions is estimated by curve fitting and plotted as a function of window width. This function decreases with the same time constants as the original dwell time probability distribution for each of the regions. The method can therefore be used: 1) to present a qualitative summary of the single channel data from which the signal-to-noise ratio, open channel noise, steadiness of the baseline, and number of conductance levels can be quickly determined; 2) to quantify the dwell time distribution in each of the levels exhibited. In this paper I present the analysis of a Na+ channel recording that had a number of complexities. The signal-to-noise ratio was only about 8 for the main open state, open channel noise, and fast flickers to other states were present, as were a substantial number of subconductance states. "Standard" half-amplitude threshold analysis of these data produce open and closed time histograms that were well fitted by the sum of two exponentials, but with apparently erroneous time constants, whereas the mean

Content Based Radiographic Images Indexing and Retrieval Using Pattern Orientation Histogram

Directory of Open Access Journals (Sweden)

Abolfazl Lakdashti

2008-06-01

Full Text Available Introduction: Content Based Image Retrieval (CBIR is a method of image searching and retrieval in a  database. In medical applications, CBIR is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. As the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retrieval is increasingly  becoming a necessity.  Materials and Methods: This paper presents a new content based radiographic image retrieval approach  based on histogram of pattern orientations, namely pattern orientation histogram (POH. POH represents  the  spatial  distribution  of  five  different  pattern  orientations:  vertical,  horizontal,  diagonal  down/left,  diagonal down/right and non-orientation. In this method, a given image is first divided into image-blocks  and  the  frequency  of  each  type  of  pattern  is  determined  in  each  image-block.  Then,  local  pattern  histograms for each of these image-blocks are computed.   Results: The method was compared to two well known texture-based image retrieval methods: Tamura  and  Edge  Histogram  Descriptors  (EHD  in  MPEG-7  standard.  Experimental  results  based  on  10000  IRMA  radiography  image  dataset,  demonstrate  that  POH  provides  better  precision  and  recall  rates  compared to Tamura and EHD. For some images, the recall and precision rates obtained by POH are,  respectively, 48% and 18% better than the best of the two above mentioned methods.    Discussion and Conclusion: Since we exploit the absolute location of the pattern in the image as well as  its global composition, the proposed matching method can retrieve semantically similar medical images.

Dose Volume Histogram analysis for rectum and urethral reaction of prostate cancer

International Nuclear Information System (INIS)

Yanagi, Takeshi; Tsuji, Hiroshi; Kamada, Tadashi; Tsujii, Hirohiko

2005-01-01

The aim of this study is to evaluate the clinically relevant parameters for rectum and urethral reaction using DVH (dose volume histogram) in carbon ion radiotherapy of prostate cancer. In this year, we studied the urinary reaction mainly. 35 patients with prostate cancer were treated with carbon ion beams between June 1995 and December 1997. The applied dose was escalated from 54.0 GyE to 72.0 GyE in fixed 20 fractions. Clinical urinary reaction and rectum reaction were reviewed using Radiation Therapy Oncology Group (RTOG) scoring system for acute reactions, RTOG/European Organization for Research and Treatment of Cancer (EORTC) scoring system for late reactions. Taking the ROI (region of interest) for DVH of urethra, we used surrogate one that was derived from the observation of MR images. 35 patients were analyzed for acute urinary reaction and 34 for late urinary reaction in the study of this year. DVH analysis suggested difference among the grades for acute and late reactions. These analysis appears to be a useful tool for predicting the urinary reactions. (author)

A 64 Mbyte VME histogramming memory card for the GA.SP gamma spectrometer

International Nuclear Information System (INIS)

Cavedini, Z.; DePoli, M.; Maron, G.; Vedovato, G.

1990-01-01

This paper reports on a 64 Mbyte VME histogramming memory card designed and built to cover the on-line and off-line data analysis needs of the GA.SP spectrometer (a 40 HpGe gamma detector array in development at LNL). The card combines the standard features of the VME/VSB bus with some special built-in functions: single cycle fast histogramming operations (typical channel increment time of 550 ns including the bus arbitration), fast clear of the whole memory (∼1 second to erase 64 Mbyte) and data broadcasting

Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability.

Science.gov (United States)

Surov, Alexey; Hamerla, Gordian; Meyer, Hans Jonas; Winter, Karsten; Schob, Stefan; Fiedler, Eckhard

2018-09-01

To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma. The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADC mean , ADC max , ADC min , ADC median , ADC mode , ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters. A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADC min . ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4. ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity. Copyright © 2018 Elsevier Inc. All rights reserved.

A monitoring program of the histograms based on ROOT package

International Nuclear Information System (INIS)

Zhou Yongzhao; Liang Hao; Chen Yixin; Xue Jundong; Yang Tao; Gong Datao; Jin Ge; Yu Xiaoqi

2002-01-01

KHBOOK is a histogram monitor and browser based on ROOT package, which reads the histogram file in HBOOK format from Physmon, converts it into ROOT format, and browses the histograms in Repeat and Overlap modes to monitor and trace the quality of the data from DAQ. KHBOOK is a program of small memory, easy maintenance and fast running as well, using mono-behavior classes and a communication class of C ++

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

Science.gov (United States)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

DNA IMAGE CYTOMETRY IN PROGNOSTICATION OF COLORECTAL CANCER: PRACTICAL CONSIDERATIONS OF THE TECHNIQUE AND INTERPRETATION OF THE HISTOGRAMS

Directory of Open Access Journals (Sweden)

Abdelbaset Buhmeida

2011-05-01

Full Text Available The role of DNA content as a prognostic factor in colorectal cancer (CRC is highly controversial. Some of these controversies are due to purely technical reasons, e.g. variable practices in interpreting the DNA histograms, which is problematic particularly in advanced cases. In this report, we give a detailed account on various options how these histograms could be optimally interpreted, with the idea of establishing the potential value of DNA image cytometry in prognosis and in selection of proper treatment. Material consists of nuclei isolated from 50 ƒĘm paraffin sections from 160 patients with stage II, III or IV CRC diagnosed, treated and followed-up in our clinic. The nuclei were stained with the Feulgen stain. Nuclear DNA was measured using computer-assisted image cytometry. We applied 4 different approaches to analyse the DNA histograms: 1 appearance of the histogram (ABCDE approach, 2 range of DNA values, 3 peak evaluation, and 4 events present at high DNA values. Intra-observer reproducibility of these four histogram interpretation was 89%, 95%, 96%, and 100%, respectively. We depicted selected histograms to illustrate the four analytical approaches in cases with different stages of CRC, with variable disease outcome. In our analysis, the range of DNA values was the best prognosticator, i.e., the tumours with the widest histograms had the most ominous prognosis. These data implicate that DNA cytometry based on isolated nuclei is valuable in predicting the prognosis of CRC. Different interpretation techniques differed in their reproducibility, but the method showing the best prognostic value also had high reproducibility in our analysis.

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs).

Science.gov (United States)

Hoffman, David H; Ream, Justin M; Hajdu, Christina H; Rosenkrantz, Andrew B

2017-04-01

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features. Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared. Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10-25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50-78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18-0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004). Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

Potential of MR histogram analyses for prediction of response to chemotherapy in patients with colorectal hepatic metastases.

Science.gov (United States)

Liang, He-Yue; Huang, Ya-Qin; Yang, Zhao-Xia; Ying-Ding; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-07-01

To determine if magnetic resonance imaging (MRI) histogram analyses can help predict response to chemotherapy in patients with colorectal hepatic metastases by using response evaluation criteria in solid tumours (RECIST1.1) as the reference standard. Standard MRI including diffusion-weighted imaging (b=0, 500 s/mm(2)) was performed before chemotherapy in 53 patients with colorectal hepatic metastases. Histograms were performed for apparent diffusion coefficient (ADC) maps, arterial, and portal venous phase images; thereafter, mean, percentiles (1st, 10th, 50th, 90th, 99th), skewness, kurtosis, and variance were generated. Quantitative histogram parameters were compared between responders (partial and complete response, n=15) and non-responders (progressive and stable disease, n=38). Receiver operator characteristics (ROC) analyses were further analyzed for the significant parameters. The mean, 1st percentile, 10th percentile, 50th percentile, 90th percentile, 99th percentile of the ADC maps were significantly lower in responding group than that in non-responding group (p=0.000-0.002) with area under the ROC curve (AUCs) of 0.76-0.82. The histogram parameters of arterial and portal venous phase showed no significant difference (p>0.05) between the two groups. Histogram-derived parameters for ADC maps seem to be a promising tool for predicting response to chemotherapy in patients with colorectal hepatic metastases. • ADC histogram analyses can potentially predict chemotherapy response in colorectal liver metastases. • Lower histogram-derived parameters (mean, percentiles) for ADC tend to have good response. • MR enhancement histogram analyses are not reliable to predict response.

Infrared Contrast Enhancement Through Log-Power Histogram Modification

NARCIS (Netherlands)

Toet, A.; Wu, T.

2015-01-01

A simple power-logarithm histogram modification operator is proposed to enhance infrared (IR) image contrast. The algorithm combines a logarithm operator that smoothes the input image histogram while retaining the relative ordering of the original bins, with a power operator that restores the

PENGARUH HISTOGRAM EQUALIZATION UNTUK PERBAIKAN KUALITAS CITRA DIGITAL

Directory of Open Access Journals (Sweden)

Sisilia Daeng Bakka Mau

2016-04-01

Full Text Available Penelitian ini membahas penggunaan metode histogram equalization yang akan digunakan untuk perbaikan kualitas citra. Perbaikan kualitas citra (image enhancement merupakan salah satu proses awal dalam peningkatan mutu citra. Peningkatan mutu citra diperlukan karena seringkali citra yang dijadikan objek pembahasan mempunyai kualitas yang buruk, misalnya citra mengalami derau, kabur, citra terlalu gelap atau terang, citra kurang tajam dan sebagainya. Perbaikan kualitas citra adalah proses memperjelas dan mempertajam ciri atau fitur tertentu dari citra agar citra lebih mudah dipersepsi maupun dianalisa secara lebih teliti. Hasil penelitian ini membuktikan bahwa penggunaan metode histogram equalization dapat digunakan untuk meningkatkan kontras citra dan dapat meningkatkan kualitas citra, sehingga informasi yang ada pada citra lebih jelas terlihat. Kata kunci: perbaikan kualitas citra, histogram equalization, citra digital

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

Science.gov (United States)

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-04-06

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10 -3 mm 2 /s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

WASP (Write a Scientific Paper) using Excel - 4: Histograms.

Science.gov (United States)

Grech, Victor

2018-02-01

Plotting data into graphs is a crucial step in data analysis as part of an initial descriptive statistics exercise since it gives the researcher an overview of the shape and nature of the data. Outlier values may also be identified, and these may be incorrect data, or true and important outliers. This paper explains how to access Microsoft Excel's Analysis Toolpak and provides some pointers for the utilisation of the histogram tool within the Toolpak. Copyright © 2018. Published by Elsevier B.V.

Visualizing Contour Trees within Histograms

DEFF Research Database (Denmark)

Kraus, Martin

2010-01-01

Many of the topological features of the isosurfaces of a scalar volume field can be compactly represented by its contour tree. Unfortunately, the contour trees of most real-world volume data sets are too complex to be visualized by dot-and-line diagrams. Therefore, we propose a new visualization...... that is suitable for large contour trees and efficiently conveys the topological structure of the most important isosurface components. This visualization is integrated into a histogram of the volume data; thus, it offers strictly more information than a traditional histogram. We present algorithms...... to automatically compute the graph layout and to calculate appropriate approximations of the contour tree and the surface area of the relevant isosurface components. The benefits of this new visualization are demonstrated with the help of several publicly available volume data sets....

LHCb: Machine assisted histogram classification

CERN Multimedia

Somogyi, P; Gaspar, C

2009-01-01

LHCb is one of the four major experiments under completion at the Large Hadron Collider (LHC). Monitoring the quality of the acquired data is important, because it allows the verification of the detector performance. Anomalies, such as missing values or unexpected distributions can be indicators of a malfunctioning detector, resulting in poor data quality. Spotting faulty components can be either done visually using instruments such as the LHCb Histogram Presenter, or by automated tools. In order to assist detector experts in handling the vast monitoring information resulting from the sheer size of the detector, a graph-theoretic based clustering tool, combined with machine learning algorithms is proposed and demonstrated by processing histograms representing 2D event hitmaps. The concept is proven by detecting ion feedback events in the LHCb RICH subdetector.

A New Method of Histogram Computation for Efficient Implementation of the HOG Algorithm

Directory of Open Access Journals (Sweden)

Mariana-Eugenia Ilas

2018-03-01

Full Text Available In this paper we introduce a new histogram computation method to be used within the histogram of oriented gradients (HOG algorithm. The new method replaces the arctangent with the slope computation and the classical magnitude allocation based on interpolation with a simpler algorithm. The new method allows a more efficient implementation of HOG in general, and particularly in field-programmable gate arrays (FPGAs, by considerably reducing the area (thus increasing the level of parallelism, while maintaining very close classification accuracy compared to the original algorithm. Thus, the new method is attractive for many applications, including car detection and classification.

Conductance histogram evolution of an EC-MCBJ fabricated Au atomic point contact

Energy Technology Data Exchange (ETDEWEB)

Yang Yang; Liu Junyang; Chen Zhaobin; Tian Jinghua; Jin Xi; Liu Bo; Yang Fangzu; Tian Zhongqun [State Key Laboratory of Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005 (China); Li Xiulan; Tao Nongjian [Center for Bioelectronics and Biosensors, Biodesign Institute, Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287-6206 (United States); Luo Zhongzi; Lu Miao, E-mail: zqtian@xmu.edu.cn [Micro-Electro-Mechanical Systems Research Center, Pen-Tung Sah Micro-Nano Technology Institute, Xiamen University, Xiamen 361005 (China)

2011-07-08

This work presents a study of Au conductance quantization based on a combined electrochemical deposition and mechanically controllable break junction (MCBJ) method. We describe the microfabrication process and discuss improved features of our microchip structure compared to the previous one. The improved structure prolongs the available life of the microchip and also increases the success rate of the MCBJ experiment. Stepwise changes in the current were observed at the last stage of atomic point contact breakdown and conductance histograms were constructed. The evolution of 1G{sub 0} peak height in conductance histograms was used to investigate the probability of formation of an atomic point contact. It has been shown that the success rate in forming an atomic point contact can be improved by decreasing the stretching speed and the degree that the two electrodes are brought into contact. The repeated breakdown and formation over thousands of cycles led to a distinctive increase of 1G{sub 0} peak height in the conductance histograms, and this increased probability of forming a single atomic point contact is discussed.

Conductance histogram evolution of an EC-MCBJ fabricated Au atomic point contact

International Nuclear Information System (INIS)

Yang Yang; Liu Junyang; Chen Zhaobin; Tian Jinghua; Jin Xi; Liu Bo; Yang Fangzu; Tian Zhongqun; Li Xiulan; Tao Nongjian; Luo Zhongzi; Lu Miao

2011-01-01

This work presents a study of Au conductance quantization based on a combined electrochemical deposition and mechanically controllable break junction (MCBJ) method. We describe the microfabrication process and discuss improved features of our microchip structure compared to the previous one. The improved structure prolongs the available life of the microchip and also increases the success rate of the MCBJ experiment. Stepwise changes in the current were observed at the last stage of atomic point contact breakdown and conductance histograms were constructed. The evolution of 1G 0 peak height in conductance histograms was used to investigate the probability of formation of an atomic point contact. It has been shown that the success rate in forming an atomic point contact can be improved by decreasing the stretching speed and the degree that the two electrodes are brought into contact. The repeated breakdown and formation over thousands of cycles led to a distinctive increase of 1G 0 peak height in the conductance histograms, and this increased probability of forming a single atomic point contact is discussed.

IMPLEMENTASI METODE HISTOGRAM EQUALIZATION UNTUK MENINGKATKAN KUALITAS CITRA DIGITAL

Directory of Open Access Journals (Sweden)

Isa Akhlis

2012-02-01

Full Text Available Radiografi dapat digunakan untuk membantu mendiagnosis penyakit dalam bidang medis. Umumnya citra radiograf masih tampak kabur sehingga memerlukan pengolahan untuk menghilangkan atau mengurangi kekaburan tersebut. Tujuan penelitian ini adalah mendesain perangkat lunak untuk meningkatkan kualitas citra digital foto Roentgen yaitu dengan meningkatkan kontras citra tersebut. Salah satu metode untuk meningkatkan kontras citra digital adalah dengan menggunakan metode histogram equalization. Metoda tersebut membuat tingkat keabuan citra tersebar merata pada semua tingkat keabuan. Hasil penelitian menunjukkan bahwa metoda histogram equalization dapat digunakan untuk meningkatkan kontras citra.  Hal ini dapat langsung dilihat pada layar monitor.   Kata kunci: citra radiograf,  histogram equalization

Comparative analysis of hybridizing histogram equalization ...

African Journals Online (AJOL)

Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 21, No 2 (2014) >. Log in or Register to get access to full text downloads.

Histogram specification as a method of density modification

International Nuclear Information System (INIS)

Harrison, R.W.

1988-01-01

A new method for improving the quality and extending the resolution of Fourier maps is described. The method is based on a histogram analysis of the electron density. The distribution of electron density values in the map is forced to be 'ideal'. The 'ideal' distribution is assumed to be Gaussian. The application of the method to improve the electron density map for the protein Acinetobacter asparaginase, which is a tetrameric enzyme of molecular weight 140000 daltons, is described. (orig.)

Two non-parametric methods for derivation of constraints from radiotherapy dose–histogram data

International Nuclear Information System (INIS)

Ebert, M A; Kennedy, A; Joseph, D J; Gulliford, S L; Buettner, F; Foo, K; Haworth, A; Denham, J W

2014-01-01

Dose constraints based on histograms provide a convenient and widely-used method for informing and guiding radiotherapy treatment planning. Methods of derivation of such constraints are often poorly described. Two non-parametric methods for derivation of constraints are described and investigated in the context of determination of dose-specific cut-points—values of the free parameter (e.g., percentage volume of the irradiated organ) which best reflect resulting changes in complication incidence. A method based on receiver operating characteristic (ROC) analysis and one based on a maximally-selected standardized rank sum are described and compared using rectal toxicity data from a prostate radiotherapy trial. Multiple test corrections are applied using a free step-down resampling algorithm, which accounts for the large number of tests undertaken to search for optimal cut-points and the inherent correlation between dose–histogram points. Both methods provide consistent significant cut-point values, with the rank sum method displaying some sensitivity to the underlying data. The ROC method is simple to implement and can utilize a complication atlas, though an advantage of the rank sum method is the ability to incorporate all complication grades without the need for grade dichotomization. (note)

Enhancing tumor apparent diffusion coefficient histogram skewness stratifies the postoperative survival in recurrent glioblastoma multiforme patients undergoing salvage surgery.

Science.gov (United States)

Zolal, Amir; Juratli, Tareq A; Linn, Jennifer; Podlesek, Dino; Sitoci Ficici, Kerim Hakan; Kitzler, Hagen H; Schackert, Gabriele; Sobottka, Stephan B; Rieger, Bernhard; Krex, Dietmar

2016-05-01

Objective To determine the value of apparent diffusion coefficient (ADC) histogram parameters for the prediction of individual survival in patients undergoing surgery for recurrent glioblastoma (GBM) in a retrospective cohort study. Methods Thirty-one patients who underwent surgery for first recurrence of a known GBM between 2008 and 2012 were included. The following parameters were collected: age, sex, enhancing tumor size, mean ADC, median ADC, ADC skewness, ADC kurtosis and fifth percentile of the ADC histogram, initial progression free survival (PFS), extent of second resection and further adjuvant treatment. The association of these parameters with survival and PFS after second surgery was analyzed using log-rank test and Cox regression. Results Using log-rank test, ADC histogram skewness of the enhancing tumor was significantly associated with both survival (p = 0.001) and PFS after second surgery (p = 0.005). Further parameters associated with prolonged survival after second surgery were: gross total resection at second surgery (p = 0.026), tumor size (0.040) and third surgery (p = 0.003). In the multivariate Cox analysis, ADC histogram skewness was shown to be an independent prognostic factor for survival after second surgery. Conclusion ADC histogram skewness of the enhancing lesion, enhancing lesion size, third surgery, as well as gross total resection have been shown to be associated with survival following the second surgery. ADC histogram skewness was an independent prognostic factor for survival in the multivariate analysis.

HPLOT: the graphics interface package for the HBOOK histogramming package

International Nuclear Information System (INIS)

Watkins, H.

1978-01-01

The subroutine package HPLOT described in this report, enables the CERN histogramming package HBOOK to produce high-quality pictures by means of high-resolution devices such as plotters. HPLOT can be implemented on any scientific computing system with a Fortran IV compiler and can be interfaced with any graphics package; spectral routines in addition to the basic ones enable users to embellish their histograms. Examples are also given of the use of HPLOT as a graphics package for plotting simple pictures without histograms. (Auth.)

Calibration of 14C Histograms : A Comparison of Methods

NARCIS (Netherlands)

Stolk, Ad; Törnqvist, Torbjörn E.; Hekhuis, Kilian P.V.; Berendsen, Henk J.A.; Plicht, Johannes van der

1994-01-01

The interpretation of C-14 histograms is complicated by the non-linearity of the C-14 time scale in terms of Calendar years, which may result in clustering of C-14 ages in certain time intervals unrelated to the (geologic or archaeologic) phenomenon of interest. One can calibrate C-14 histograms for

Treatment plan evaluation using dose-volume histogram (DVH) and spatial dose-volume histogram (zDVH)

International Nuclear Information System (INIS)

Cheng, C.-W.; Das, Indra J.

1999-01-01

Objective: The dose-volume histogram (DVH) has been accepted as a tool for treatment-plan evaluation. However, DVH lacks spatial information. A new concept, the z-dependent dose-volume histogram (zDVH), is presented as a supplement to the DVH in three-dimensional (3D) treatment planning to provide the spatial variation, as well as the size and magnitude of the different dose regions within a region of interest. Materials and Methods: Three-dimensional dose calculations were carried out with various plans for three disease sites: lung, breast, and prostate. DVHs were calculated for the entire volume. A zDVH is defined as a differential dose-volume histogram with respect to a computed tomographic (CT) slice position. In this study, zDVHs were calculated for each CT slice in the treatment field. DVHs and zDVHs were compared. Results: In the irradiation of lung, DVH calculation indicated that the treatment plan satisfied the dose-volume constraint placed on the lung and zDVH of the lung revealed that a sizable fraction of the lung centered about the central axis (CAX) received a significant dose, a situation that warranted a modification of the treatment plan due to the removal of one lung. In the irradiation of breast with tangential fields, the DVH showed that about 7% of the breast volume received at least 110% of the prescribed dose (PD) and about 11% of the breast received less than 98% PD. However, the zDVHs of the breast volume in each of seven planes showed the existence of high-dose regions of 34% and 15%, respectively, of the volume in the two caudal-most planes and cold spots of about 40% in the two cephalic planes. In the treatment planning of prostate, DVHs showed that about 15% of the bladder and 40% of the rectum received 102% PD, whereas about 30% of the bladder and 50% of the rectum received the full dose. Taking into account the hollow structure of both the bladder and the rectum, the dose-surface histograms (DSH) showed larger hot-spot volume, about

Oriented Shape Index Histograms for Cell Classification

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo; Dahl, Anders Bjorholm; Larsen, Rasmus

2015-01-01

We propose a novel extension to the shape index histogram feature descriptor where the orientation of the second-order curvature is included in the histograms. The orientation of the shape index is reminiscent but not equal to gradient orientation which is widely used for feature description. We...... evaluate our new feature descriptor using a public dataset consisting of HEp-2 cell images from indirect immunoflourescence lighting. Our results show that we can improve classification performance significantly when including the shape index orientation. Notably, we show that shape index orientation...

Apparent diffusion coefficient histogram analysis of neonatal hypoxic-ischemic encephalopathy

Energy Technology Data Exchange (ETDEWEB)

Cauley, Keith A. [University of Massachusetts Medical School, Department of Radiology, Worcester, MA (United States); New York Presbyterian Hospital, Columbia University Medical Center, Department of Radiology, New York, NY (United States); Filippi, Christopher G. [New York Presbyterian Hospital, Columbia University Medical Center, Department of Radiology, New York, NY (United States)

2014-06-15

Diffusion-weighted imaging is a valuable tool in the assessment of the neonatal brain, and changes in diffusion are seen in normal development as well as in pathological states such as hypoxic-ischemic encephalopathy (HIE). Various methods of quantitative assessment of diffusion values have been reported. Global ischemic injury occurring during the time of rapid developmental changes in brain myelination can complicate the imaging diagnosis of neonatal HIE. To compare a quantitative method of histographic analysis of brain apparent coefficient (ADC) maps to the qualitative interpretation of routine brain MR imaging studies. We correlate changes in diffusion values with gestational age in radiographically normal neonates, and we investigate the sensitivity of the method as a quantitative measure of hypoxic-ischemic encephalopathy. We reviewed all brain MRI studies from the neonatal intensive care unit (NICU) at our university medical center over a 4-year period to identify cases that were radiographically normal (23 cases) and those with diffuse, global hypoxic-ischemic encephalopathy (12 cases). We histographically displayed ADC values of a single brain slice at the level of the basal ganglia and correlated peak (s-sD{sub av}) and lowest histogram values (s-sD{sub lowest}) with gestational age. Normative s-sD{sub av} values correlated significantly with gestational age and declined linearly through the neonatal period (r {sup 2} = 0.477, P < 0.01). Six of 12 cases of known HIE demonstrated significantly lower s-sD{sub av} and s-sD{sub lowest} ADC values than were reflected in the normative distribution; several cases of HIE fell within a 95% confidence interval for normative studies, and one case demonstrated higher-than-normal s-sD{sub av}. Single-slice histographic display of ADC values is a rapid and clinically feasible method of quantitative analysis of diffusion. In this study normative values derived from consecutive neonates without radiographic evidence of

A Modified Image Comparison Algorithm Using Histogram Features

OpenAIRE

Al-Oraiqat, Anas M.; Kostyukova, Natalya S.

2018-01-01

This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed. The modified method shows 97% average precision for a collection containing about 700 images without loss of the adv...

Three-dimensional volumetric gray-scale uterine cervix histogram prediction of days to delivery in full term pregnancy.

Science.gov (United States)

Kim, Ji Youn; Kim, Hai-Joong; Hahn, Meong Hi; Jeon, Hye Jin; Cho, Geum Joon; Hong, Sun Chul; Oh, Min Jeong

2013-09-01

Our aim was to figure out whether volumetric gray-scale histogram difference between anterior and posterior cervix can indicate the extent of cervical consistency. We collected data of 95 patients who were appropriate for vaginal delivery with 36th to 37th weeks of gestational age from September 2010 to October 2011 in the Department of Obstetrics and Gynecology, Korea University Ansan Hospital. Patients were excluded who had one of the followings: Cesarean section, labor induction, premature rupture of membrane. Thirty-four patients were finally enrolled. The patients underwent evaluation of the cervix through Bishop score, cervical length, cervical volume, three-dimensional (3D) cervical volumetric gray-scale histogram. The interval days from the cervix evaluation to the delivery day were counted. We compared to 3D cervical volumetric gray-scale histogram, Bishop score, cervical length, cervical volume with interval days from the evaluation of the cervix to the delivery. Gray-scale histogram difference between anterior and posterior cervix was significantly correlated to days to delivery. Its correlation coefficient (R) was 0.500 (P = 0.003). The cervical length was significantly related to the days to delivery. The correlation coefficient (R) and P-value between them were 0.421 and 0.013. However, anterior lip histogram, posterior lip histogram, total cervical volume, Bishop score were not associated with days to delivery (P >0.05). By using gray-scale histogram difference between anterior and posterior cervix and cervical length correlated with the days to delivery. These methods can be utilized to better help predict a cervical consistency.

Quantitative analysis of 3 dimensional volumetry and histogram of thyroid gland on neck computed tomography for patients with Hashimoto's thyroiditis

International Nuclear Information System (INIS)

Nam, In Chul; Lee, Kwang Hwi; Ryu, Ji Hwa; Kim, Ok Hwa; Kim, Seung Ho; Baek, Hye Jin; Lee, Ye Daum; Kim, Tae Nyun; Kim, Mi Kyung; Kim, Seon Jeong; Kim, Sung Mok

2015-01-01

To analyze three-dimensional (3D) volume and histogram of thyroid gland on neck computed tomography (CT) for patients with Hashimoto's thyroiditis. A total of 121 subjects who underwent neck CT between March 2013 and February 2014 were included in this study. These subjects were divided into the following two groups: 1) control group (n = 76); 2) Hashimoto's thyroiditis group (n = 45). Non-enhanced and contrast-enhanced CT images were obtained. On contrast-enhanced images, the 3D volume of thyroid gland was semi-automatically calculated. On CT histogram, attenuation number, mean, median, standard deviation (SD), and coefficient of variation (CV) of thyroid gland were calculated. These values were compared between the two groups. Total 3D volume of thyroid gland was 14.9 ± 4.8 cm 3 in the control group, which was significantly (p = 0.002) lower than that (19.2 ± 8 cm 3 ) in the Hashimoto's thyroiditis group. On CT histogram, the mean, median, SD, and CV of thyroid gland on non-enhanced images were 95.8, 99.3, 21.7, and 0.226, respectively, in the control group and 72.2, 72.6, 19.6, and 0.28 in the Hashimoto's thyroiditis group (p < 0.05). Histogram parameters on contrast-enhanced images were not significantly (p > 0.05) different. Median at cut-off value of 83 revealed the largest Az value (Az: 0.905; 95% confidence interval: 0.837-0.951; sensitivity: 84.4%; specificity: 85.5%). The Hashimoto's thyroiditis group had larger volume but lower CT attenuation number with more prominent parenchymal heterogeneity of thyroid gland than the control group

Quantitative analysis of 3 dimensional volumetry and histogram of thyroid gland on neck computed tomography for patients with Hashimoto's thyroiditis

Energy Technology Data Exchange (ETDEWEB)

Nam, In Chul; Lee, Kwang Hwi; Ryu, Ji Hwa; Kim, Ok Hwa; Kim, Seung Ho; Baek, Hye Jin; Lee, Ye Daum; Kim, Tae Nyun; Kim, Mi Kyung [Haeundae Paik Hospital, Inje University College of Medicine, Busan (Korea, Republic of); Kim, Seon Jeong [Dept. of Radiology, Myongji Hospital, Seonam University College of Medicine, Goyang (Korea, Republic of); Kim, Sung Mok [Dept. of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

2015-12-15

To analyze three-dimensional (3D) volume and histogram of thyroid gland on neck computed tomography (CT) for patients with Hashimoto's thyroiditis. A total of 121 subjects who underwent neck CT between March 2013 and February 2014 were included in this study. These subjects were divided into the following two groups: 1) control group (n = 76); 2) Hashimoto's thyroiditis group (n = 45). Non-enhanced and contrast-enhanced CT images were obtained. On contrast-enhanced images, the 3D volume of thyroid gland was semi-automatically calculated. On CT histogram, attenuation number, mean, median, standard deviation (SD), and coefficient of variation (CV) of thyroid gland were calculated. These values were compared between the two groups. Total 3D volume of thyroid gland was 14.9 ± 4.8 cm{sup 3} in the control group, which was significantly (p = 0.002) lower than that (19.2 ± 8 cm{sup 3}) in the Hashimoto's thyroiditis group. On CT histogram, the mean, median, SD, and CV of thyroid gland on non-enhanced images were 95.8, 99.3, 21.7, and 0.226, respectively, in the control group and 72.2, 72.6, 19.6, and 0.28 in the Hashimoto's thyroiditis group (p < 0.05). Histogram parameters on contrast-enhanced images were not significantly (p > 0.05) different. Median at cut-off value of 83 revealed the largest Az value (Az: 0.905; 95% confidence interval: 0.837-0.951; sensitivity: 84.4%; specificity: 85.5%). The Hashimoto's thyroiditis group had larger volume but lower CT attenuation number with more prominent parenchymal heterogeneity of thyroid gland than the control group.

Histogram specification as a method of density modification

Energy Technology Data Exchange (ETDEWEB)

Harrison, R.W.

1988-12-01

A new method for improving the quality and extending the resolution of Fourier maps is described. The method is based on a histogram analysis of the electron density. The distribution of electron density values in the map is forced to be 'ideal'. The 'ideal' distribution is assumed to be Gaussian. The application of the method to improve the electron density map for the protein Acinetobacter asparaginase, which is a tetrameric enzyme of molecular weight 140000 daltons, is described.

Histogram-based quantitative evaluation of endobronchial ultrasonography images of peripheral pulmonary lesion.

Science.gov (United States)

Morikawa, Kei; Kurimoto, Noriaki; Inoue, Takeo; Mineshita, Masamichi; Miyazawa, Teruomi

2015-01-01

Endobronchial ultrasonography using a guide sheath (EBUS-GS) is an increasingly common bronchoscopic technique, but currently, no methods have been established to quantitatively evaluate EBUS images of peripheral pulmonary lesions. The purpose of this study was to evaluate whether histogram data collected from EBUS-GS images can contribute to the diagnosis of lung cancer. Histogram-based analyses focusing on the brightness of EBUS images were retrospectively conducted: 60 patients (38 lung cancer; 22 inflammatory diseases), with clear EBUS images were included. For each patient, a 400-pixel region of interest was selected, typically located at a 3- to 5-mm radius from the probe, from recorded EBUS images during bronchoscopy. Histogram height, width, height/width ratio, standard deviation, kurtosis and skewness were investigated as diagnostic indicators. Median histogram height, width, height/width ratio and standard deviation were significantly different between lung cancer and benign lesions (all p histogram standard deviation. Histogram standard deviation appears to be the most useful characteristic for diagnosing lung cancer using EBUS images. © 2015 S. Karger AG, Basel.

Non-parametric comparison of histogrammed two-dimensional data distributions using the Energy Test

International Nuclear Information System (INIS)

Reid, Ivan D; Lopes, Raul H C; Hobson, Peter R

2012-01-01

When monitoring complex experiments, comparison is often made between regularly acquired histograms of data and reference histograms which represent the ideal state of the equipment. With the larger HEP experiments now ramping up, there is a need for automation of this task since the volume of comparisons could overwhelm human operators. However, the two-dimensional histogram comparison tools available in ROOT have been noted in the past to exhibit shortcomings. We discuss a newer comparison test for two-dimensional histograms, based on the Energy Test of Aslan and Zech, which provides more conclusive discrimination between histograms of data coming from different distributions than methods provided in a recent ROOT release.

Defect detection based on extreme edge of defective region histogram

Directory of Open Access Journals (Sweden)

Zouhir Wakaf

2018-01-01

Full Text Available Automatic thresholding has been used by many applications in image processing and pattern recognition systems. Specific attention was given during inspection for quality control purposes in various industries like steel processing and textile manufacturing. Automatic thresholding problem has been addressed well by the commonly used Otsu method, which provides suitable results for thresholding images based on a histogram of bimodal distribution. However, the Otsu method fails when the histogram is unimodal or close to unimodal. Defects have different shapes and sizes, ranging from very small to large. The gray-level distributions of the image histogram can vary between unimodal and multimodal. Furthermore, Otsu-revised methods, like the valley-emphasis method and the background histogram mode extents, which overcome the drawbacks of the Otsu method, require preprocessing steps and fail to use the general threshold for multimodal defects. This study proposes a new automatic thresholding algorithm based on the acquisition of the defective region histogram and the selection of its extreme edge as the threshold value to segment all defective objects in the foreground from the image background. To evaluate the proposed defect-detection method, common standard images for experimentation were used. Experimental results of the proposed method show that the proposed method outperforms the current methods in terms of defect detection.

Isobio software: biological dose distribution and biological dose volume histogram from physical dose conversion using linear-quadratic-linear model.

Science.gov (United States)

Jaikuna, Tanwiwat; Khadsiri, Phatchareewan; Chawapun, Nisa; Saekho, Suwit; Tharavichitkul, Ekkasit

2017-02-01

To develop an in-house software program that is able to calculate and generate the biological dose distribution and biological dose volume histogram by physical dose conversion using the linear-quadratic-linear (LQL) model. The Isobio software was developed using MATLAB version 2014b to calculate and generate the biological dose distribution and biological dose volume histograms. The physical dose from each voxel in treatment planning was extracted through Computational Environment for Radiotherapy Research (CERR), and the accuracy was verified by the differentiation between the dose volume histogram from CERR and the treatment planning system. An equivalent dose in 2 Gy fraction (EQD 2 ) was calculated using biological effective dose (BED) based on the LQL model. The software calculation and the manual calculation were compared for EQD 2 verification with pair t -test statistical analysis using IBM SPSS Statistics version 22 (64-bit). Two and three-dimensional biological dose distribution and biological dose volume histogram were displayed correctly by the Isobio software. Different physical doses were found between CERR and treatment planning system (TPS) in Oncentra, with 3.33% in high-risk clinical target volume (HR-CTV) determined by D 90% , 0.56% in the bladder, 1.74% in the rectum when determined by D 2cc , and less than 1% in Pinnacle. The difference in the EQD 2 between the software calculation and the manual calculation was not significantly different with 0.00% at p -values 0.820, 0.095, and 0.593 for external beam radiation therapy (EBRT) and 0.240, 0.320, and 0.849 for brachytherapy (BT) in HR-CTV, bladder, and rectum, respectively. The Isobio software is a feasible tool to generate the biological dose distribution and biological dose volume histogram for treatment plan evaluation in both EBRT and BT.

Histogram bin width selection for time-dependent Poisson processes

International Nuclear Information System (INIS)

Koyama, Shinsuke; Shinomoto, Shigeru

2004-01-01

In constructing a time histogram of the event sequences derived from a nonstationary point process, we wish to determine the bin width such that the mean squared error of the histogram from the underlying rate of occurrence is minimized. We find that the optimal bin widths obtained for a doubly stochastic Poisson process and a sinusoidally regulated Poisson process exhibit different scaling relations with respect to the number of sequences, time scale and amplitude of rate modulation, but both diverge under similar parametric conditions. This implies that under these conditions, no determination of the time-dependent rate can be made. We also apply the kernel method to these point processes, and find that the optimal kernels do not exhibit any critical phenomena, unlike the time histogram method

Histogram bin width selection for time-dependent Poisson processes

Energy Technology Data Exchange (ETDEWEB)

Koyama, Shinsuke; Shinomoto, Shigeru [Department of Physics, Graduate School of Science, Kyoto University, Sakyo-ku, Kyoto 606-8502 (Japan)

2004-07-23

In constructing a time histogram of the event sequences derived from a nonstationary point process, we wish to determine the bin width such that the mean squared error of the histogram from the underlying rate of occurrence is minimized. We find that the optimal bin widths obtained for a doubly stochastic Poisson process and a sinusoidally regulated Poisson process exhibit different scaling relations with respect to the number of sequences, time scale and amplitude of rate modulation, but both diverge under similar parametric conditions. This implies that under these conditions, no determination of the time-dependent rate can be made. We also apply the kernel method to these point processes, and find that the optimal kernels do not exhibit any critical phenomena, unlike the time histogram method.

Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images

Science.gov (United States)

Chen, Chieh-Li; Ishikawa, Hiroshi; Wollstein, Gadi; Bilonick, Richard A.; Sigal, Ian A.; Kagemann, Larry; Schuman, Joel S.

2015-01-01

Purpose. We minimized the influence of image quality variability, as measured by signal strength (SS), on optical coherence tomography (OCT) thickness measurements using the histogram matching (HM) method. Methods. We scanned 12 eyes from 12 healthy subjects with the Cirrus HD-OCT device to obtain a series of OCT images with a wide range of SS (maximal range, 1–10) at the same visit. For each eye, the histogram of an image with the highest SS (best image quality) was set as the reference. We applied HM to the images with lower SS by shaping the input histogram into the reference histogram. Retinal nerve fiber layer (RNFL) thickness was automatically measured before and after HM processing (defined as original and HM measurements), and compared to the device output (device measurements). Nonlinear mixed effects models were used to analyze the relationship between RNFL thickness and SS. In addition, the lowest tolerable SSs, which gave the RNFL thickness within the variability margin of manufacturer recommended SS range (6–10), were determined for device, original, and HM measurements. Results. The HM measurements showed less variability across a wide range of image quality than the original and device measurements (slope = 1.17 vs. 4.89 and 1.72 μm/SS, respectively). The lowest tolerable SS was successfully reduced to 4.5 after HM processing. Conclusions. The HM method successfully extended the acceptable SS range on OCT images. This would qualify more OCT images with low SS for clinical assessment, broadening the OCT application to a wider range of subjects. PMID:26066749

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

Science.gov (United States)

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other

Pengaruh Pola MACD Histogram IHSG Terhadap Pola MACD Histogram Perusahaan Dari Daftar Indeks LQ45 (Periode Februari s.d Juli 2015 Bursa Efek Jakarta [Effect of MACD Histogram IHSG Patterns to Patterns of Companies Listed on the Jakarta Stock Exchange LQ-45 (Period February till July 2015

Directory of Open Access Journals (Sweden)

Heri Fatkhurrokhim

2015-09-01

Full Text Available The purpose of this study is to determine the effect of MACDIHSG pattern to the MACD Company pattern in the L045 index on the period of February until July 2015 at the Indonesia Stock Exchange. This study also aims to facilitate investors to make investment decisions in the stock market. This study provides benefits to capital market investors, especially for stock investors in the Indonesia Stock Exchange as a mean of enhancing their insights in the development of technical analysis on investing. For the general public as well in order to know that investing in the stock market differs from gambling since there are analyzes that easy and can be applied very simply. In addition, this research aims to enhance the reader's desire to invest in the stock market. The samples were the closing data price of IHSG and shares ofLQ45 in the period of February until July 2015 in the Indonesia Stock Exchange. Based on the hypothesis testing, it can be explained that the MACD Histogram IHSG has a significant effect on 38 issuers listed in LQ45. As for the difference between the MACD Histogram effect against one company with another company that is very small. From the 38 stocks that rank on the top 3 company, the Summarecon Agung Tbk is on the top 1, that amounted to 98.3348%, then Alam Sutera Reality Lestari Tbk amounted to 98.2376%, and Adhi Katya (Persero Tbk amounted to 98.1320%. The third of these shares have MACD Histogram movement that approaching the MACD Histogram IHSG.

Application of whole-lesion histogram analysis of pharmacokinetic parameters in dynamic contrast-enhanced MRI of breast lesions with the CAIPIRINHA-Dixon-TWIST-VIBE technique.

Science.gov (United States)

Li, Zhiwei; Ai, Tao; Hu, Yiqi; Yan, Xu; Nickel, Marcel Dominik; Xu, Xiao; Xia, Liming

2018-01-01

To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (K trans ), outflow rate of agent between interstitium and plasma (K ep ), extravascular space volume per unit volume of tissue (v e ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis. Malignant breast lesions had significantly higher K trans , K ep , and lower v e in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v e than benign breast lesions (all P 0.05). The 90th percentile of K trans , the 90th percentile of K ep , and the 50th percentile of v e showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K ep achieved the highest AUC value (0.927) among all histogram-derived values. The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of K ep may be the best indicator in differentiation between malignant and benign breast lesions. 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96. © 2017 International Society for Magnetic Resonance in Medicine.

DSP+FPGA-based real-time histogram equalization system of infrared image

Science.gov (United States)

Gu, Dongsheng; Yang, Nansheng; Pi, Defu; Hua, Min; Shen, Xiaoyan; Zhang, Ruolan

2001-10-01

Histogram Modification is a simple but effective method to enhance an infrared image. There are several methods to equalize an infrared image's histogram due to the different characteristics of the different infrared images, such as the traditional HE (Histogram Equalization) method, and the improved HP (Histogram Projection) and PE (Plateau Equalization) method and so on. If to realize these methods in a single system, the system must have a mass of memory and extremely fast speed. In our system, we introduce a DSP + FPGA based real-time procession technology to do these things together. FPGA is used to realize the common part of these methods while DSP is to do the different part. The choice of methods and the parameter can be input by a keyboard or a computer. By this means, the function of the system is powerful while it is easy to operate and maintain. In this article, we give out the diagram of the system and the soft flow chart of the methods. And at the end of it, we give out the infrared image and its histogram before and after the process of HE method.

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

Science.gov (United States)

Gihr, Georg Alexander; Horvath-Rizea, Diana; Garnov, Nikita; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Meyer, Hans Jonas; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-02-01

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC

3D Model Retrieval Based on Vector Quantisation Index Histograms

International Nuclear Information System (INIS)

Lu, Z M; Luo, H; Pan, J S

2006-01-01

This paper proposes a novel technique to retrieval 3D mesh models using vector quantisation index histograms. Firstly, points are sampled uniformly on mesh surface. Secondly, to a point five features representing global and local properties are extracted. Thus feature vectors of points are obtained. Third, we select several models from each class, and employ their feature vectors as a training set. After training using LBG algorithm, a public codebook is constructed. Next, codeword index histograms of the query model and those in database are computed. The last step is to compute the distance between histograms of the query and those of the models in database. Experimental results show the effectiveness of our method

Adaptive histogram equalization and its variations

NARCIS (Netherlands)

Pizer, S.M.; Amburn, E.P.; Austin, J.D.; Cromartie, R.; Geselowitz, A.; Greer, Trey; Haar Romenij, ter B.M.; Zimmerman, J.B.; Zuiderveld, K.J.

1987-01-01

Adaptive histogram equalization (ahe) is a contrast enhancement method designed to be broadly applicable and having demonstrated effectiveness. However, slow speed and the overenhancement of noise it produces in relatively homogeneous regions are two problems. We report algorithms designed to

Centroid and full-width at half maximum uncertainties of histogrammed data with an underlying Gaussian distribution -- The moments method

International Nuclear Information System (INIS)

Valentine, J.D.; Rana, A.E.

1996-01-01

The effect of approximating a continuous Gaussian distribution with histogrammed data are studied. The expressions for theoretical uncertainties in centroid and full-width at half maximum (FWHM), as determined by calculation of moments, are derived using the error propagation method for a histogrammed Gaussian distribution. The results are compared with the corresponding pseudo-experimental uncertainties for computer-generated histogrammed Gaussian peaks to demonstrate the effect of binning the data. It is shown that increasing the number of bins in the histogram improves the continuous distribution approximation. For example, a FWHM ≥ 9 and FWHM ≥ 12 bins are needed to reduce the pseudo-experimental standard deviation of FWHM to within ≥5% and ≥1%, respectively, of the theoretical value for a peak containing 10,000 counts. In addition, the uncertainties in the centroid and FWHM as a function of peak area are studied. Finally, Sheppard's correction is applied to partially correct for the binning effect

Robust histogram-based image retrieval

Czech Academy of Sciences Publication Activity Database

Höschl, Cyril; Flusser, Jan

2016-01-01

Roč. 69, č. 1 (2016), s. 72-81 ISSN 0167-8655 R&D Projects: GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : Image retrieval * Noisy image * Histogram * Convolution * Moments * Invariants Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.995, year: 2016 http://library.utia.cas.cz/separaty/2015/ZOI/hoschl-0452147.pdf

Histogram analysis of stretched-exponential and monoexponential diffusion-weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma.

Science.gov (United States)

Liu, Wei; Liu, Xiao H; Tang, Wei; Gao, Hong B; Zhou, Bing N; Zhou, Liang P

2018-02-07

Noninvasive measures to evaluate the aggressiveness of prostate carcinoma (PCa) may benefit patients. To assess the value of stretched-exponential and monoexponential diffusion-weighted imaging (DWI) for predicting the aggressiveness of PCa. Retrospective study. Seventy-five patients with PCa. 3T DWI examinations were performed using b-values of 0, 500, 1000, and 2000 s/mm 2 . The research were based on entire-tumor histogram analysis and the reference standard was radical prostectomy. The correlation analysis was programmed with Spearman's rank-order analysis between the histogram variables and Gleason grade group (GG). Receiver operating characteristic (ROC) regression was used to analyze the ability of these histogram variables to differentiate low-grade (LG) from intermediate/high-grade (HG) PCa. The percentiles and mean of apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were correlated with GG (ρ: 0.414-0.593), while there was no significant relation among α value, skewnesses, and kurtosises with GG (ρ:0.034-0.323). HG tumors (ADC:484 ± 136, 592 ± 139, 670 ± 144, 788 ± 146, 895 ± 141 mm 2 /s; DDC: 410 ± 142, 532 ± 172, 666 ± 193, 786 ± 196, 914 ± 181 mm 2 /s) had lower values in the 10 th , 25 th , 50 th , 75 th percentiles and means than LG tumors (ADC: 644 ± 779, 737 ± 84, 836 ± 83, 919 ± 82, 997 ± 107 mm 2 /s; DDC: 552 ± 82, 680 ± 94, 829 ± 112, 931 ± 106, 1045 ± 100 mm 2 /s). However, there was no difference between LG and HG tumors in α value (0.671 ± 0.041 vs. 0.633 ± 0.114), kurtosises (ADC 0.09 vs. 0.086; DDC -0.033 vs. -0.317), or skewnesses (ADC -0.036 vs. 0.073; DDC -0.063 vs. 0.136). The above statistics were P Histogram variables of DDC and ADC may predict the aggressiveness of PCa, while α value does not. The abilities of ADC10 and DDC10 to discriminate LG from HG tumors were similar, and

PET quantification with a histogram derived total activity metric: Superior quantitative consistency compared to total lesion glycolysis with absolute or relative SUV thresholds in phantoms and lung cancer patients

International Nuclear Information System (INIS)

Burger, Irene A.; Vargas, Hebert Alberto; Apte, Aditya; Beattie, Bradley J.; Humm, John L.; Gonen, Mithat; Larson, Steven M.; Ross Schmidtlein, C.

2014-01-01

Introduction: The increasing use of molecular imaging probes as biomarkers in oncology emphasizes the need for robust and stable methods for quantifying tracer uptake in PET imaging. The primary motivation for this research was to find an accurate method to quantify the total tumor uptake. Therefore we developed a histogram-based method to calculate the background subtracted lesion (BSL) activity and validated BSL by comparing the quantitative consistency with the total lesion glycolysis (TLG) in phantom and patient studies. Methods: A thorax phantom and a PET-ACR quality assurance phantom were scanned with increasing FDG concentrations. Volumes of interest (VOIs) were placed over each chamber. TLG was calculated with a fixed threshold at SUV 2.5 (TLG 2.5 ) and a relative threshold at 42% of SUV max (TLG 42% ). The histogram for each VOI was built and BSL was calculated. Comparison with the total injected FDG activity (TIA) was performed using concordance correlation coefficients (CCC) and the slope (a). Fifty consecutive patients with FDG-avid lung tumors were selected under an IRB waiver. TLG 42% , TLG 2.5 and BSL were compared to the reference standard calculating CCC and the slope. Results: In both phantoms, the CCC for lesions with a TIA ≤ 50 ml*SUV between TIA and BSL was higher and the slope closer to 1 (CCC = 0.933, a = 1.189), than for TLG 42% (CCC = 0.350, a = 0.731) or TLG 2.5 (CCC = 0.761, a = 0.727). In 50 lung lesions BSL had a slope closer to 1 compared to the reference activity than TLG 42% (a = 1.084 vs 0.618 – for high activity lesions) and also closer to 1 than TLG 2.5 (a = 1.117 vs 0.548 – for low activity lesions). Conclusion: The histogram based BSL correlated better with TIA in both phantom studies than TLG 2.5 or TLG 42% . Also in lung tumors, the BSL activity is overall more accurate in quantifying the lesion activity compared to the two most commonly applied TLG quantification methods

Extracting rate coefficients from single-molecule photon trajectories and FRET efficiency histograms for a fast-folding protein.

Science.gov (United States)

Chung, Hoi Sung; Gopich, Irina V; McHale, Kevin; Cellmer, Troy; Louis, John M; Eaton, William A

2011-04-28

Recently developed statistical methods by Gopich and Szabo were used to extract folding and unfolding rate coefficients from single-molecule Förster resonance energy transfer (FRET) data for proteins with kinetics too fast to measure waiting time distributions. Two types of experiments and two different analyses were performed. In one experiment bursts of photons were collected from donor and acceptor fluorophores attached to a 73-residue protein, α(3)D, freely diffusing through the illuminated volume of a confocal microscope system. In the second, the protein was immobilized by linkage to a surface, and photons were collected until one of the fluorophores bleached. Folding and unfolding rate coefficients and mean FRET efficiencies for the folded and unfolded subpopulations were obtained from a photon by photon analysis of the trajectories using a maximum likelihood method. The ability of the method to describe the data in terms of a two-state model was checked by recoloring the photon trajectories with the extracted parameters and comparing the calculated FRET efficiency histograms with the measured histograms. The sum of the rate coefficients for the two-state model agreed to within 30% with the relaxation rate obtained from the decay of the donor-acceptor cross-correlation function, confirming the high accuracy of the method. Interestingly, apparently reliable rate coefficients could be extracted using the maximum likelihood method, even at low (rate coefficients and mean FRET efficiencies were also obtained in an approximate procedure by simply fitting the FRET efficiency histograms, calculated by binning the donor and acceptor photons, with a sum of three-Gaussian functions. The kinetics are exposed in these histograms by the growth of a FRET efficiency peak at values intermediate between the folded and unfolded peaks as the bin size increases, a phenomenon with similarities to NMR exchange broadening. When comparable populations of folded and unfolded

3D facial expression recognition based on histograms of surface differential quantities

KAUST Repository

Li, Huibin; Morvan, Jean-Marie; Chen, Liming

2011-01-01

. To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle

Neutrosophic Similarity Score Based Weighted Histogram for Robust Mean-Shift Tracking

Directory of Open Access Journals (Sweden)

Keli Hu

2017-10-01

Full Text Available Visual object tracking is a critical task in computer vision. Challenging things always exist when an object needs to be tracked. For instance, background clutter is one of the most challenging problems. The mean-shift tracker is quite popular because of its efficiency and performance in a range of conditions. However, the challenge of background clutter also disturbs its performance. In this article, we propose a novel weighted histogram based on neutrosophic similarity score to help the mean-shift tracker discriminate the target from the background. Neutrosophic set (NS is a new branch of philosophy for dealing with incomplete, indeterminate, and inconsistent information. In this paper, we utilize the single valued neutrosophic set (SVNS, which is a subclass of NS to improve the mean-shift tracker. First, two kinds of criteria are considered as the object feature similarity and the background feature similarity, and each bin of the weight histogram is represented in the SVNS domain via three membership functions T(Truth, I(indeterminacy, and F(Falsity. Second, the neutrosophic similarity score function is introduced to fuse those two criteria and to build the final weight histogram. Finally, a novel neutrosophic weighted mean-shift tracker is proposed. The proposed tracker is compared with several mean-shift based trackers on a dataset of 61 public sequences. The results revealed that our method outperforms other trackers, especially when confronting background clutter.

Using histograms to introduce randomization in the generation of ensembles of decision trees

Science.gov (United States)

Kamath, Chandrika; Cantu-Paz, Erick; Littau, David

2005-02-22

A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.

Finding significantly connected voxels based on histograms of connection strengths

DEFF Research Database (Denmark)

Kasenburg, Niklas; Pedersen, Morten Vester; Darkner, Sune

2016-01-01

We explore a new approach for structural connectivity based segmentations of subcortical brain regions. Connectivity based segmentations are usually based on fibre connections from a seed region to predefined target regions. We present a method for finding significantly connected voxels based...... on the distribution of connection strengths. Paths from seed voxels to all voxels in a target region are obtained from a shortest-path tractography. For each seed voxel we approximate the distribution with a histogram of path scores. We hypothesise that the majority of estimated connections are false-positives...... and that their connection strength is distributed differently from true-positive connections. Therefore, an empirical null-distribution is defined for each target region as the average normalized histogram over all voxels in the seed region. Single histograms are then tested against the corresponding null...

Quantifying the Impact of Immediate Reconstruction in Postmastectomy Radiation: A Large, Dose-Volume Histogram-Based Analysis

Energy Technology Data Exchange (ETDEWEB)

Ohri, Nisha [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Cordeiro, Peter G. [Department of Plastic Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Keam, Jennifer [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ballangrud, Ase [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Shi Weiji; Zhang Zhigang [Department of Biostatistics and Epidemiology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Nerbun, Claire T.; Woch, Katherine M.; Stein, Nicholas F.; Zhou Ying [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); McCormick, Beryl; Powell, Simon N. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ho, Alice Y., E-mail: HoA1234@mskcc.org [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York (United States)

2012-10-01

Purpose: To assess the impact of immediate breast reconstruction on postmastectomy radiation (PMRT) using dose-volume histogram (DVH) data. Methods and Materials: Two hundred forty-seven women underwent PMRT at our center, 196 with implant reconstruction and 51 without reconstruction. Patients with reconstruction were treated with tangential photons, and patients without reconstruction were treated with en-face electron fields and customized bolus. Twenty percent of patients received internal mammary node (IMN) treatment. The DVH data were compared between groups. Ipsilateral lung parameters included V20 (% volume receiving 20 Gy), V40 (% volume receiving 40 Gy), mean dose, and maximum dose. Heart parameters included V25 (% volume receiving 25 Gy), mean dose, and maximum dose. IMN coverage was assessed when applicable. Chest wall coverage was assessed in patients with reconstruction. Propensity-matched analysis adjusted for potential confounders of laterality and IMN treatment. Results: Reconstruction was associated with lower lung V20, mean dose, and maximum dose compared with no reconstruction (all P<.0001). These associations persisted on propensity-matched analysis (all P<.0001). Heart doses were similar between groups (P=NS). Ninety percent of patients with reconstruction had excellent chest wall coverage (D95 >98%). IMN coverage was superior in patients with reconstruction (D95 >92.0 vs 75.7%, P<.001). IMN treatment significantly increased lung and heart parameters in patients with reconstruction (all P<.05) but minimally affected those without reconstruction (all P>.05). Among IMN-treated patients, only lower lung V20 in those without reconstruction persisted (P=.022), and mean and maximum heart doses were higher than in patients without reconstruction (P=.006, P=.015, respectively). Conclusions: Implant reconstruction does not compromise the technical quality of PMRT when the IMNs are untreated. Treatment technique, not reconstruction, is the primary

Differentially Private Event Histogram Publication on Sequences over Graphs

Institute of Scientific and Technical Information of China (English)

Ning Wang; Yu Gu; Jia Xu; Fang-Fang Li; Ge Yu

2017-01-01

The big data era is coming with strong and ever-growing demands on analyzing personal information and footprints in the cyber world. To enable such analysis without privacy leak risk, differential privacy (DP) has been quickly rising in recent years, as the first practical privacy protection model with rigorous theoretical guarantee. This paper discusses how to publish differentially private histograms on events in time series domain, with sequences of personal events over graphs with events as edges. Such individual-generated sequences commonly appear in formalized industrial workflows, online game logs, and spatial-temporal trajectories. Directly publishing the statistics of sequences may compromise personal privacy. While existing DP mechanisms mainly target at normalized domains with fixed and aligned dimensions, our problem raises new challenges when the sequences could follow arbitrary paths on the graph. To tackle the problem, we reformulate the problem with a three-step framework, which 1) carefully truncates the original sequences, trading off errors introduced by the truncation with those introduced by the noise added to guarantee privacy, 2) decomposes the event graph into path sub-domains based on a group of event pivots, and 3) employs a deeply optimized tree-based histogram construction approach for each sub-domain to benefit with less noise addition. We present a careful analysis on our framework to support thorough optimizations over each step of the framework, and verify the huge improvements of our proposals over state-of-the-art solutions.

Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

OpenAIRE

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover's distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stoc...

In vivo portal dosimetry for head-and-neck VMAT and lung IMRT: Linking γ-analysis with differences in dose–volume histograms of the PTV

International Nuclear Information System (INIS)

Rozendaal, Roel Arthur; Mijnheer, Ben J.; Herk, Marcel van; Mans, Anton

2014-01-01

Purpose: To relate the results of γ-analysis and dose–volume histogram (DVH) analysis of the PTV for detecting dose deviations with in vivo dosimetry for two treatment sites. Methods and materials: In vivo 3D dose distributions were reconstructed for 722 fractions of 200 head-and-neck (H and N) VMAT treatments and 183 fractions of 61 lung IMRT plans. The reconstructed and planned dose distributions in the PTV were compared using (a) the γ-distribution and (b) the differences in D2, D50 and D98 between the two dose distributions. Using pre-defined tolerance levels, all fractions were classified as deviating or not deviating by both methods. The mutual agreement, the sensitivity and the specificity of the two methods were compared. Results: For lung IMRT, the classification of the fractions was nearly identical for γ- and DVH-analyses of the PTV (94% agreement) and the sensitivity and specificity were comparable for both methods. Less agreement (80%) was found for H and N VMAT, while γ-analysis was both less sensitive and less specific. Conclusions: DVH- and γ-analyses perform nearly equal in finding dose deviations in the PTV for lung IMRT treatments; for H and N VMAT treatments, DVH-analysis is preferable. As a result of this study, a smooth transition to using DVH-analysis clinically for detecting in vivo dose deviations in the PTV is within reach

Integral Histogram with Random Projection for Pedestrian Detection.

Directory of Open Access Journals (Sweden)

Chang-Hua Liu

Full Text Available In this paper, we give a systematic study to report several deep insights into the HOG, one of the most widely used features in the modern computer vision and image processing applications. We first show that, its magnitudes of gradient can be randomly projected with random matrix. To handle over-fitting, an integral histogram based on the differences of randomly selected blocks is proposed. The experiments show that both the random projection and integral histogram outperform the HOG feature obviously. Finally, the two ideas are combined into a new descriptor termed IHRP, which outperforms the HOG feature with less dimensions and higher speed.

The application of the distance histogram in microdosimetry for evaluating heterogeneity

International Nuclear Information System (INIS)

Dieren, E.B. van; Lingen, A. van; Roos, J.C.; Teule, G.J.J.

1992-01-01

Heterogeneity of radionuclide distributions at a microscopic level is relevant for the dosimetry of short path-length emissions. The present study explores the methodological aspects and the limitations of source target histograms by using computer simulations of radionuclide distributions. Sources were formed by labeled cells, containing 50 decay sites each. Cell nuclei were considered as targets. Within a matrix of 2,500 cells, the authors investigated uniform distributions (MIRD assumption), various cluster sizes, the single labeled cell, and a random distribution. Furthermore, four different intracellular source localizations were studied in a matrix of one cell. The distance histograms for both matrices were combined. For both 125 I and 131 I , absorbed doses in the targets were calculated from multiplication of the distance histograms by the point source absorbed radiation dose distribution. The presented results indicate that the use of distance histograms might be a mathematically convenient approach to microdosimetrical studies. They provide a means to study combinations of source distributions at various levels of magnification for several radionuclides within a reasonable calculation time

Adaptive Histogram Equalization Based Image Forensics Using Statistics of DC DCT Coefficients

Directory of Open Access Journals (Sweden)

Neetu Singh

2018-01-01

Full Text Available The vulnerability of digital images is growing towards manipulation. This motivated an area of research to deal with digital image forgeries. The certifying origin and content of digital images is an open problem in the multimedia world. One of the ways to find the truth of images is finding the presence of any type of contrast enhancement. In this work, novel and simple machine learning tool is proposed to detect the presence of histogram equalization using statistical parameters of DC Discrete Cosine Transform (DCT coefficients. The statistical parameters of the Gaussian Mixture Model (GMM fitted to DC DCT coefficients are used as features for classifying original and histogram equalized images. An SVM classifier has been developed to classify original and histogram equalized image which can detect histogram equalized image with accuracy greater than 95% when false rate is less than 5%.

Histogram equalization with Bayesian estimation for noise robust speech recognition.

Science.gov (United States)

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

DE-STRIPING FOR TDICCD REMOTE SENSING IMAGE BASED ON STATISTICAL FEATURES OF HISTOGRAM

Directory of Open Access Journals (Sweden)

H.-T. Gao

2016-06-01

Full Text Available Aim to striping noise brought by non-uniform response of remote sensing TDI CCD, a novel de-striping method based on statistical features of image histogram is put forward. By analysing the distribution of histograms,the centroid of histogram is selected to be an eigenvalue representing uniformity of ground objects,histogrammic centroid of whole image and each pixels are calculated first,the differences between them are regard as rough correction coefficients, then in order to avoid the sensitivity caused by single parameter and considering the strong continuity and pertinence of ground objects between two adjacent pixels,correlation coefficient of the histograms is introduces to reflect the similarities between them,fine correction coefficient is obtained by searching around the rough correction coefficient,additionally,in view of the influence of bright cloud on histogram,an automatic cloud detection based on multi-feature including grey level,texture,fractal dimension and edge is used to pre-process image.Two 0-level panchromatic images of SJ-9A satellite with obvious strip noise are processed by proposed method to evaluate the performance, results show that the visual quality of images are improved because the strip noise is entirely removed,we quantitatively analyse the result by calculating the non-uniformity ,which has reached about 1% and is better than histogram matching method.

Image compression using moving average histogram and RBF network

International Nuclear Information System (INIS)

Khowaja, S.; Ismaili, I.A.

2015-01-01

Modernization and Globalization have made the multimedia technology as one of the fastest growing field in recent times but optimal use of bandwidth and storage has been one of the topics which attract the research community to work on. Considering that images have a lion share in multimedia communication, efficient image compression technique has become the basic need for optimal use of bandwidth and space. This paper proposes a novel method for image compression based on fusion of moving average histogram and RBF (Radial Basis Function). Proposed technique employs the concept of reducing color intensity levels using moving average histogram technique followed by the correction of color intensity levels using RBF networks at reconstruction phase. Existing methods have used low resolution images for the testing purpose but the proposed method has been tested on various image resolutions to have a clear assessment of the said technique. The proposed method have been tested on 35 images with varying resolution and have been compared with the existing algorithms in terms of CR (Compression Ratio), MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), computational complexity. The outcome shows that the proposed methodology is a better trade off technique in terms of compression ratio, PSNR which determines the quality of the image and computational complexity. (author)

[Comparison of film-screen combinations in contrast-detail diagram and with interactive image analysis. 3: Trimodal histograms of gray scale distribution in bar groups of lead pattern images].

Science.gov (United States)

Hagemann, G; Eichbaum, G; Stamm, G

1998-05-01

The following four screen film combinations were compared: a) a combination of anticrossover film and UV-light emitting screens, b) a combination of blue-light emitting screens and film and c) two conventional green fluorescing screen film combinations. Radiographs of a specially designed plexiglass phantom (0.2 x 0.2 x 0.12 m3) with bar patterns of lead and plaster and of air, respectively were obtained using the following parameters: 12 pulse generator, 0.6 mm focus size, 4.7 mm aluminum prefilter, a grid with 40 lines/cm (12:1) and a focus-detector distance of 1.15 m. Image analysis was performed using an Ibas system and a Zeiss Kontron computer. Display conditions were the following: display distance 0.12 m, a vario film objective 35/70 (Zeiss), a video camera tube with a PbO photocathode, 625 lines (Siemens Heimann), an Ibas image matrix of 512 x 512 pixels with a spatial resolution of ca. 7 cycles/mm, the projected matrix area was 5000 micron 2. Maxima in the histograms of a grouped bar pattern were estimated as mean values from the bar and gap regions ("mean value method"). They were used to calculate signal contrast, standard deviations of the means and scatter fraction. Comparing the histograms with respect to spatial resolution and kV setting a clear advantage of the UVR system becomes obvious. The quantitative analysis yielded a maximum spatial resolution of approx. 3 cycles/mm for the UVR system at 60 kV which decreased to half of this value at 117 kV caused by the increasing influence of scattered radiation. A ranking of screen-film systems with respect to image quality and dose requirement is presented. For its evaluation an interactive image analysis using the mean value method was found to be superior to signal/noise ratio measurements and visual analysis in respect to diagnostic relevance and saving of time.

Visual vs Fully Automatic Histogram-Based Assessment of Idiopathic Pulmonary Fibrosis (IPF) Progression Using Sequential Multidetector Computed Tomography (MDCT)

Science.gov (United States)

Colombi, Davide; Dinkel, Julien; Weinheimer, Oliver; Obermayer, Berenike; Buzan, Teodora; Nabers, Diana; Bauer, Claudia; Oltmanns, Ute; Palmowski, Karin; Herth, Felix; Kauczor, Hans Ulrich; Sverzellati, Nicola

2015-01-01

Objectives To describe changes over time in extent of idiopathic pulmonary fibrosis (IPF) at multidetector computed tomography (MDCT) assessed by semi-quantitative visual scores (VSs) and fully automatic histogram-based quantitative evaluation and to test the relationship between these two methods of quantification. Methods Forty IPF patients (median age: 70 y, interquartile: 62-75 years; M:F, 33:7) that underwent 2 MDCT at different time points with a median interval of 13 months (interquartile: 10-17 months) were retrospectively evaluated. In-house software YACTA quantified automatically lung density histogram (10th-90th percentile in 5th percentile steps). Longitudinal changes in VSs and in the percentiles of attenuation histogram were obtained in 20 untreated patients and 20 patients treated with pirfenidone. Pearson correlation analysis was used to test the relationship between VSs and selected percentiles. Results In follow-up MDCT, visual overall extent of parenchymal abnormalities (OE) increased in median by 5 %/year (interquartile: 0 %/y; +11 %/y). Substantial difference was found between treated and untreated patients in HU changes of the 40th and of the 80th percentiles of density histogram. Correlation analysis between VSs and selected percentiles showed higher correlation between the changes (Δ) in OE and Δ 40th percentile (r=0.69; phistogram analysis at one year follow-up of IPF patients, whether treated or untreated: Δ 40th percentile might reflect the change in overall extent of lung abnormalities, notably of ground-glass pattern; furthermore Δ 80th percentile might reveal the course of reticular opacities. PMID:26110421

Conformal irradiation of the prostate: estimating long-term rectal bleeding risk using dose-volume histograms

International Nuclear Information System (INIS)

Hartford, Alan C.; Niemierko, Andrzej; Adams, Judith A.; Urie, Marcia M.; Shipley, William U.

1996-01-01

Purpose: Dose-volume histograms (DVHs) may be very useful tools for estimating probability of normal tissue complications (NTCP), but there is not yet an agreed upon method for their analysis. This study introduces a statistical method of aggregating and analyzing primary data from DVHs and associated outcomes. It explores the dose-volume relationship for NTCP of the rectum, using long-term data on rectal wall bleeding following prostatic irradiation. Methods and Materials: Previously published data were reviewed and updated on 41 patients with Stages T3 and T4 prostatic carcinoma treated with photons followed by perineal proton boost, including dose-volume histograms (DVHs) of each patient's anterior rectal wall and data on the occurrence of postirradiation rectal bleeding (minimum FU > 4 years). Logistic regression was used to test whether some individual combination of dose and volume irradiated might best separate the DVHs into categories of high or low risk for rectal bleeding. Further analysis explored whether a group of such dose-volume combinations might be superior in predicting complication risk. These results were compared with results of the 'critical volume model', a mathematical model based on assumptions of underlying radiobiological interactions. Results: Ten of the 128 tested dose-volume combinations proved to be 'statistically significant combinations' (SSCs) distinguishing between bleeders (14 out of 41) and nonbleeders (27 out of 41), ranging contiguously between 60 CGE (Cobalt Gray Equivalent) to 70% of the anterior rectal wall and 75 CGE to 30%. Calculated odds ratios for each SSC were not significantly different across the individual SSCs; however, analysis combining SSCs allowed segregation of DVHs into three risk groups: low, moderate, and high. Estimates of probabilities of normal tissue complications (NTCPs) based on these risk groups correlated strongly with observed data (p = 0.003) and with biomathematical model-generated NTCPs

A comparison of automatic histogram constructions

NARCIS (Netherlands)

Davies, P.L.; Gather, U.; Nordman, D.J.; Weinert, H.

2009-01-01

Even for a well-trained statistician the construction of a histogram for a given real-valued data set is a difficult problem. It is even more difficult to construct a fully automatic procedure which specifies the number and widths of the bins in a satisfactory manner for a wide range of data sets.

Control system of hexacopter using color histogram footprint and convolutional neural network

Science.gov (United States)

Ruliputra, R. N.; Darma, S.

2017-07-01

The development of unmanned aerial vehicles (UAV) has been growing rapidly in recent years. The use of logic thinking which is implemented into the program algorithms is needed to make a smart system. By using visual input from a camera, UAV is able to fly autonomously by detecting a target. However, some weaknesses arose as usage in the outdoor environment might change the target's color intensity. Color histogram footprint overcomes the problem because it divides color intensity into separate bins that make the detection tolerant to the slight change of color intensity. Template matching compare its detection result with a template of the reference image to determine the target position and use it to position the vehicle in the middle of the target with visual feedback control based on Proportional-Integral-Derivative (PID) controller. Color histogram footprint method localizes the target by calculating the back projection of its histogram. It has an average success rate of 77 % from a distance of 1 meter. It can position itself in the middle of the target by using visual feedback control with an average positioning time of 73 seconds. After the hexacopter is in the middle of the target, Convolutional Neural Networks (CNN) classifies a number contained in the target image to determine a task depending on the classified number, either landing, yawing, or return to launch. The recognition result shows an optimum success rate of 99.2 %.

Principal Component Analysis-Based Pattern Analysis of Dose-Volume Histograms and Influence on Rectal Toxicity

International Nuclear Information System (INIS)

Soehn, Matthias; Alber, Markus; Yan Di

2007-01-01

Purpose: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. Methods and Materials: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as 'eigenmodes,' which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. Results: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe ∼94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses (∼40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. Conclusions: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches

Histogram Modification and Wavelet Transform for High Performance Watermarking

Directory of Open Access Journals (Sweden)

Ying-Shen Juang

2012-01-01

Full Text Available This paper proposes a reversible watermarking technique for natural images. According to the similarity of neighbor coefficients’ values in wavelet domain, most differences between two adjacent pixels are close to zero. The histogram is built based on these difference statistics. As more peak points can be used for secret data hiding, the hiding capacity is improved compared with those conventional methods. Moreover, as the differences concentricity around zero is improved, the transparency of the host image can be increased. Experimental results and comparison show that the proposed method has both advantages in hiding capacity and transparency.

Neutron stars as X-ray burst sources. II. Burst energy histograms and why they burst

International Nuclear Information System (INIS)

Baan, W.A.

1979-01-01

In this work we explore some of the implications of a model for X-ray burst sources where bursts are caused by Kruskal-Schwarzschild instabilities at the magnetopause of an accreting and rotating neutron star. A number of simplifying assumptions are made in order to test the model using observed burst-energy histograms for the rapid burster MXB 1730--335. The predicted histograms have a correct general shape, but it appears that other effects are important as well, and that mode competition, for instance, may suppress the histograms at high burst energies. An explanation is ventured for the enhancement in the histogram at the highest burst energies, which produces the bimodal shape in high accretion rate histograms. Quantitative criteria are given for deciding when accreting neutron stars are steady sources or burst sources, and these criteria are tested using the X-ray pulsars

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

Science.gov (United States)

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Histogram analysis for age change of human lung with computed tomography

International Nuclear Information System (INIS)

Shirabe, Ichiju

1990-01-01

In order to evaluate physiological changes of normal lung with aging by computed tomography (CT), the peak position (PP) and full width half maximum (FWHM) of CT-histogram were studied in 77 normal human lung. Above 30 years old, PP tended to be seen in the lower attenuation value with advancing ages, with the result that the follow equation was obtained. CT attenuation value of PP=-0.87 x age -815. The peak position shifted to the range of higher CT attenuation in 30's. FWHM did not change with advancing ages. There were no differences of peak value and FWHM among the upper, middle and lower lung field. In this study, physiological changes of lung were evaluated quantitatively. Furthermore, this study was considered to be useful for diagnosis and treatment in lung diseases. (author)

FPGA based high-performance multi-channel analyzer with local histogram memory

International Nuclear Information System (INIS)

Kulkarni, C.P.; Vaidya, P.P.; Paulson, M.

2004-01-01

Modern nuclear spectroscopy systems demand for a Multi-Channel Analyzer (MCA) with higher resolution, faster speed and other advanced features. The MCA described here is targeted for such demanding applications. The MCA has an in-built local histogram memory and a memory management unit integrated in an FPGA (Field Programmable Gate Array) chip. In addition to the integrated low power digital circuitry, the system utilizes state of the art advanced analog circuits like low power, high speed and high precision comparators, op-amps, ADC and DAC. The operating resolution is selectable from 256 channels to 16384 channels for pulse height analysis. It supports high count rate applications (typically 100 KHz) without significant dead time penalty. It can have an USB bus interface with simple changes. In general, the MCA gives a high performance, compact and low power alternative for portable and battery operated systems as well as for high end laboratory instruments. (author)

AN ILLUMINATION INVARIANT FACE RECOGNITION BY ENHANCED CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION

Directory of Open Access Journals (Sweden)

A. Thamizharasi

2016-05-01

Full Text Available Face recognition system is gaining more importance in social networks and surveillance. The face recognition task is complex due to the variations in illumination, expression, occlusion, aging and pose. The illumination variations in image are due to changes in lighting conditions, poor illumination, low contrast or increased brightness. The variations in illumination adversely affect the quality of image and recognition accuracy. The illumination variations in face image have to be pre-processed prior to face recognition. The Contrast Limited Adaptive Histogram Equalization (CLAHE is an image enhancement technique popular in enhancing medical images. The proposed work is to create illumination invariant face recognition system by enhancing Contrast Limited Adaptive Histogram Equalization technique. This method is termed as “Enhanced CLAHE”. The efficiency of Enhanced CLAHE is tested using Fuzzy K Nearest Neighbour classifier and fisher face subspace projection method. The face recognition accuracy percentage rate, Equal Error Rate and False Acceptance Rate at 1% are calculated. The performance of CLAHE and Enhanced CLAHE methods is compared. The efficiency of the Enhanced CLAHE method is tested with three public face databases AR, Yale and ORL. The Enhanced CLAHE has very high recognition accuracy percentage rate when compared to CLAHE.

The Standardized Histogram Shift of T2 Magnetic Resonance Image (MRI) Signal Intensities of Nephroblastoma Does Not Predict Histopathological Diagnostic Information

OpenAIRE

M?ller, Sabine; David, Ruslan; Marias, Kostas; Graf, Norbert

2015-01-01

The objective of this study is to assess standardized histograms of signal intensities of T2-weighted magnetic resonance image (MRI) modality before and after preoperative chemotherapy for nephroblastoma (Wilms? tumor). All analyzed patients are enrolled in the International Society of Paediatric Oncology (SIOP) 2001/GPOH trial.1 The question to be answered is whether the comparison of the histograms can add new knowledge by comparing them with the histology of the tumor after preoperative ch...

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However

An evaluation of an improved method for computing histograms in dynamic tracer studies using positron-emission tomography

International Nuclear Information System (INIS)

Ollinger, J.M.; Snyder, D.L.

1986-01-01

A method for computing approximate minimum-mean-square-error estimates of histograms from list-mode data for use in dynamic tracer studies is evaluated. Parameters estimated from these histograms are significantly more accurate than those estimated from histograms computed by a commonly used method

Predicting pathologic tumor response to chemoradiotherapy with histogram distances characterizing longitudinal changes in 18F-FDG uptake patterns

Science.gov (United States)

Tan, Shan; Zhang, Hao; Zhang, Yongxue; Chen, Wengen; D’Souza, Warren D.; Lu, Wei

2013-01-01

Purpose: A family of fluorine-18 (18F)-fluorodeoxyglucose (18F-FDG) positron-emission tomography (PET) features based on histogram distances is proposed for predicting pathologic tumor response to neoadjuvant chemoradiotherapy (CRT). These features describe the longitudinal change of FDG uptake distribution within a tumor. Methods: Twenty patients with esophageal cancer treated with CRT plus surgery were included in this study. All patients underwent PET/CT scans before (pre-) and after (post-) CRT. The two scans were first rigidly registered, and the original tumor sites were then manually delineated on the pre-PET/CT by an experienced nuclear medicine physician. Two histograms representing the FDG uptake distribution were extracted from the pre- and the registered post-PET images, respectively, both within the delineated tumor. Distances between the two histograms quantify longitudinal changes in FDG uptake distribution resulting from CRT, and thus are potential predictors of tumor response. A total of 19 histogram distances were examined and compared to both traditional PET response measures and Haralick texture features. Receiver operating characteristic analyses and Mann-Whitney U test were performed to assess their predictive ability. Results: Among all tested histogram distances, seven bin-to-bin and seven crossbin distances outperformed traditional PET response measures using maximum standardized uptake value (AUC = 0.70) or total lesion glycolysis (AUC = 0.80). The seven bin-to-bin distances were: L2 distance (AUC = 0.84), χ2 distance (AUC = 0.83), intersection distance (AUC = 0.82), cosine distance (AUC = 0.83), squared Euclidean distance (AUC = 0.83), L1 distance (AUC = 0.82), and Jeffrey distance (AUC = 0.82). The seven crossbin distances were: quadratic-chi distance (AUC = 0.89), earth mover distance (AUC = 0.86), fast earth mover distance (AUC = 0.86), diffusion distance (AUC = 0.88), Kolmogorov-Smirnov distance (AUC = 0.88), quadratic form distance

Symbol recognition via statistical integration of pixel-level constraint histograms: a new descriptor.

Science.gov (United States)

Yang, Su

2005-02-01

A new descriptor for symbol recognition is proposed. 1) A histogram is constructed for every pixel to figure out the distribution of the constraints among the other pixels. 2) All the histograms are statistically integrated to form a feature vector with fixed dimension. The robustness and invariance were experimentally confirmed.

Reducing variability in the output of pattern classifiers using histogram shaping

International Nuclear Information System (INIS)

Gupta, Shalini; Kan, Chih-Wen; Markey, Mia K.

2010-01-01

Purpose: The authors present a novel technique based on histogram shaping to reduce the variability in the output and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs. Methods: The authors identify different sources of variability in the output of linear pattern classifiers with identical ROC curves, which also result in classifiers with differently distributed outputs. They theoretically develop a novel technique based on the matching of the histograms of these differently distributed pattern classifier outputs to reduce the variability in their (sensitivity, specificity) pairs at fixed decision thresholds, and to reduce the variability in their actual output values. They empirically demonstrate the efficacy of the proposed technique by means of analyses on the simulated data and real world mammography data. Results: For the simulated data, with three different known sources of variability, and for the real world mammography data with unknown sources of variability, the proposed classifier output calibration technique significantly reduced the variability in the classifiers' (sensitivity, specificity) pairs at fixed decision thresholds. Furthermore, for classifiers with monotonically or approximately monotonically related output variables, the histogram shaping technique also significantly reduced the variability in their actual output values. Conclusions: Classifier output calibration based on histogram shaping can be successfully employed to reduce the variability in the output values and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs.

A novel parallel architecture for local histogram equalization

Science.gov (United States)

Ohannessian, Mesrob I.; Choueiter, Ghinwa F.; Diab, Hassan

2005-07-01

Local histogram equalization is an image enhancement algorithm that has found wide application in the pre-processing stage of areas such as computer vision, pattern recognition and medical imaging. The computationally intensive nature of the procedure, however, is a main limitation when real time interactive applications are in question. This work explores the possibility of performing parallel local histogram equalization, using an array of special purpose elementary processors, through an HDL implementation that targets FPGA or ASIC platforms. A novel parallelization scheme is presented and the corresponding architecture is derived. The algorithm is reduced to pixel-level operations. Processing elements are assigned image blocks, to maintain a reasonable performance-cost ratio. To further simplify both processor and memory organizations, a bit-serial access scheme is used. A brief performance assessment is provided to illustrate and quantify the merit of the approach.

PROCESS PERFORMANCE EVALUATION USING HISTOGRAM AND TAGUCHI TECHNIQUE IN LOCK MANUFACTURING COMPANY

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Hagos Berhane

2013-12-01

Full Text Available Process capability analysis is a vital part of an overall quality improvement program. It is a technique that has application in many segments of the product cycle, including product and process design, vendor sourcing, production or manufacturing planning, and manufacturing. Frequently, a process capability study involves observing a quality characteristic of the product. Since this information usually pertains to the product rather than the process, this analysis should strictly speaking be called a product analysis study. A true process capability study in this context would involve collecting data that relates to process parameters so that remedial actions can be identified on a timely basis. The present study attempts to analyze performance of drilling, pressing, and reaming operations carried out for the manufacturing of two major lock components viz. handle and lever plate, at Gaurav International, Aligarh (India. The data collected for depth of hole on handle, central hole diameter, and key hole diameter are used to construct histogram. Next, the information available in frequency distribution table, the process mean, process capability from calculations and specification limits provided by the manufacturing concern are used with Taguchi technique. The data obtained from histogram and Taguchi technique combined are used to evaluate the performance of the manufacturing process. Results of this study indicated that the performance of all the processes used to produce depth of hole on handle, key hole diameter, and central hole diameter are potentially incapable as the process capability indices are found to be 0.54, 0.54 and 0.76 respectively. The number of nonconforming parts expressed in terms of parts per million (ppm that have fallen out of the specification limits are found to be 140000, 26666.66, and 146666.66 for depth of hole on handle, central hole diameter, and key hole diameter respectively. As a result, the total loss incurred

Sistem Verifikasi Tanda Tangan Off-Line Berdasar Ciri Histogram Of Oriented Gradient (HOG Dan Histogram Of Curvature (HoC

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Agus Wahyu Widodo

2015-08-01

Full Text Available Abstrak Tanda tangan dengan sifat uniknya merupakan salah satu dari sekian banyak atribut personal yang diterima secara luas untuk verifikasi indentitas seseorang, alat pembuktian kepemilikan berbagai transaksi atau dokumen di dalam masyarakat. Keberhasilan penggunaan ciri gradien dan curvature dalam bidang-bidang penelitian pengenalan pola dan bahwa tanda tangan dapat dikatakan merupakan hasil tulisan tangan yang tersusun atas beragam garis dan lengkungan (curve yang memiliki arah atau orientasi merupakan alasan bahwa kedua ciri tersebut digunakan sebagai metoda verifikasi tanda tangan offline di penelitian ini. Berbagai implementasi dari pre-processing, ekstraksi dan representasi ciri, dan pembelajaran SVM serta usaha perbaikan yang telah dilakukan dalam penelitian ini menunjukkan hasil bahwa ciri HOG dan HoC mampu dimanfaatkan dalam proses verifikasi tanda tangan secara offline.  Pada basis data GPDS960Signature, HOG dan HoC yang dihitung pada ukuran sel 30 x 30 piksel memberikan dengan nilai %FRR terbaik 26,90 dan %FAR 37,56.  Sedangkan pada basis data FUM-PHSDB, HOG dn HoC yang dihitung pada ukuran 60 x 60 piksel memberikan nilai %FRR terbaik 4 dan %FAR 57. Kata kunci: verifikasi tanda tangan, curvature, orientation, gradient, histogram of curvature (HoC, histogram of oriented gradient (HOG Abstract Signature with unique properties is one of the many personal attributes that are widely accepted to verify a person's identity, proof of ownership transactions instrument or document in the community. The successful use of gradient and curvature feature in the research fields of pattern recognition is the reason that both of these features are used as an offline signature verification method in this study. Various implementations of preprocessing, feature extraction and representation, and SVM learning has been done in the study showed results that HOG and HoC feature can be utilized in the process of offline signature verification.  HOG and

Postimplantation Analysis Enables Improvement of Dose-Volume Histograms and Reduction of Toxicity for Permanent Seed Implantation

International Nuclear Information System (INIS)

Wust, Peter; Postrach, Johanna; Kahmann, Frank; Henkel, Thomas; Graf, Reinhold; Cho, Chie Hee; Budach, Volker; Boehmer, Dirk

2008-01-01

Purpose: To demonstrate how postimplantation analysis is useful for improving permanent seed implantation and reducing toxicity. Patients and Methods: We evaluated 197 questionnaires completed by patients after permanent seed implantation (monotherapy between 1999 and 2003). For 70% of these patients, a computed tomography was available to perform postimplantation analysis. The index doses and volumes of the dose-volume histograms (DVHs) were determined and categorized with respect to the date of implantation. Differences in symptom scores relative to pretherapeutic status were analyzed with regard to follow-up times and DVH descriptors. Acute and subacute toxicities in a control group of 117 patients from an earlier study (June 1999 to September 2001) by Wust et al. (2004) were compared with a matched subgroup from this study equaling 110 patients treated between October 2001 and August 2003. Results: Improved performance, identifying a characteristic time dependency of DVH parameters (after implantation) and toxicity scores, was demonstrated. Although coverage (volume covered by 100% of the prescription dose of the prostate) increased slightly, high-dose regions decreased with the growing experience of the users. Improvement in the DVH and a reduction of toxicities were found in the patient group implanted in the later period. A decline in symptoms with follow-up time counteracts this gain of experience and must be considered. Urinary and sexual discomfort was enhanced by dose heterogeneities (e.g., dose covering 10% of the prostate volume, volume covered by 200% of prescription dose). In contrast, rectal toxicities correlated with exposed rectal volumes, especially the rectal volume covered by 100% of the prescription dose. Conclusion: The typical side effects occurring after permanent seed implantation can be reduced by improving the dose distributions. An improvement in dose distributions and a reduction of toxicities were identified with elapsed time between

Yet Another Method for Image Segmentation based on Histograms and Heuristics

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Horia-Nicolai L. Teodorescu

2012-07-01

Full Text Available We introduce a method for image segmentation that requires little computations, yet providing comparable results to other methods. While the proposed method resembles to the known ones based on histograms, it is still different in the use of the gray level distribution. When to the basic procedure we add several heuristic rules, the method produces results that, in some cases, may outperform the results produced by the known methods. The paper reports preliminary results. More details on the method, improvements, and results will be presented in a future paper.

Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

Science.gov (United States)

Warner, Graham C.; Helmer, Karl G.

2018-01-01

As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor). PMID:29568257

Thresholding using two-dimensional histogram and watershed algorithm in the luggage inspection system

International Nuclear Information System (INIS)

Chen Jingyun; Cong Peng; Song Qi

2006-01-01

The authors present a new DR image segmentation method based on two-dimensional histogram and watershed algorithm. The authors use watershed algorithm to locate threshold on the vertical projection plane of two-dimensional histogram. This method is applied to the segmentation of DR images produced by luggage inspection system with DR-CT. The advantage of this method is also analyzed. (authors)

Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

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Vishakha Kelkar

2017-01-01

Full Text Available In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient’s information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image.

Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

Science.gov (United States)

Tuckley, Kushal

2017-01-01

In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient's information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB) obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image. PMID:29104744

Flat-histogram methods in quantum Monte Carlo simulations: Application to the t-J model

International Nuclear Information System (INIS)

Diamantis, Nikolaos G.; Manousakis, Efstratios

2016-01-01

We discuss that flat-histogram techniques can be appropriately applied in the sampling of quantum Monte Carlo simulation in order to improve the statistical quality of the results at long imaginary time or low excitation energy. Typical imaginary-time correlation functions calculated in quantum Monte Carlo are subject to exponentially growing errors as the range of imaginary time grows and this smears the information on the low energy excitations. We show that we can extract the low energy physics by modifying the Monte Carlo sampling technique to one in which configurations which contribute to making the histogram of certain quantities flat are promoted. We apply the diagrammatic Monte Carlo (diag-MC) method to the motion of a single hole in the t-J model and we show that the implementation of flat-histogram techniques allows us to calculate the Green's function in a wide range of imaginary-time. In addition, we show that applying the flat-histogram technique alleviates the “sign”-problem associated with the simulation of the single-hole Green's function at long imaginary time. (paper)

Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization

Science.gov (United States)

Chiu, Chung-Cheng; Ting, Chih-Chung

2016-01-01

Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE) is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE) is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA), which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods. PMID:27338412

Contrast Enhancement Algorithm Based on Gap Adjustment for Histogram Equalization

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Chung-Cheng Chiu

2016-06-01

Full Text Available Image enhancement methods have been widely used to improve the visual effects of images. Owing to its simplicity and effectiveness histogram equalization (HE is one of the methods used for enhancing image contrast. However, HE may result in over-enhancement and feature loss problems that lead to unnatural look and loss of details in the processed images. Researchers have proposed various HE-based methods to solve the over-enhancement problem; however, they have largely ignored the feature loss problem. Therefore, a contrast enhancement algorithm based on gap adjustment for histogram equalization (CegaHE is proposed. It refers to a visual contrast enhancement algorithm based on histogram equalization (VCEA, which generates visually pleasing enhanced images, and improves the enhancement effects of VCEA. CegaHE adjusts the gaps between two gray values based on the adjustment equation, which takes the properties of human visual perception into consideration, to solve the over-enhancement problem. Besides, it also alleviates the feature loss problem and further enhances the textures in the dark regions of the images to improve the quality of the processed images for human visual perception. Experimental results demonstrate that CegaHE is a reliable method for contrast enhancement and that it significantly outperforms VCEA and other methods.

Calculation of normal tissue complication probability and dose-volume histogram reduction schemes for tissues with a critical element architecture

International Nuclear Information System (INIS)

Niemierko, Andrzej; Goitein, Michael

1991-01-01

The authors investigate a model of normal tissue complication probability for tissues that may be represented by a critical element architecture. They derive formulas for complication probability that apply to both a partial volume irradiation and to an arbitrary inhomogeneous dose distribution. The dose-volume isoeffect relationship which is a consequence of a critical element architecture is discussed and compared to the empirical power law relationship. A dose-volume histogram reduction scheme for a 'pure' critical element model is derived. In addition, a point-based algorithm which does not require precomputation of a dose-volume histogram is derived. The existing published dose-volume histogram reduction algorithms are analyzed. The authors show that the existing algorithms, developed empirically without an explicit biophysical model, have a close relationship to the critical element model at low levels of complication probability. However, it is also showed that they have aspects which are not compatible with a critical element model and the authors propose a modification to one of them to circumvent its restriction to low complication probabilities. (author). 26 refs.; 7 figs

Estimation of pneumonitis risk in three-dimensional treatment planning using dose-volume histogram analysis

International Nuclear Information System (INIS)

Oetzel, Dieter; Schraube, Peter; Hensley, Frank; Sroka-Perez, Gabriele; Menke, Markus; Flentje, Michael

1995-01-01

Purpose: Investigations to study correlations between the estimations of biophysical models in three dimensional (3D) treatment planning and clinical observations are scarce. The development of clinically symptomatic pneumonitis in the radiotherapy of thoracic malignomas was chosen to test the predictive power of Lyman's normal tissue complication probability (NTCP) model for the assessment of side effects for nonuniform irradiation. Methods and Materials: In a retrospective analysis individual computed-tomography-based 3D dose distributions of a random sample of (46(20)) patients with lung/esophageal cancer were reconstructed. All patients received tumor doses between 50 and 60 Gy in a conventional treatment schedule. Biological isoeffective dose-volume histograms (DVHs) were used for the calculation of complication probabilities after applying Lyman's and Kutcher's DVH-reduction algorithm. Lung dose statistics were performed for single lung (involved ipsilateral and contralateral) and for the lung as a paired organ. Results: In the lung cancer group, about 20% of the patients (9 out of 46) developed pneumonitis 3-12 (median 7.5) weeks after completion of radiotherapy. For the majority of these lung cancer patients, the involved ipsilateral lung received a much higher dose than the contralateral lung, and the pneumonitis patients had on average a higher lung exposure with a doubling of the predicted complication risk (38% vs. 20%). The lower lung exposure for the esophagus patients resulted in a mean lung dose of 13.2 Gy (lung cancer: 20.5 Gy) averaged over all patients in correlation with an almost zero complication risk and only one observed case of pneumonitis (1 out of 20). To compare the pneumonitis risk estimations with observed complication rates, the patients were ranked into bins of mean ipsilateral lung dose. Particularly, in the bins with the highest patient numbers, a good correlation was achieved. Agreement was not reached for the lung functioning as

Dose-volume histograms for optimization of treatment plans illustrated by the example of oesophagus carcinoma

International Nuclear Information System (INIS)

Roth, J.; Huenig, R.; Huegli, C.

1995-01-01

Using the example of oesophagus carcinoma, dose-volume histograms for diverse treatment techniques are calculated and judged by means of multiplanar isodose representations. The selected treatment plans are ranked with the aid of the dose-volume histograms. We distinguish the tissue inside and outside of the target volume. The description of the spatial dose distribution in dependence of the different volumes and the respective fractions of the tumor dose therein with the help of dose-volume histograms brings about a correlation between the physical parameters and the biological effects. In addition one has to bear in mind the consequences of measures that influence the reaction and the side-effects of radiotherapy (e.g. chemotherapy), i.e. the recuperation of the tissues that were irradiated intentionally or inevitably. Taking all that into account it is evident that the dose-volume histograms are a powerful tool for assessing the quality of treatment plans. (orig./MG) [de

Boundary condition histograms for modulated phases

International Nuclear Information System (INIS)

Benakli, M.; Gabay, M.; Saslow, W.M.

1997-11-01

Boundary conditions strongly affect the results of numerical computations for finite size inhomogeneous or incommensurate structures. We present a method which allows to deal with this problem, both for ground state and for critical properties: it combines fluctuating boundary conditions and specific histogram techniques. Our approach concerns classical as well as quantum systems. In particular, current-current correlation functions, which probe large scale coherence of the states, can be accurately evaluated. We illustrate our method on a frustrated two dimensional XY model. (author)

Measurement of susceptibility artifacts with histogram-based reference value on magnetic resonance images according to standard ASTM F2119.

Science.gov (United States)

Heinrich, Andreas; Teichgräber, Ulf K; Güttler, Felix V

2015-12-01

The standard ASTM F2119 describes a test method for measuring the size of a susceptibility artifact based on the example of a passive implant. A pixel in an image is considered to be a part of an image artifact if the intensity is changed by at least 30% in the presence of a test object, compared to a reference image in which the test object is absent (reference value). The aim of this paper is to simplify and accelerate the test method using a histogram-based reference value. Four test objects were scanned parallel and perpendicular to the main magnetic field, and the largest susceptibility artifacts were measured using two methods of reference value determination (reference image-based and histogram-based reference value). The results between both methods were compared using the Mann-Whitney U-test. The difference between both reference values was 42.35 ± 23.66. The difference of artifact size was 0.64 ± 0.69 mm. The artifact sizes of both methods did not show significant differences; the p-value of the Mann-Whitney U-test was between 0.710 and 0.521. A standard-conform method for a rapid, objective, and reproducible evaluation of susceptibility artifacts could be implemented. The result of the histogram-based method does not significantly differ from the ASTM-conform method.

The equivalent Histograms in clinical practice; Los histogramas equivalentes en la practica clinica

Energy Technology Data Exchange (ETDEWEB)

Pizarro Trigo, F.; Teijeira Garcia, M.; Zaballos Carrera, S.

2013-07-01

Is frequently abused of The tolerances established for organ at risk [1] in diagrams of standard fractionation (2Gy/session, 5 sessions per week) when applied to Dose-Volume histograms non-standard schema. The purpose of this work is to establish when this abuse may be more important and realize a transformation of fractionation non-standard of histograms dosis-volumen. Is exposed a case that can be useful to make clinical decisions. (Author)

A comparative analysis of machine learning approaches for plant disease identification

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Hidayat ur Rahman

2017-08-01

Full Text Available Background: The problems to leaf in plants are very severe and they usually shorten the lifespan of plants. Leaf diseases are mainly caused due to three types of attacks including viral, bacterial or fungal. Diseased leaves reduce the crop production and affect the agricultural economy. Since agriculture plays a vital role in the economy, thus effective mechanism is required to detect the problem in early stages. Methods: Traditional approaches used for the identification of diseased plants are based on field visits which is time consuming and tedious. In this paper a comparative analysis of machine learning approaches has been presented for the identification of healthy and non-healthy plant leaves. For experimental purpose three different types of plant leaves have been selected namely, cabbage, citrus and sorghum. In order to classify healthy and non-healthy plant leaves color based features such as pixels, statistical features such as mean, standard deviation, min, max and descriptors such as Histogram of Oriented Gradients (HOG have been used. Results: 382 images of cabbage, 539 images of citrus and 262 images of sorghum were used as the primary dataset. The 40% data was utilized for testing and 60% were used for training which consisted of both healthy and damaged leaves. The results showed that random forest classifier is the best machine method for classification of healthy and diseased plant leaves. Conclusion: From the extensive experimentation it is concluded that features such as color information, statistical distribution and histogram of gradients provides sufficient clue for the classification of healthy and non-healthy plants.

optBINS: Optimal Binning for histograms

Science.gov (United States)

Knuth, Kevin H.

2018-03-01

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

Real time object localization based on histogram of s-RGB

Science.gov (United States)

Mudjirahardjo, Panca; Suyono, Hadi; Setyawan, Raden Arief

2017-09-01

Object localization is the first task in pattern detection and recognition. This task is very important due to it reduces the searching time to the interest object. In this paper we introduce our novel method of object localization based on color feature. Our novel method is a histogram of s-RGB. This histogram is used in the training phase to determine the color dominant in the initial Region of Interest (ROI). Then this information is used to label the interest object. To reduce noise and localize the interest object, we apply the row and column density function of pixels. The comparison result with some processes, our system gives a best result and takes a short computation time of 26.56 ms, in the video rate of 15 frames per second (fps).

Sensitivity of volumetric modulated arc therapy patient specific QA results to multileaf collimator errors and correlation to dose volume histogram based metrics.

LENUS (Irish Health Repository)

Coleman, Linda

2013-11-01

This study investigates the impact of systematic multileaf collimator (MLC) positional errors on gamma analysis results used for quality assurance (QA) of Rapidarc treatments. In addition, this study evaluates the relationship of these gamma analysis results and clinical dose volume histogram metrics (DVH) for Rapidarc treatment plans.

Sistem Pendeteksi Kualitas Daging Dengan Ekualisasi Histogram Dan Thresholding Berbasis Android

Directory of Open Access Journals (Sweden)

Anggit Sri Herlambang

2016-04-01

Full Text Available Kebutuhan daging sapi yang meningkat sering dimanfaatkan oleh penjual daging sapi untuk melakukan kecurangan. Kecurangan yang sering dimanfaatkan biasanya dalam hal kualitas daging sapi. Kualitas daging ditentukan oleh beberapa parameter, termasuk parameter ukuran, tekstur, karakteristik warna, bau daging dan lain - lain. Parameter adalah salah satu faktor penting untuk menentukan kualitas daging. Umumnya dalam menentukan kualitas daging dilakukan dengan menggunakan indra penglihatan. Sehingga cara manual masih bersifat subjektif dalam menilai kualitas daging. Penelitian ini bertujuan untuk merancang aplikasi sistem pendeteksi kualitas daging dengan sampel 20 citra daging data uji. Sistem pendeteksi kualitas daging dengan ekualisasi histogram dan thresholding berbasis android ini dibangun dengan menggunakan bahasa pemrograman berbasis Android yang terintegrasi dengan SDK Android, Eclipse dan library OpenCV. Metode yang digunakan menggunakan metode pra-pengolahan ekualisasi histogram dan segmentasi thresholding pengolahan citra. Deteksi kualitas daging dilakukan dengan mencari nilai statistik ekstraksi ciri citra berdasarkan data citra daging dari penelitian. Hasil penelitian ini adalah dapat menentukan nilai statistik mean dan standar deviasi dari hasil citra olahan ekualisasi histogram dan thresholding disertai analisis kualitas citra daging sapi. Pengujian black box dari aplikasi sistem pendeteksi kualitas daging ini menunjukkan bahwa semua fungsi yang terdapat pada aplikasi ini telah berhasil berjalan sesuai fungsinya. Penelitian ini harapannya bisa digunakan untuk membantu penelitian tahap selanjutnya.

LOR-OSEM: statistical PET reconstruction from raw line-of-response histograms

International Nuclear Information System (INIS)

Kadrmas, Dan J

2004-01-01

Iterative statistical reconstruction methods are becoming the standard in positron emission tomography (PET). Conventional maximum-likelihood expectation-maximization (MLEM) and ordered-subsets (OSEM) algorithms act on data which have been pre-processed into corrected, evenly-spaced histograms; however, such pre-processing corrupts the Poisson statistics. Recent advances have incorporated attenuation, scatter and randoms compensation into the iterative reconstruction. The objective of this work was to incorporate the remaining pre-processing steps, including arc correction, to reconstruct directly from raw unevenly-spaced line-of-response (LOR) histograms. This exactly preserves Poisson statistics and full spatial information in a manner closely related to listmode ML, making full use of the ML statistical model. The LOR-OSEM algorithm was implemented using a rotation-based projector which maps directly to the unevenly-spaced LOR grid. Simulation and phantom experiments were performed to characterize resolution, contrast and noise properties for 2D PET. LOR-OSEM provided a beneficial noise-resolution tradeoff, outperforming AW-OSEM by about the same margin that AW-OSEM outperformed pre-corrected OSEM. The relationship between LOR-ML and listmode ML algorithms was explored, and implementation differences are discussed. LOR-OSEM is a viable alternative to AW-OSEM for histogram-based reconstruction with improved spatial resolution and noise properties

Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability

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Minjie Wan

2017-06-01

Full Text Available In order to detect both bright and dark small moving targets effectively in infrared (IR video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.

Improved dose–volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

International Nuclear Information System (INIS)

Cheng Lishui; Hobbs, Robert F; Sgouros, George; Frey, Eric C; Segars, Paul W

2013-01-01

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose–volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator–detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less

Improved dose-volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

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Cheng, Lishui; Hobbs, Robert F.; Segars, Paul W.; Sgouros, George; Frey, Eric C.

2013-06-01

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less

Comparison of screen film combinations: results of a contrast detail study and interactive image quality analysis. Pt. III. Trimodal histograms of grey-value distributions found in the images of grouped lead bar pattern

International Nuclear Information System (INIS)

Hagemann, G.; Eichbaum, G.; Stamm, G.

1998-01-01

The following four screen film combinations were compared: (a) a combination of anticrossover film and UV-light emitting screens, (b) a combination of blue-light emitting screens and film and (c) two conventional green fluorescing screen film combinations. Radiographs of a specially designed plexiglass phantom (0.2 x 0.2 x 0.12 m 3 ) with bar patterns of lead and plaster and of air, respectively were obtained using the following parameters: 12 pulse generator, 0.6 mm focus size, 4.7 mm aluminum prefilter, a grid with 40 lines/cm (12:1) and a focus-detector distance of 1.15 m. Image analyses was performed using an Ibas system and a Zeiss Kontron computer. Display conditions were the following: display distance 0.12 m, a vario film objective 35/70 (Zeiss), a video camera tube with a PbO photocathode, 625 lines (Siemens Heimann), an Ibas image matrix of 512 x 512 pixels with a spatial resolution of ca. 7 cycles/mm, the projected matrix area was 5000 μm 2 . Maxima in the histograms of a grouped bar pattern were estimated as mean values from the bar and gap regions ('mean value method'). They were used to calculate signal contrast, standard deviations of the means and scatter fraction. Comparing the histograms with respect to spatial resolution and kV setting a clear advantage of the UVR system becomes obvious. The quantitative analysis yielded a maximum spatial resolution of approx. 3 cycles/mm for the UVR system at 60 kV which decreased to half of this value at 117 kV caused by the increasing influence of scattered radiation. A ranking of screen-film systems with respect to image quality and dose requirement is presented. For its evaluation an interactive image analysis using the mean value method was found to be superior to signal/noise ratio measurements and visual analysis in respect to diagnostic relevance and saving of time. (orig./MG) [de

Whole-tumor MRI histogram analyses of hepatocellular carcinoma: Correlations with Ki-67 labeling index.

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Hu, Xin-Xing; Yang, Zhao-Xia; Liang, He-Yue; Ding, Ying; Grimm, Robert; Fu, Cai-Xia; Liu, Hui; Yan, Xu; Ji, Yuan; Zeng, Meng-Su; Rao, Sheng-Xiang

2017-08-01

To evaluate whether whole-tumor histogram-derived parameters for an apparent diffusion coefficient (ADC) map and contrast-enhanced magnetic resonance imaging (MRI) could aid in assessing Ki-67 labeling index (LI) of hepatocellular carcinoma (HCC). In all, 57 patients with HCC who underwent pretreatment MRI with a 3T MR scanner were included retrospectively. Histogram parameters including mean, median, standard deviation, skewness, kurtosis, and percentiles (5 th , 25 th , 75 th , 95 th ) were derived from the ADC map and MR enhancement. Correlations between histogram parameters and Ki-67 LI were evaluated and differences between low Ki-67 (≤10%) and high Ki-67 (>10%) groups were assessed. Mean, median, 5 th , 25 th , 75 th percentiles of ADC, and mean, median, 25 th , 75 th , 95 th percentiles of enhancement of arterial phase (AP) demonstrated significant inverse correlations with Ki-67 LI (rho up to -0.48 for ADC, -0.43 for AP) and showed significant differences between low and high Ki-67 groups (P Histogram-derived parameters of ADC and AP were potentially helpful for predicting Ki-67 LI of HCC. 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:383-392. © 2016 International Society for Magnetic Resonance in Medicine.

Breast density pattern characterization by histogram features and texture descriptors

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Pedro Cunha Carneiro

2017-04-01

Full Text Available Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

Visual Contrast Enhancement Algorithm Based on Histogram Equalization

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Ting, Chih-Chung; Wu, Bing-Fei; Chung, Meng-Liang; Chiu, Chung-Cheng; Wu, Ya-Ching

2015-01-01

Image enhancement techniques primarily improve the contrast of an image to lend it a better appearance. One of the popular enhancement methods is histogram equalization (HE) because of its simplicity and effectiveness. However, it is rarely applied to consumer electronics products because it can cause excessive contrast enhancement and feature loss problems. These problems make the images processed by HE look unnatural and introduce unwanted artifacts in them. In this study, a visual contrast enhancement algorithm (VCEA) based on HE is proposed. VCEA considers the requirements of the human visual perception in order to address the drawbacks of HE. It effectively solves the excessive contrast enhancement problem by adjusting the spaces between two adjacent gray values of the HE histogram. In addition, VCEA reduces the effects of the feature loss problem by using the obtained spaces. Furthermore, VCEA enhances the detailed textures of an image to generate an enhanced image with better visual quality. Experimental results show that images obtained by applying VCEA have higher contrast and are more suited to human visual perception than those processed by HE and other HE-based methods. PMID:26184219

Variational Histogram Equalization for Single Color Image Defogging

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Li Zhou

2016-01-01

Full Text Available Foggy images taken in the bad weather inevitably suffer from contrast loss and color distortion. Existing defogging methods merely resort to digging out an accurate scene transmission in ignorance of their unpleasing distortion and high complexity. Different from previous works, we propose a simple but powerful method based on histogram equalization and the physical degradation model. By revising two constraints in a variational histogram equalization framework, the intensity component of a fog-free image can be estimated in HSI color space, since the airlight is inferred through a color attenuation prior in advance. To cut down the time consumption, a general variation filter is proposed to obtain a numerical solution from the revised framework. After getting the estimated intensity component, it is easy to infer the saturation component from the physical degradation model in saturation channel. Accordingly, the fog-free image can be restored with the estimated intensity and saturation components. In the end, the proposed method is tested on several foggy images and assessed by two no-reference indexes. Experimental results reveal that our method is relatively superior to three groups of relevant and state-of-the-art defogging methods.

Visual Contrast Enhancement Algorithm Based on Histogram Equalization

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Chih-Chung Ting

2015-07-01

Full Text Available Image enhancement techniques primarily improve the contrast of an image to lend it a better appearance. One of the popular enhancement methods is histogram equalization (HE because of its simplicity and effectiveness. However, it is rarely applied to consumer electronics products because it can cause excessive contrast enhancement and feature loss problems. These problems make the images processed by HE look unnatural and introduce unwanted artifacts in them. In this study, a visual contrast enhancement algorithm (VCEA based on HE is proposed. VCEA considers the requirements of the human visual perception in order to address the drawbacks of HE. It effectively solves the excessive contrast enhancement problem by adjusting the spaces between two adjacent gray values of the HE histogram. In addition, VCEA reduces the effects of the feature loss problem by using the obtained spaces. Furthermore, VCEA enhances the detailed textures of an image to generate an enhanced image with better visual quality. Experimental results show that images obtained by applying VCEA have higher contrast and are more suited to human visual perception than those processed by HE and other HE-based methods.

RGB Color Cube-Based Histogram Specification for Hue-Preserving Color Image Enhancement

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Kohei Inoue

2017-07-01

Full Text Available A large number of color image enhancement methods are based on the methods for grayscale image enhancement in which the main interest is contrast enhancement. However, since colors usually have three attributes, including hue, saturation and intensity of more than only one attribute of grayscale values, the naive application of the methods for grayscale images to color images often results in unsatisfactory consequences. Conventional hue-preserving color image enhancement methods utilize histogram equalization (HE for enhancing the contrast. However, they cannot always enhance the saturation simultaneously. In this paper, we propose a histogram specification (HS method for enhancing the saturation in hue-preserving color image enhancement. The proposed method computes the target histogram for HS on the basis of the geometry of RGB (rad, green and blue color space, whose shape is a cube with a unit side length. Therefore, the proposed method includes no parameters to be set by users. Experimental results show that the proposed method achieves higher color saturation than recent parameter-free methods for hue-preserving color image enhancement. As a result, the proposed method can be used for an alternative method of HE in hue-preserving color image enhancement.

Calculation of complication probability of pion treatment at PSI using dose-volume histograms

International Nuclear Information System (INIS)

Nakagawa, Keiichi; Akanuma, Atsuo; Aoki, Yukimasa

1991-01-01

In the conformation technique a target volume is irradiated uniformly as in conventional radiations, whereas surrounding tissue and organs are nonuniformly irradiated. Clinical data on radiation injuries that accumulate with conventional radiation are not applicable without appropriate compensation. Recently a putative solution of this problem was proposed by Lyman using dose-volume histograms. This histogram reduction method reduces a given dose-volume histogram of an organ to a single step which corresponds to the equivalent complication probability by interpolation. As a result it converts nonuniform radiation into a unique dose to the whole organ which has the equivalent likelihood of radiation injury. This method is based on low LET radiation with conventional fractionation schedules. When it is applied to high LET radiation such as negative pion treatment, a high LET dose should be converted to an equivalent photon dose using an appropriate value of RBE. In the present study the histogram reduction method was applied to actual patients treated by the negative pion conformation technique at the Paul Scherrer Institute. Out of evaluable 90 cases of pelvic tumors, 16 developed grade III-IV bladder injury, and 7 developed grade III-IV rectal injury. The 90 cases were divided into roughly equal groups according to the equivalent doses to the entire bladder and rectum. Complication rates and equivalent doses to the full organs in these groups could be represented by a sigmoid dose-effect relation. When RBE from a pion dose to a photon dose is assumed to be 2.1 for bladder injury, the rates of bladder complications fit best to the theoretical complication curve. When the RBE value was 2.3, the rates of rectal injury fit the theoretical curve best. These values are close to the conversion factor of 2.0 that is used in clinical practice at PSI. This agreement suggests the clinical feasibility of the histogram reduction method in conformation radiotherapy. (author)

Comparison of dose-volume histograms for Tomo therapy, linear accelerator-based 3D conformal radiation therapy, and intensity-modulated radiation therapy

International Nuclear Information System (INIS)

Ji, Youn-Sang; Dong, Kyung-Rae; Kim, Chang-Bok; Choi, Seong-Kwan; Chung, Woon-Kwan; Lee, Jong-Woong

2011-01-01

Highlights: → Evaluation of DVH from 3D CRT, IMRT and Tomo therapy was conducted for tumor therapy. → The doses of GTV and CTV were compared using DVHs from 3D CRT, IMRT and Tomo therapy. → The GTV was higher when Tomo therapy was used, while the doses of critical organ were low. → They said that Tomo therapy satisfied the goal of radiation therapy more than the others. - Abstract: Evaluation of dose-volume histograms from three-dimensional conformal radiation therapy (3D CRT), intensity-modulated radiation therapy (IMRT), and Tomo therapy was conducted. These three modalities are among the diverse treatment systems available for tumor therapy. Three patients who received tumor therapy for a malignant oligodendroglioma in the cranium, nasopharyngeal carcinoma in the cervical neck, and prostate cancer in the pelvis were selected as study subjects. Therapy plans were made for the three patients before dose-volume histograms were obtained. The doses of the gross tumor volume (GTV) and the clinical target volume (CTV) were compared using the dose-volume histograms obtained from the LINAC-based 3D CRT, IMRT planning station (Varian Eclipse-Varian, version 8.1), and Tomo therapy planning station. In addition, the doses of critical organs in the cranium, cervix, and pelvis that should be protected were compared. The GTV was higher when Tomo therapy was used compared to 3D CRT and the LINAC-based IMRT, while the doses of critical organ tissues that required protection were low. These results demonstrated that Tomo therapy satisfied the ultimate goal of radiation therapy more than the other therapies.

Ultrasonic histogram assessment of early response to concurrent chemo-radiotherapy in patients with locally advanced cervical cancer: a feasibility study.

Science.gov (United States)

Xu, Yan; Ru, Tong; Zhu, Lijing; Liu, Baorui; Wang, Huanhuan; Zhu, Li; He, Jian; Liu, Song; Zhou, Zhengyang; Yang, Xiaofeng

To monitor early response for locally advanced cervical cancers undergoing concurrent chemo-radiotherapy (CCRT) by ultrasonic histogram. B-mode ultrasound examinations were performed at 4 time points in thirty-four patients during CCRT. Six ultrasonic histogram parameters were used to assess the echogenicity, homogeneity and heterogeneity of tumors. I peak increased rapidly since the first week after therapy initiation, whereas W low , W high and A high changed significantly at the second week. The average ultrasonic histogram progressively moved toward the right and converted into more symmetrical shape. Ultrasonic histogram could be served as a potential marker to monitor early response during CCRT. Copyright © 2018 Elsevier Inc. All rights reserved.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma.

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Surov, Alexey; Meyer, Hans Jonas; Leifels, Leonard; Höhn, Anne-Kathrin; Richter, Cindy; Winter, Karsten

2018-04-20

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K trans , V e , and K ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with K trans min ( p = -0.386, P = 0.043) and s K trans skewness ( p = 0.382, P = 0.045), V e min ( p = -0.473, P = 0.011), Ve entropy ( p = 0.424, P = 0.025), and K ep entropy ( p = 0.464, P = 0.013). Cell count correlated with K trans kurtosis ( p = 0.40, P = 0.034), V e entropy ( p = 0.475, P = 0.011). Total nucleic area correlated with V e max ( p = 0.386, P = 0.042) and V e entropy ( p = 0.411, P = 0.030). In G1/2 tumors, only K trans entropy correlated well with total ( P =0.78, P =0.013) and average nucleic areas ( p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min ( p = -0.552, P = 0.022) and V e entropy ( p = 0.524, P = 0.031). Ve max correlated with total nucleic area ( p = 0.483, P = 0.049). Kep max correlated with total area ( p = -0.51, P = 0.037), and K ep entropy with KI 67 ( p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of K trans , V e , and K ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Investigating the Role of Global Histogram Equalization Technique for 99mTechnetium-Methylene diphosphonate Bone Scan Image Enhancement.

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Pandey, Anil Kumar; Sharma, Param Dev; Dheer, Pankaj; Parida, Girish Kumar; Goyal, Harish; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

99m Technetium-methylene diphosphonate ( 99m Tc-MDP) bone scan images have limited number of counts per pixel, and hence, they have inferior image quality compared to X-rays. Theoretically, global histogram equalization (GHE) technique can improve the contrast of a given image though practical benefits of doing so have only limited acceptance. In this study, we have investigated the effect of GHE technique for 99m Tc-MDP-bone scan images. A set of 89 low contrast 99m Tc-MDP whole-body bone scan images were included in this study. These images were acquired with parallel hole collimation on Symbia E gamma camera. The images were then processed with histogram equalization technique. The image quality of input and processed images were reviewed by two nuclear medicine physicians on a 5-point scale where score of 1 is for very poor and 5 is for the best image quality. A statistical test was applied to find the significance of difference between the mean scores assigned to input and processed images. This technique improves the contrast of the images; however, oversaturation was noticed in the processed images. Student's t -test was applied, and a statistically significant difference in the input and processed image quality was found at P histogram equalization technique in combination with some other postprocessing technique is useful.

Application of histogram analysis for the evaluation of vascular permeability in glioma by the K2 parameter obtained with the dynamic susceptibility contrast method: Comparisons with Ktrans obtained with the dynamic contrast enhance method and cerebral blood volume.

Science.gov (United States)

Taoka, Toshiaki; Kawai, Hisashi; Nakane, Toshiki; Hori, Saeka; Ochi, Tomoko; Miyasaka, Toshiteru; Sakamoto, Masahiko; Kichikawa, Kimihiko; Naganawa, Shinji

2016-09-01

The "K2" value is a factor that represents the vascular permeability of tumors and can be calculated from datasets obtained with the dynamic susceptibility contrast (DSC) method. The purpose of the current study was to correlate K2 with Ktrans, which is a well-established permeability parameter obtained with the dynamic contrast enhance (DCE) method, and determine the usefulness of K2 for glioma grading with histogram analysis. The subjects were 22 glioma patients (Grade II: 5, III: 6, IV: 11) who underwent DSC studies, including eight patients in which both DSC and DCE studies were performed on separate days within 10days. We performed histogram analysis of regions of interest of the tumors and acquired 20th percentile values for leakage-corrected cerebral blood volume (rCBV20%ile), K2 (K220%ile), and for patients who underwent a DCE study, Ktrans (Ktrans20%ile). We evaluated the correlation between K220%ile and Ktrans20%ile and the statistical difference between rCBV20%ile and K220%ile. We found a statistically significant correlation between K220%ile and Ktrans20%ile (r=0.717, pK220%ile showed a statistically significant (pK2 value calculated from the DSC dataset, which can be obtained with a short acquisition time, showed a correlation with Ktrans obtained with the DCE method and may be useful for glioma grading when analyzed with histogram analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Whole Tumor Histogram-profiling of Diffusion-Weighted Magnetic Resonance Images Reflects Tumorbiological Features of Primary Central Nervous System Lymphoma.

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Schob, Stefan; Münch, Benno; Dieckow, Julia; Quäschling, Ulf; Hoffmann, Karl-Titus; Richter, Cindy; Garnov, Nikita; Frydrychowicz, Clara; Krause, Matthias; Meyer, Hans-Jonas; Surov, Alexey

2018-04-01

Diffusion weighted imaging (DWI) quantifies motion of hydrogen nuclei in biological tissues and hereby has been used to assess the underlying tissue microarchitecture. Histogram-profiling of DWI provides more detailed information on diffusion characteristics of a lesion than the standardly calculated values of the apparent diffusion coefficient (ADC)-minimum, mean and maximum. Hence, the aim of our study was to investigate, which parameters of histogram-profiling of DWI in primary central nervous system lymphoma can be used to specifically predict features like cellular density, chromatin content and proliferative activity. Pre-treatment ADC maps of 21 PCNSL patients (8 female, 13 male, 28-89 years) from a 1.5T system were used for Matlab-based histogram profiling. Results of histopathology (H&E staining) and immunohistochemistry (Ki-67 expression) were quantified. Correlations between histogram-profiling parameters and neuropathologic examination were calculated using SPSS 23.0. The lower percentiles (p10 and p25) showed significant correlations with structural parameters of the neuropathologic examination (cellular density, chromatin content). The highest percentile, p90, correlated significantly with Ki-67 expression, resembling proliferative activity. Kurtosis of the ADC histogram correlated significantly with cellular density. Histogram-profiling of DWI in PCNSL provides a comprehensible set of parameters, which reflect distinct tumor-architectural and tumor-biological features, and hence, are promising biomarkers for treatment response and prognosis. Copyright © 2018. Published by Elsevier Inc.

3-D Image Analysis of Fluorescent Drug Binding

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M. Raquel Miquel

2005-01-01

Full Text Available Fluorescent ligands provide the means of studying receptors in whole tissues using confocal laser scanning microscopy and have advantages over antibody- or non-fluorescence-based method. Confocal microscopy provides large volumes of images to be measured. Histogram analysis of 3-D image volumes is proposed as a method of graphically displaying large amounts of volumetric image data to be quickly analyzed and compared. The fluorescent ligand BODIPY FL-prazosin (QAPB was used in mouse aorta. Histogram analysis reports the amount of ligand-receptor binding under different conditions and the technique is sensitive enough to detect changes in receptor availability after antagonist incubation or genetic manipulations. QAPB binding was concentration dependent, causing concentration-related rightward shifts in the histogram. In the presence of 10 μM phenoxybenzamine (blocking agent, the QAPB (50 nM histogram overlaps the autofluorescence curve. The histogram obtained for the 1D knockout aorta lay to the left of that of control and 1B knockout aorta, indicating a reduction in 1D receptors. We have shown, for the first time, that it is possible to graphically display binding of a fluorescent drug to a biological tissue. Although our application is specific to adrenergic receptors, the general method could be applied to any volumetric, fluorescence-image-based assay.

Variance of a potential of mean force obtained using the weighted histogram analysis method.

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Cukier, Robert I

2013-11-27

A potential of mean force (PMF) that provides the free energy of a thermally driven system along some chosen reaction coordinate (RC) is a useful descriptor of systems characterized by complex, high dimensional potential energy surfaces. Umbrella sampling window simulations use potential energy restraints to provide more uniform sampling along a RC so that potential energy barriers that would otherwise make equilibrium sampling computationally difficult can be overcome. Combining the results from the different biased window trajectories can be accomplished using the Weighted Histogram Analysis Method (WHAM). Here, we provide an analysis of the variance of a PMF along the reaction coordinate. We assume that the potential restraints used for each window lead to Gaussian distributions for the window reaction coordinate densities and that the data sampling in each window is from an equilibrium ensemble sampled so that successive points are statistically independent. Also, we assume that neighbor window densities overlap, as required in WHAM, and that further-than-neighbor window density overlap is negligible. Then, an analytic expression for the variance of the PMF along the reaction coordinate at a desired level of spatial resolution can be generated. The variance separates into a sum over all windows with two kinds of contributions: One from the variance of the biased window density normalized by the total biased window density and the other from the variance of the local (for each window's coordinate range) PMF. Based on the desired spatial resolution of the PMF, the former variance can be minimized relative to that from the latter. The method is applied to a model system that has features of a complex energy landscape evocative of a protein with two conformational states separated by a free energy barrier along a collective reaction coordinate. The variance can be constructed from data that is already available from the WHAM PMF construction.

Absolute and relative dose-surface and dose-volume histograms of the bladder: which one is the most representative for the actual treatment?

International Nuclear Information System (INIS)

Hoogeman, Mischa S; Peeters, Stephanie T H; Bois, Josien de; Lebesque, Joos V

2005-01-01

The purpose of this study was to quantify to what extent relative and absolute bladder dose-volume and dose-surface histograms of the planning CT scan were representative for the actual treatment. We used data of 17 patients, who each received 11 repeat CT scans and a planning CT scan. The repeat CT scans were matched on the planning CT scan by the bony anatomy. Clinical treatment plans were used to evaluate the impact of bladder filling changes on the four histogram types. The impact was quantified by calculating for this patient group the correlation coefficient between the planning histogram and the treatment histogram. We found that the absolute dose-surface histogram was the most representative one for the actual treatment

Independent histogram pursuit for segmentation of skin lesions

DEFF Research Database (Denmark)

Gomez, D.D.; Butakoff, C.; Ersbøll, Bjarne Kjær

2008-01-01

In this paper, an unsupervised algorithm, called the Independent Histogram Pursuit (HIP), for segmenting dermatological lesions is proposed. The algorithm estimates a set of linear combinations of image bands that enhance different structures embedded in the image. In particular, the first estima...... to deal with different types of dermatological lesions. The boundary detection precision using k-means segmentation was close to 97%. The proposed algorithm can be easily combined with the majority of classification algorithms....

Face Recognition Performance Improvement using a Similarity Score of Feature Vectors based on Probabilistic Histograms

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SRIKOTE, G.

2016-08-01

Full Text Available This paper proposes an improved performance algorithm of face recognition to identify two face mismatch pairs in cases of incorrect decisions. The primary feature of this method is to deploy the similarity score with respect to Gaussian components between two previously unseen faces. Unlike the conventional classical vector distance measurement, our algorithms also consider the plot of summation of the similarity index versus face feature vector distance. A mixture of Gaussian models of labeled faces is also widely applicable to different biometric system parameters. By comparative evaluations, it has been shown that the efficiency of the proposed algorithm is superior to that of the conventional algorithm by an average accuracy of up to 1.15% and 16.87% when compared with 3x3 Multi-Region Histogram (MRH direct-bag-of-features and Principal Component Analysis (PCA-based face recognition systems, respectively. The experimental results show that similarity score consideration is more discriminative for face recognition compared to feature distance. Experimental results of Labeled Face in the Wild (LFW data set demonstrate that our algorithms are suitable for real applications probe-to-gallery identification of face recognition systems. Moreover, this proposed method can also be applied to other recognition systems and therefore additionally improves recognition scores.

Introducing the Jacobian-volume-histogram of deforming organs: application to parotid shrinkage evaluation

International Nuclear Information System (INIS)

Fiorino, Claudio; Maggiulli, Eleonora; Broggi, Sara; Cattaneo, Giovanni Mauro; Calandrino, Riccardo; Liberini, Simone; Faggiano, Elena; Rizzo, Giovanna; Dell'Oca, Italo; Di Muzio, Nadia

2011-01-01

The Jacobian of the deformation field of elastic registration between images taken during radiotherapy is a measure of inter-fraction local deformation. The histogram of the Jacobian values (Jac) within an organ was introduced (JVH-Jacobian-volume-histogram) and first applied in quantifying parotid shrinkage. MVCTs of 32 patients previously treated with helical tomotherapy for head-neck cancers were collected. Parotid deformation was evaluated through elastic registration between MVCTs taken at the first and last fractions. Jac was calculated for each voxel of all parotids, and integral JVHs were calculated for each parotid; the correlation between the JVH and the planning dose-volume histogram (DVH) was investigated. On average, 82% (±17%) of the voxels shrinks (Jac 50% (Jac < 0.5). The best correlation between the DVH and the JVH was found between V10 and V15, and Jac < 0.4-0.6 (p < 0.01). The best constraint predicting a higher number of largely compressing voxels (Jac0.5<7.5%, median value) was V15 ≥ 75% (OR: 7.6, p = 0.002). Jac and the JVH are promising tools for scoring/modelling toxicity and for evaluating organ/contour variations with potential applications in adaptive radiotherapy.

Correlation between surrogates of bladder dosimetry and dose–volume histograms of the bladder wall defined on MRI in prostate cancer radiotherapy

International Nuclear Information System (INIS)

Carillo, Viviana; Cozzarini, Cesare; Chietera, Andreina; Perna, Lucia; Gianolini, Stefano; Maggio, Angelo; Botti, Andrea; Rancati, Tiziana; Valdagni, Riccardo; Fiorino, Claudio

2012-01-01

The correlation between bladder dose–wall-histogram (DWH) and dose–volume-histogram (DVH), dose–surface-histogram (DSH), and DVH-5/10 was investigated in a group of 28 patients; bladder walls were drawn on T2-MRI. DVH showed the poorest correlation with DWH; DSH or DVH-5/10 should be preferred in planning; absolute DVH may be used for radical patients, although less robust.

SU-G-BRC-08: Evaluation of Dose Mass Histogram as a More Representative Dose Description Method Than Dose Volume Histogram in Lung Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Liu, J; Eldib, A; Ma, C [Fox Chase Cancer Center, Philadelphia, PA (United States); Lin, M [The University of Texas Southwestern Medical Ctr, Dallas, TX (United States); Li, J [Cyber Medical Inc, Xian, Shaanxi (China); Mora, G [Universidade de Lisboa, Codex, Lisboa (Portugal)

2016-06-15

Purpose: Dose-volume-histogram (DVH) is widely used for plan evaluation in radiation treatment. The concept of dose-mass-histogram (DMH) is expected to provide a more representative description as it accounts for heterogeneity in tissue density. This study is intended to assess the difference between DVH and DMH for evaluating treatment planning quality. Methods: 12 lung cancer treatment plans were exported from the treatment planning system. DVHs for the planning target volume (PTV), the normal lung and other structures of interest were calculated. DMHs were calculated in a similar way as DVHs expect that the voxel density converted from the CT number was used in tallying the dose histogram bins. The equivalent uniform dose (EUD) was calculated based on voxel volume and mass, respectively. The normal tissue complication probability (NTCP) in relation to the EUD was calculated for the normal lung to provide quantitative comparison of DVHs and DMHs for evaluating the radiobiological effect. Results: Large differences were observed between DVHs and DMHs for lungs and PTVs. For PTVs with dense tumor cores, DMHs are higher than DVHs due to larger mass weighing in the high dose conformal core regions. For the normal lungs, DMHs can either be higher or lower than DVHs depending on the target location within the lung. When the target is close to the lower lung, DMHs show higher values than DVHs because the lower lung has higher density than the central portion or the upper lung. DMHs are lower than DVHs for targets in the upper lung. The calculated NTCPs showed a large range of difference between DVHs and DMHs. Conclusion: The heterogeneity of lung can be well considered using DMH for evaluating target coverage and normal lung pneumonitis. Further studies are warranted to quantify the benefits of DMH over DVH for plan quality evaluation.

Multipeak Mean Based Optimized Histogram Modification Framework Using Swarm Intelligence for Image Contrast Enhancement

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P. Babu

2015-01-01

Full Text Available A novel approach, Multipeak mean based optimized histogram modification framework (MMOHM is introduced for the purpose of enhancing the contrast as well as preserving essential details for any given gray scale and colour images. The basic idea of this technique is the calculation of multiple peaks (local maxima from the original histogram. The mean value of multiple peaks is computed and the input image’s histogram is segmented into two subhistograms based on this multipeak mean (mmean value. Then, a bicriteria optimization problem is formulated and the subhistograms are modified by selecting optimal contrast enhancement parameters. While formulating the enhancement parameters, particle swarm optimization is employed to find optimal values of them. Finally, the union of the modified subhistograms produces a contrast enhanced and details preserved output image. This mechanism enhances the contrast of the input image better than the existing contemporary HE methods. The performance of the proposed method is well supported by the contrast enhancement quantitative metrics such as discrete entropy, natural image quality evaluator, and absolute mean brightness error.

CHOBS: Color Histogram of Block Statistics for Automatic Bleeding Detection in Wireless Capsule Endoscopy Video.

Science.gov (United States)

Ghosh, Tonmoy; Fattah, Shaikh Anowarul; Wahid, Khan A

2018-01-01

Wireless capsule endoscopy (WCE) is the most advanced technology to visualize whole gastrointestinal (GI) tract in a non-invasive way. But the major disadvantage here, it takes long reviewing time, which is very laborious as continuous manual intervention is necessary. In order to reduce the burden of the clinician, in this paper, an automatic bleeding detection method for WCE video is proposed based on the color histogram of block statistics, namely CHOBS. A single pixel in WCE image may be distorted due to the capsule motion in the GI tract. Instead of considering individual pixel values, a block surrounding to that individual pixel is chosen for extracting local statistical features. By combining local block features of three different color planes of RGB color space, an index value is defined. A color histogram, which is extracted from those index values, provides distinguishable color texture feature. A feature reduction technique utilizing color histogram pattern and principal component analysis is proposed, which can drastically reduce the feature dimension. For bleeding zone detection, blocks are classified using extracted local features that do not incorporate any computational burden for feature extraction. From extensive experimentation on several WCE videos and 2300 images, which are collected from a publicly available database, a very satisfactory bleeding frame and zone detection performance is achieved in comparison to that obtained by some of the existing methods. In the case of bleeding frame detection, the accuracy, sensitivity, and specificity obtained from proposed method are 97.85%, 99.47%, and 99.15%, respectively, and in the case of bleeding zone detection, 95.75% of precision is achieved. The proposed method offers not only low feature dimension but also highly satisfactory bleeding detection performance, which even can effectively detect bleeding frame and zone in a continuous WCE video data.

Assessment of Autonomic Function by Phase Rectification of RRInterval Histogram Analysis in Chagas Disease

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Olivassé Nasari Junior

2015-06-01

Full Text Available Background: In chronic Chagas disease (ChD, impairment of cardiac autonomic function bears prognostic implications. Phase‑rectification of RR-interval series isolates the sympathetic, acceleration phase (AC and parasympathetic, deceleration phase (DC influences on cardiac autonomic modulation. Objective: This study investigated heart rate variability (HRV as a function of RR-interval to assess autonomic function in healthy and ChD subjects. Methods: Control (n = 20 and ChD (n = 20 groups were studied. All underwent 60-min head-up tilt table test under ECG recording. Histogram of RR-interval series was calculated, with 100 ms class, ranging from 600–1100 ms. In each class, mean RR-intervals (MNN and root-mean-squared difference (RMSNN of consecutive normal RR-intervals that suited a particular class were calculated. Average of all RMSNN values in each class was analyzed as function of MNN, in the whole series (RMSNNT, and in AC (RMSNNAC and DC (RMSNNDC phases. Slopes of linear regression lines were compared between groups using Student t-test. Correlation coefficients were tested before comparisons. RMSNN was log-transformed. (α < 0.05. Results: Correlation coefficient was significant in all regressions (p < 0.05. In the control group, RMSNNT, RMSNNAC, and RMSNNDC significantly increased linearly with MNN (p < 0.05. In ChD, only RMSNNAC showed significant increase as a function of MNN, whereas RMSNNT and RMSNNDC did not. Conclusion: HRV increases in proportion with the RR-interval in healthy subjects. This behavior is lost in ChD, particularly in the DC phase, indicating cardiac vagal incompetence.

Outcomes of visual acuity in carbon ion radiotherapy: Analysis of dose-volume histograms and prognostic factors

International Nuclear Information System (INIS)

Hasegawa, Azusa; Mizoe, Jun-etsu; Mizota, Atsushi; Tsujii, Hirohiko

2006-01-01

Purpose: To analyze the tolerance dose for retention of visual acuity in patients with head-and-neck tumors treated with carbon ion radiotherapy. Methods and Materials: From June 1994 to March 2000, 163 patients with tumors in the head and neck or skull base region were treated with carbon ion radiotherapy. Analysis was performed on 54 optic nerves (ONs) corresponding to 30 patients whose ONs had been included in the irradiated volume. These patients showed no evidence of visual impairment due to other factors and had a follow-up period of >4 years. All patients had been informed of the possibility of visual impairment before treatment. We evaluated the dose-complication probability and the prognostic factors for the retention of visual acuity in carbon ion radiotherapy, using dose-volume histograms and multivariate analysis. Results: The median age of 30 patients (14 men, 16 women) was 57.2 years. Median prescribed total dose was 56.0 gray equivalents (GyE) at 3.0-4.0 GyE per fraction per day (range, 48-64 GyE; 16-18 fractions; 4-6 weeks). Of 54 ONs that were analyzed, 35 had been irradiated with max ]) resulting in no visual loss. Conversely, 11 of the 19 ONs (58%) irradiated with >57 GyE (D max ) suffered a decrease of visual acuity. In all of these cases, the ONs had been involved in the tumor before carbon ion radiotherapy. In the multivariate analysis, a dose of 20% of the volume of the ON (D 2 ) was significantly associated with visual loss. Conclusions: The occurrence of visual loss seems to be correlated with a delivery of >60 GyE to 20% of the volume of the ON

Adaptive local backlight dimming algorithm based on local histogram and image characteristics

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Burini, Nino; Korhonen, Jari

2013-01-01

-off between power consumption and image quality preservation than the other algorithms representing the state of the art among feature based backlight algorithms. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.......Liquid Crystal Display (LCDs) with Light Emitting Diode (LED) backlight is a very popular display technology, used for instance in television sets, monitors and mobile phones. This paper presents a new backlight dimming algorithm that exploits the characteristics of the target image......, such as the local histograms and the average pixel intensity of each backlight segment, to reduce the power consumption of the backlight and enhance image quality. The local histogram of the pixels within each backlight segment is calculated and, based on this average, an adaptive quantile value is extracted...

Evaluation of dose-volume histograms after prostate seed implantation. 4-year experience

International Nuclear Information System (INIS)

Hoinkis, C.; Lehmann, D.; Winkler, C.; Herrmann, T.; Hakenberg, O.W.; Wirth, M.P.

2004-01-01

Background and purpose: permanent interstitial brachytherapy by seed implantation is a treatment alternative for low-volume low-risk prostate cancer and a complex interdisciplinary treatment with a learning curve. Dose-volume histograms are used to assess postimplant quality. The authors evaluated their learning curve based on dose-volume histograms and analyzed factors influencing implantation quality. Patients and methods: since 1999, 38 patients with a minimum follow-up of 6 months were treated at the authors' institution with seed implantation using palladium-103 or iodine-125, initially using the preplan method and later real-time planning. Postimplant CT was performed after 4 weeks. The dose-volume indices D90, V100, V150, the D max of pre- and postplans, and the size and position of the volume receiving the prescribed dose (high-dose volume) of the postplans were evaluated. In six patients, postplan imaging both by CT and MRI was used and prostate volumes were compared with preimplant transrectal ultrasound volumes. The first five patients were treated under external supervision. Results: patients were divided into three consecutive groups for analysis of the learning curve (group 1: n = 5 patients treated under external supervision; group 2: n = 13 patients; group 3: n = 20 patients). D90 post for the three groups were 79.3%, 74.2%, and 99.9%, the V100 post were 78.6%, 73.5%, and 88.2%, respectively. The relationship between high-dose volume and prostate volume showed a similar increase as the D90, while the relationship between high-dose volume lying outside the prostate and prostate volume remained constant. The ratio between prostate volumes from transrectal ultrasound and CT imaging decreased with increasing D90 post , while the preplanning D90 and V100 remained constant. The different isotopes used, the method of planning, and the implanted activity per prostate volume did not influence results. Conclusion: a learning curve characterized by an increase

Optimization of radiation therapy, III: a method of assessing complication probabilities from dose-volume histograms

International Nuclear Information System (INIS)

Lyman, J.T.; Wolbarst, A.B.

1987-01-01

To predict the likelihood of success of a therapeutic strategy, one must be able to assess the effects of the treatment upon both diseased and healthy tissues. This paper proposes a method for determining the probability that a healthy organ that receives a non-uniform distribution of X-irradiation, heat, chemotherapy, or other agent will escape complications. Starting with any given dose distribution, a dose-cumulative-volume histogram for the organ is generated. This is then reduced by an interpolation scheme (involving the volume-weighting of complication probabilities) to a slightly different histogram that corresponds to the same overall likelihood of complications, but which contains one less step. The procedure is repeated, one step at a time, until there remains a final, single-step histogram, for which the complication probability can be determined. The formalism makes use of a complication response function C(D, V) which, for the given treatment schedule, represents the probability of complications arising when the fraction V of the organ receives dose D and the rest of the organ gets none. Although the data required to generate this function are sparse at present, it should be possible to obtain the necessary information from in vivo and clinical studies. Volume effects are taken explicitly into account in two ways: the precise shape of the patient's histogram is employed in the calculation, and the complication response function is a function of the volume

SU-F-R-50: Radiation-Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer

International Nuclear Information System (INIS)

Chen, X; Schott, D; Song, Y; Li, D; Hall, W; Erickson, B; Li, X

2016-01-01

Purpose: In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogram including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two-tailed t-test and the correlations were analyzed using Spearman rank correlation tests. Results: In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response. Conclusion: Significant changes in HU histogram and the histogram-based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.

SU-F-R-50: Radiation-Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer

Energy Technology Data Exchange (ETDEWEB)

Chen, X; Schott, D; Song, Y; Li, D; Hall, W; Erickson, B; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

2016-06-15

Purpose: In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Diagnostic-quality CT data acquired daily during routine CT-guided CRT using a CT-on-rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogram including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two-tailed t-test and the correlations were analyzed using Spearman rank correlation tests. Results: In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response. Conclusion: Significant changes in HU histogram and the histogram-based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.

[Characteristics of high resolution diffusion weighted imaging apparent diffusion coefficient histogram and its correlations with cancer stages in patients with nasopharyngeal carcinoma].

Science.gov (United States)

Wang, G J; Wang, Y; Ye, Y; Chen, F; Lu, Y T; Li, S L

2017-11-07

Objective: To investigate the features of apparent diffusion coefficient (ADC) histogram parameters based on entire tumor volume data in high resolution diffusion weighted imaging of nasopharyngeal carcinoma (NPC) and to evaluate its correlations with cancer stages. Methods: This retrospective study included 154 cases of NPC patients[102 males and 52 females, mean age (48±11) years]who had received readout segmentation of long variable echo trains of MRI scan before radiation therapy. The area of tumor was delineated on each section of axial ADC maps to generate ADC histogram by using Image J. ADC histogram of entire tumor along with the histogram parameters-the tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness and kurtosis were obtained by merging all sections with SPSS 22.0 software. Intra-observer repeatability was assessed by using intra-class correlation coefficients (ICC). The patients were subdivided into two groups according to cancer volume: small cancer group (histogram parameters and cancer stages was evaluated with Spearman test. Results: The ICC of measuring ADC histogram parameters of tumor voxels, ADC(mean), ADC(25%), ADC(50%), ADC(75%), skewness, kurtosis was 0.938, 0.861, 0.885, 0.838, 0.836, 0.358 and 0.456, respectively. The tumor voxels was positively correlated with T staging ( r =0.368, P histogram (ADC(mean), ADC(25%), ADC(50%)) increases with T staging in NPC smaller than 2 cm(3).

Condition monitoring of face milling tool using K-star algorithm and histogram features of vibration signal

Directory of Open Access Journals (Sweden)

C.K. Madhusudana

2016-09-01

Full Text Available This paper deals with the fault diagnosis of the face milling tool based on machine learning approach using histogram features and K-star algorithm technique. Vibration signals of the milling tool under healthy and different fault conditions are acquired during machining of steel alloy 42CrMo4. Histogram features are extracted from the acquired signals. The decision tree is used to select the salient features out of all the extracted features and these selected features are used as an input to the classifier. K-star algorithm is used as a classifier and the output of the model is utilised to study and classify the different conditions of the face milling tool. Based on the experimental results, K-star algorithm is provided a better classification accuracy in the range from 94% to 96% with histogram features and is acceptable for fault diagnosis.

Expression robust 3D face recognition via mesh-based histograms of multiple order surface differential quantities

KAUST Repository

Li, Huibin

2011-09-01

This paper presents a mesh-based approach for 3D face recognition using a novel local shape descriptor and a SIFT-like matching process. Both maximum and minimum curvatures estimated in the 3D Gaussian scale space are employed to detect salient points. To comprehensively characterize 3D facial surfaces and their variations, we calculate weighted statistical distributions of multiple order surface differential quantities, including histogram of mesh gradient (HoG), histogram of shape index (HoS) and histogram of gradient of shape index (HoGS) within a local neighborhood of each salient point. The subsequent matching step then robustly associates corresponding points of two facial surfaces, leading to much more matched points between different scans of a same person than the ones of different persons. Experimental results on the Bosphorus dataset highlight the effectiveness of the proposed method and its robustness to facial expression variations. © 2011 IEEE.

Influence of Sampling Practices on the Appearance of DNA Image Histograms of Prostate Cells in FNAB Samples

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Abdelbaset Buhmeida

1999-01-01

Full Text Available Twenty‐one fine needle aspiration biopsies (FNAB of the prostate, diagnostically classified as definitely malignant, were studied. The Papanicolaou or H&E stained samples were destained and then stained for DNA with the Feulgen reaction. DNA cytometry was applied after different sampling rules. The histograms varied according to the sampling rule applied. Because free cells between cell groups were easier to measure than cells in the cell groups, two sampling rules were tested in all samples: (i cells in the cell groups were measured, and (ii free cells between cell groups were measured. Abnormal histograms were more common after the sampling rule based on free cells, suggesting that abnormal patterns are best revealed through the free cells in these samples. The conclusions were independent of the applied histogram interpretation method.

Diagnostic accuracy of ultrasonic histogram features to evaluate radiation toxicity of the parotid glands: a clinical study of xerostomia following head-and-neck cancer radiotherapy.

Science.gov (United States)

Yang, Xiaofeng; Tridandapani, Srini; Beitler, Jonathan J; Yu, David S; Chen, Zhengjia; Kim, Sungjin; Bruner, Deborah W; Curran, Walter J; Liu, Tian

2014-10-01

To investigate the diagnostic accuracy of ultrasound histogram features in the quantitative assessment of radiation-induced parotid gland injury and to identify potential imaging biomarkers for radiation-induced xerostomia (dry mouth)-the most common and debilitating side effect after head-and-neck radiotherapy (RT). Thirty-four patients, who have developed xerostomia after RT for head-and-neck cancer, were enrolled. Radiation-induced xerostomia was defined by the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer morbidity scale. Ultrasound scans were performed on each patient's parotids bilaterally. The 34 patients were stratified into the acute-toxicity groups (16 patients, ≤ 3 months after treatment) and the late-toxicity group (18 patients, > 3 months after treatment). A separate control group of 13 healthy volunteers underwent similar ultrasound scans of their parotid glands. Six sonographic features were derived from the echo-intensity histograms to assess acute and late toxicity of the parotid glands. The quantitative assessments were compared to a radiologist's clinical evaluations. The diagnostic accuracy of these ultrasonic histogram features was evaluated with the receiver operating characteristic (ROC) curve. With an area under the ROC curve greater than 0.90, several histogram features demonstrated excellent diagnostic accuracy for evaluation of acute and late toxicity of parotid glands. Significant differences (P xerostomia monitoring and assessment. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Optimized broad-histogram simulations for strong first-order phase transitions: droplet transitions in the large-Q Potts model

International Nuclear Information System (INIS)

Bauer, Bela; Troyer, Matthias; Gull, Emanuel; Trebst, Simon; Huse, David A

2010-01-01

The numerical simulation of strongly first-order phase transitions has remained a notoriously difficult problem even for classical systems due to the exponentially suppressed (thermal) equilibration in the vicinity of such a transition. In the absence of efficient update techniques, a common approach for improving equilibration in Monte Carlo simulations is broadening the sampled statistical ensemble beyond the bimodal distribution of the canonical ensemble. Here we show how a recently developed feedback algorithm can systematically optimize such broad-histogram ensembles and significantly speed up equilibration in comparison with other extended ensemble techniques such as flat-histogram, multicanonical and Wang–Landau sampling. We simulate, as a prototypical example of a strong first-order transition, the two-dimensional Potts model with up to Q = 250 different states in large systems. The optimized histogram develops a distinct multi-peak structure, thereby resolving entropic barriers and their associated phase transitions in the phase coexistence region—such as droplet nucleation and annihilation, and droplet–strip transitions for systems with periodic boundary conditions. We characterize the efficiency of the optimized histogram sampling by measuring round-trip times τ(N, Q) across the phase transition for samples comprised of N spins. While we find power-law scaling of τ versus N for small Q∼ 2 , we observe a crossover to exponential scaling for larger Q. These results demonstrate that despite the ensemble optimization, broad-histogram simulations cannot fully eliminate the supercritical slowing down at strongly first-order transitions

Optimized broad-histogram simulations for strong first-order phase transitions: droplet transitions in the large-Q Potts model

Science.gov (United States)

Bauer, Bela; Gull, Emanuel; Trebst, Simon; Troyer, Matthias; Huse, David A.

2010-01-01

The numerical simulation of strongly first-order phase transitions has remained a notoriously difficult problem even for classical systems due to the exponentially suppressed (thermal) equilibration in the vicinity of such a transition. In the absence of efficient update techniques, a common approach for improving equilibration in Monte Carlo simulations is broadening the sampled statistical ensemble beyond the bimodal distribution of the canonical ensemble. Here we show how a recently developed feedback algorithm can systematically optimize such broad-histogram ensembles and significantly speed up equilibration in comparison with other extended ensemble techniques such as flat-histogram, multicanonical and Wang-Landau sampling. We simulate, as a prototypical example of a strong first-order transition, the two-dimensional Potts model with up to Q = 250 different states in large systems. The optimized histogram develops a distinct multi-peak structure, thereby resolving entropic barriers and their associated phase transitions in the phase coexistence region—such as droplet nucleation and annihilation, and droplet-strip transitions for systems with periodic boundary conditions. We characterize the efficiency of the optimized histogram sampling by measuring round-trip times τ(N, Q) across the phase transition for samples comprised of N spins. While we find power-law scaling of τ versus N for small Q \\lesssim 50 and N \\lesssim 40^2 , we observe a crossover to exponential scaling for larger Q. These results demonstrate that despite the ensemble optimization, broad-histogram simulations cannot fully eliminate the supercritical slowing down at strongly first-order transitions.

Algorithms for adaptive histogram equalization

International Nuclear Information System (INIS)

Pizer, S.M.; Austin, J.D.; Cromartie, R.; Geselowitz, A.; Ter Haar Romeny, B.; Zimmerman, J.B.; Zuiderveld, K.

1986-01-01

Adaptive histogram equalization (ahe) is a contrast enhancement method designed to be broadly applicable and having demonstrated effectiveness [Zimmerman, 1985]. However, slow speed and the overenhancement of noise it produces in relatively homogeneous regions are two problems. The authors summarize algorithms designed to overcome these and other concerns. These algorithms include interpolated ahe, to speed up the method on general purpose computers; a version of interpolated ahe designed to run in a few seconds on feedback processors; a version of full ahe designed to run in under one second on custom VLSI hardware; and clipped ahe, designed to overcome the problem of overenhancement of noise contrast. The authors conclude that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clipped ahe can be made adequately fast to be routinely applied in the normal display sequence

Dynamic contrast-enhanced MR imaging of the rectum: Correlations between single-section and whole-tumor histogram analyses.

Science.gov (United States)

Choi, M H; Oh, S N; Park, G E; Yeo, D-M; Jung, S E

2018-05-10

To evaluate the interobserver and intermethod correlations of histogram metrics of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters acquired by multiple readers using the single-section and whole-tumor volume methods. Four DCE parameters (K trans , K ep , V e , V p ) were evaluated in 45 patients (31 men and 14 women; mean age, 61±11 years [range, 29-83 years]) with locally advanced rectal cancer using pre-chemoradiotherapy (CRT) MRI. Ten histogram metrics were extracted using two methods of lesion selection performed by three radiologists: the whole-tumor volume method for the whole tumor on axial section-by-section images and the single-section method for the entire area of the tumor on one axial image. The interobserver and intermethod correlations were evaluated using the intraclass correlation coefficients (ICCs). The ICCs showed excellent interobserver and intermethod correlations in most of histogram metrics of the DCE parameters. The ICCs among the three readers were > 0.7 (Phistogram metrics, except for the minimum and maximum. The intermethod correlations for most of the histogram metrics were excellent for each radiologist, regardless of the differences in the radiologists' experience. The interobserver and intermethod correlations for most of the histogram metrics of the DCE parameters are excellent in rectal cancer. Therefore, the single-section method may be a potential alternative to the whole-tumor volume method using pre-CRT MRI, despite the fact that the high agreement between the two methods cannot be extrapolated to post-CRT MRI. Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram

Directory of Open Access Journals (Sweden)

Lei Zhao

2017-01-01

Full Text Available This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better.

Digital image classification with the help of artificial neural network by simple histogram.

Science.gov (United States)

Dey, Pranab; Banerjee, Nirmalya; Kaur, Rajwant

2016-01-01

Visual image classification is a great challenge to the cytopathologist in routine day-to-day work. Artificial neural network (ANN) may be helpful in this matter. In this study, we have tried to classify digital images of malignant and benign cells in effusion cytology smear with the help of simple histogram data and ANN. A total of 404 digital images consisting of 168 benign cells and 236 malignant cells were selected for this study. The simple histogram data was extracted from these digital images and an ANN was constructed with the help of Neurointelligence software [Alyuda Neurointelligence 2.2 (577), Cupertino, California, USA]. The network architecture was 6-3-1. The images were classified as training set (281), validation set (63), and test set (60). The on-line backpropagation training algorithm was used for this study. A total of 10,000 iterations were done to train the ANN system with the speed of 609.81/s. After the adequate training of this ANN model, the system was able to identify all 34 malignant cell images and 24 out of 26 benign cells. The ANN model can be used for the identification of the individual malignant cells with the help of simple histogram data. This study will be helpful in the future to identify malignant cells in unknown situations.

Image analysis of microsialograms of the mouse parotid gland using digital image processing

International Nuclear Information System (INIS)

Yoshiura, K.; Ohki, M.; Yamada, N.

1991-01-01

The authors compared two digital-image feature-extraction methods for the analysis of microsialograms of the mouse parotid gland following either overfilling, experimentally induced acute sialoadenitis or irradiation. Microsialograms were digitized using a drum-scanning microdensitometer. The grey levels were then partitioned into four bands representing soft tissue, peripheral minor, middle-sized and major ducts, and run-length and histogram analysis of the digital images performed. Serial analysis of microsialograms during progressive filling showed that both methods depicted the structural characteristics of the ducts at each grey level. However, in the experimental groups, run-length analysis showed slight changes in the peripheral duct system more clearly. This method was therefore considered more effective than histogram analysis

3D facial expression recognition based on histograms of surface differential quantities

KAUST Repository

Li, Huibin

2011-01-01

3D face models accurately capture facial surfaces, making it possible for precise description of facial activities. In this paper, we present a novel mesh-based method for 3D facial expression recognition using two local shape descriptors. To characterize shape information of the local neighborhood of facial landmarks, we calculate the weighted statistical distributions of surface differential quantities, including histogram of mesh gradient (HoG) and histogram of shape index (HoS). Normal cycle theory based curvature estimation method is employed on 3D face models along with the common cubic fitting curvature estimation method for the purpose of comparison. Based on the basic fact that different expressions involve different local shape deformations, the SVM classifier with both linear and RBF kernels outperforms the state of the art results on the subset of the BU-3DFE database with the same experimental setting. © 2011 Springer-Verlag.

A histogram memory plug-in board for IBM-PC based nuclear pulse height analysis applications

International Nuclear Information System (INIS)

Behere, Anita; Ghodgaonkar, M.D.

1989-01-01

The histogram memory PC plug-in board has 8K x 24 dual ported memory with access from PC as well as from on board data acquisition logic. The arbitration control logic monitors the memory access requests from both the sources and honours them on first come first served basis. The data acquisition logic takes only 840 ns. to perform Read-Modify-Write memory operation. The data acquisition logic incorporates ADC interface logic for connecting to a NIM ADC which is normally housed in a NIM system along with other required front-end processing modules. Two interval timers are provided on the board. One of them provides Live Time/Clock Time counting and the other generates a 200 ms interrupt which is used for live spectrum display. The board is fully supported with system and data processing software developed in Turbo Pascal. (author)

TOP-DRAWER, Histograms, Scatterplots, Curve-Smoothing

International Nuclear Information System (INIS)

Chaffee, R.B.

1988-01-01

Description of program or function: TOP DRAWER produces histograms, scatterplots, data points with error bars and plots symbols, and curves passing through data points, with elaborate titles. It also does smoothing and calculates frequency distributions. There is little facility, however, for arithmetic manipulation. Because of its restricted applicability, TOP DRAWER can be controlled by a relatively simple set of commands, and this control is further simplified by the choice of reasonable default values for all parameters. Despite this emphasis on simplicity, TOP DRAWER plots are of exceptional quality and are suitable for publication. Input is normally from card-image records, although a set of subroutines is provided to accommodate FORTRAN calls. The program contains switches which can be set to generate code suitable for execution on IBM, DECX VAX, and PRIME computers

The analysis of the wind potential in selected locations in the southeastern Poland

Directory of Open Access Journals (Sweden)

Sornek Krzysztof

2017-01-01

Full Text Available This paper shows the results of analysis of the wind potential in selected locations in the southern Poland (placed in the Małopolskie, Świętokrzyskie and Podkarpackie Voivodships. The measurements and analysis of the wind resources in potential locations of the wind turbines are important part of the investment process. The statistical analysis involves the creation of histograms (e.g. histogram of the wind speed and direction and fitting those histograms to theoretical distributions (e.g. Weilbull distributions of wind speed. Such analysis has been described and conducted using measurement data for four selected locations. Basis on the conducted analysis, the economy efficiency and environmental impact of wind turbine operation has been estimated. Three market available wind turbines have been included to calculate NPV, IRR and SPBT indicators. Then, the avoided emissions of CO2, NOx, SO2 and dust have been calculated. There were also conducted some calculation using TRNSYS simulation software. The results of simulations have been compared with measurement data and the level of convergence have been found.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

Science.gov (United States)

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Robust Face Recognition by Computing Distances from Multiple Histograms of Oriented Gradients

NARCIS (Netherlands)

Karaaba, Mahir; Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

2015-01-01

The Single Sample per Person Problem is a challenging problem for face recognition algorithms. Patch-based methods have obtained some promising results for this problem. In this paper, we propose a new face recognition algorithm that is based on a combination of different histograms of oriented

Conductance of single-atom platinum contacts: Voltage dependence of the conductance histogram

DEFF Research Database (Denmark)

Nielsen, S.K.; Noat, Y.; Brandbyge, Mads

2003-01-01

The conductance of a single-atom contact is sensitive to the coupling of this contact atom to the atoms in the leads. Notably for the transition metals this gives rise to a considerable spread in the observed conductance values. The mean conductance value and spread can be obtained from the first...... peak in conductance histograms recorded from a large set of contact-breaking cycles. In contrast to the monovalent metals, this mean value for Pt depends strongly on the applied voltage bias and other experimental conditions and values ranging from about 1 G(0) to 2.5 G(0) (G(0)=2e(2)/h) have been...... reported. We find that at low bias the first peak in the conductance histogram is centered around 1.5 G(0). However, as the bias increases past 300 mV the peak shifts to 1.8 G(0). Here we show that this bias dependence is due to a geometric effect where monatomic chains are replaced by single-atom contacts...

A novel method for the evaluation of uncertainty in dose-volume histogram computation.

Science.gov (United States)

Henríquez, Francisco Cutanda; Castrillón, Silvia Vargas

2008-03-15

Dose-volume histograms (DVHs) are a useful tool in state-of-the-art radiotherapy treatment planning, and it is essential to recognize their limitations. Even after a specific dose-calculation model is optimized, dose distributions computed by using treatment-planning systems are affected by several sources of uncertainty, such as algorithm limitations, measurement uncertainty in the data used to model the beam, and residual differences between measured and computed dose. This report presents a novel method to take them into account. To take into account the effect of associated uncertainties, a probabilistic approach using a new kind of histogram, a dose-expected volume histogram, is introduced. The expected value of the volume in the region of interest receiving an absorbed dose equal to or greater than a certain value is found by using the probability distribution of the dose at each point. A rectangular probability distribution is assumed for this point dose, and a formulation that accounts for uncertainties associated with point dose is presented for practical computations. This method is applied to a set of DVHs for different regions of interest, including 6 brain patients, 8 lung patients, 8 pelvis patients, and 6 prostate patients planned for intensity-modulated radiation therapy. Results show a greater effect on planning target volume coverage than in organs at risk. In cases of steep DVH gradients, such as planning target volumes, this new method shows the largest differences with the corresponding DVH; thus, the effect of the uncertainty is larger.

High capacity, high speed histogramming data acquisition memory

International Nuclear Information System (INIS)

Epstein, A.; Boulin, C.

1996-01-01

A double width CAMAC DRAM store module was developed for use as a histogramming memory in fast time-resolved synchrotron radiation applications to molecular biology. High speed direct memory modify (3 MHz) is accomplished by using a discrete DRAM controller and fast page mode access. The module can be configured using standard SIMMs to sizes of up to 64M-words. The word width is 16 bit and the module can handle overflows by storing the overflow addresses in a dedicated FIFO. Simultaneous front panel DMM/DMI access and CAMAC readout of the overflow addresses is supported

Contrast Enhancement Using Brightness Preserving Histogram Equalization Technique for Classification of Date Varieties

Directory of Open Access Journals (Sweden)

G Thomas

2014-06-01

Full Text Available Computer vision technique is becoming popular for quality assessment of many products in food industries. Image enhancement is the first step in analyzing the images in order to obtain detailed information for the determination of quality. In this study, Brightness preserving histogram equalization technique was used to enhance the features of gray scale images to classify three date varieties (Khalas, Fard and Madina. Mean, entropy, kurtosis and skewness features were extracted from the original and enhanced images. Mean and entropy from original images and kurtosis from the enhanced images were selected based on Lukka's feature selection approach. An overall classification efficiency of 93.72% was achieved with just three features. Brightness preserving histogram equalization technique has great potential to improve the classification in various quality attributes of food and agricultural products with minimum features.

Text-Independent Speaker Identification Using the Histogram Transform Model

DEFF Research Database (Denmark)

Ma, Zhanyu; Yu, Hong; Tan, Zheng-Hua

2016-01-01

In this paper, we propose a novel probabilistic method for the task of text-independent speaker identification (SI). In order to capture the dynamic information during SI, we design a super-MFCCs features by cascading three neighboring Mel-frequency Cepstral coefficients (MFCCs) frames together....... These super-MFCC vectors are utilized for probabilistic model training such that the speaker’s characteristics can be sufficiently captured. The probability density function (PDF) of the aforementioned super-MFCCs features is estimated by the recently proposed histogram transform (HT) method. To recedes...

Underwater Image Enhancement by Adaptive Gray World and Differential Gray-Levels Histogram Equalization

Directory of Open Access Journals (Sweden)

WONG, S.-L.

2018-05-01

Full Text Available Most underwater images tend to be dominated by a single color cast. This paper presents a solution to remove the color cast and improve the contrast in underwater images. However, after the removal of the color cast using Gray World (GW method, the resultant image is not visually pleasing. Hence, we propose an integrated approach using Adaptive GW (AGW and Differential Gray-Levels Histogram Equalization (DHE that operate in parallel. The AGW is applied to remove the color cast while DHE is used to improve the contrast of the underwater image. The outputs of both chromaticity components of AGW and intensity components of DHE are combined to form the enhanced image. The results of the proposed method are compared with three existing methods using qualitative and quantitative measures. The proposed method increased the visibility of underwater images and in most cases produces better quantitative scores when compared to the three existing methods.

Histograms of Arecibo World Days Measurements and Linear-H Fits Between 1985 and 1995

National Research Council Canada - National Science Library

Melendez-Alvira, D

1998-01-01

This document presents histograms of linear-H model fits to electron density profiles measured with the incoherent scatter radar of the Arecibo Observatory in Puerto Rico during the World Days between 1985 and 1995...

Data analysis and graphing in an introductory physics laboratory: spreadsheet versus statistics suite

International Nuclear Information System (INIS)

Peterlin, Primoz

2010-01-01

Two methods of data analysis are compared: spreadsheet software and a statistics software suite. Their use is compared analysing data collected in three selected experiments taken from an introductory physics laboratory, which include a linear dependence, a nonlinear dependence and a histogram. The merits of each method are compared.

Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting.

Science.gov (United States)

Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn

2011-09-01

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".

Comparison of dose length, area, and volume histograms as quantifiers of urethral dose in prostate brachytherapy

International Nuclear Information System (INIS)

Butler, Wayne M.; Merrick, Gregory S.; Dorsey, Anthony T.; Hagedorn, Brenda M.

2000-01-01

Purpose: To determine the magnitude of the differences between urethral dose-volume, dose-area, and dose-length histograms (DVH, DAH, and DLH, respectively, or DgH generically). Methods and Materials: Six consecutive iodine-125 ( 125 I) patients and 6 consecutive palladium-103 ( 103 Pd) patients implanted via a modified uniform planning approach were evaluated with day 0 computed tomography (CT)-based dosimetry. The urethra was identified by the presence of a urinary catheter and was hand drawn on the CT images with a mean radius of 3.3 ± 0.7 mm. A 0.1-mm calculation matrix was employed for the urethral volume and surface analysis, and urethral dose points were placed at the centroid of the urethra on each 5-mm CT slice. Results: Although individual patient DLHs were step-like, due to the sparseness of the data points, the composite urethral DLH, DAH, and DVHs were qualitatively similar. The DAH curve delivered more radiation than the other two curves at all doses greater than 90% of the prescribed minimum peripheral dose (mPD) to the prostate. In addition, the DVH curve was consistently higher than the DLH curve at most points throughout that range. Differences between the DgH curves were analyzed by integrating the difference curves between 0 and 200% of the mPD. The area-length, area-volume, and volume-length difference curves integrated in the ratio of 3:2:1. The differences were most pronounced near the inflection point of the DgH curves with mean A 125 , V 125 , and L 125 values of 36.6%, 31.4%, and 23.0%, respectively, of the urethra. Quantifiers of urethral hot spots such as D 10 , defined as the minimal dose delivered to the hottest 10% of the urethra, followed the same ranking: area analysis indicated the highest dose and length analysis, the lowest dose. D 10 was 148% and 136% of mPD for area and length evaluations, respectively. Comparing the two isotopes in terms of the amount of urethra receiving a given dose, 103 Pd implants were significantly

Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification

Directory of Open Access Journals (Sweden)

Xiaoyang Zhao

2018-04-01

Full Text Available In recent years, digital frame cameras have been increasingly used for remote sensing applications. However, it is always a challenge to align or register images captured with different cameras or different imaging sensor units. In this research, a novel registration method was proposed. Coarse registration was first applied to approximately align the sensed and reference images. Window selection was then used to reduce the search space and a histogram specification was applied to optimize the grayscale similarity between the images. After comparisons with other commonly-used detectors, the fast corner detector, FAST (Features from Accelerated Segment Test, was selected to extract the feature points. The matching point pairs were then detected between the images, the outliers were eliminated, and geometric transformation was performed. The appropriate window size was searched and set to one-tenth of the image width. The images that were acquired by a two-camera system, a camera with five imaging sensors, and a camera with replaceable filters mounted on a manned aircraft, an unmanned aerial vehicle, and a ground-based platform, respectively, were used to evaluate the performance of the proposed method. The image analysis results showed that, through the appropriate window selection and histogram specification, the number of correctly matched point pairs had increased by 11.30 times, and that the correct matching rate had increased by 36%, compared with the results based on FAST alone. The root mean square error (RMSE in the x and y directions was generally within 0.5 pixels. In comparison with the binary robust invariant scalable keypoints (BRISK, curvature scale space (CSS, Harris, speed up robust features (SURF, and commercial software ERDAS and ENVI, this method resulted in larger numbers of correct matching pairs and smaller, more consistent RMSE. Furthermore, it was not necessary to choose any tie control points manually before registration

Histogramming in the LATOME-firmware for the Phase-1 upgrade of the ATLAS LAr calorimeter readout

Energy Technology Data Exchange (ETDEWEB)

Horn, Philipp; Hentges, Rainer; Straessner, Arno [Institut fuer Kern- und Teilchenphysik, Dresden (Germany)

2016-07-01

Due to the increased luminosity and the higher effective event rate after the phase 1 upgrade the ATLAS LAr detector needs new trigger electronics. The so-called LATOME-Board was designed as a LAr Digital Processing Blade (LPDB) to reconstruct the energy deposited by the particles and is an important part of the read out system. A prototype has already been build and the firmware for the on-board FPGA is under development. The insertion of a histogram-builder in this device gives the unique opportunity to look at untriggered data. This talk provides an insight in the LATOME-firmware and shows the different possibilities to implement the histogram-builder.

Strain histograms are equal to strain ratios in predicting malignancy in breast tumours

DEFF Research Database (Denmark)

Carlsen, Jonathan Frederik; Ewertsen, Caroline; Sletting, Susanne

2017-01-01

Objectives: To assess whether strain histograms are equal to strain ratios in predicting breast tumour malignancy and to see if either could be used to upgrade Breast Imaging Reporting and Data System (BI-RADS) 3 tumours for immediate biopsy. Methods: Ninety-nine breast tumours were examined using...

Quantitatively assessed CT imaging measures of pulmonary interstitial pneumonia: Effects of reconstruction algorithms on histogram parameters

International Nuclear Information System (INIS)

Koyama, Hisanobu; Ohno, Yoshiharu; Yamazaki, Youichi; Nogami, Munenobu; Kusaka, Akiko; Murase, Kenya; Sugimura, Kazuro

2010-01-01

This study aimed the influences of reconstruction algorithm for quantitative assessments in interstitial pneumonia patients. A total of 25 collagen vascular disease patients (nine male patients and 16 female patients; mean age, 57.2 years; age range 32-77 years) underwent thin-section MDCT examinations, and MDCT data were reconstructed with three kinds of reconstruction algorithm (two high-frequencies [A and B] and one standard [C]). In reconstruction algorithm B, the effect of low- and middle-frequency space was suppressed compared with reconstruction algorithm A. As quantitative CT parameters, kurtosis, skewness, and mean lung density (MLD) were acquired from a frequency histogram of the whole lung parenchyma in each reconstruction algorithm. To determine the difference of quantitative CT parameters affected by reconstruction algorithms, these parameters were compared statistically. To determine the relationships with the disease severity, these parameters were correlated with PFTs. In the results, all the histogram parameters values had significant differences each other (p < 0.0001) and those of reconstruction algorithm C were the highest. All MLDs had fair or moderate correlation with all parameters of PFT (-0.64 < r < -0.45, p < 0.05). Though kurtosis and skewness in high-frequency reconstruction algorithm A had significant correlations with all parameters of PFT (-0.61 < r < -0.45, p < 0.05), there were significant correlations only with diffusing capacity of carbon monoxide (DLco) and total lung capacity (TLC) in reconstruction algorithm C and with forced expiratory volume in 1 s (FEV1), DLco and TLC in reconstruction algorithm B. In conclusion, reconstruction algorithm has influence to quantitative assessments on chest thin-section MDCT examination in interstitial pneumonia patients.

Quantitatively assessed CT imaging measures of pulmonary interstitial pneumonia: Effects of reconstruction algorithms on histogram parameters

Energy Technology Data Exchange (ETDEWEB)

Koyama, Hisanobu [Department of Radiology, Hyogo Kaibara Hospital, 5208-1 Kaibara, Kaibara-cho, Tanba 669-3395 (Japan)], E-mail: hisanobu19760104@yahoo.co.jp; Ohno, Yoshiharu [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: yosirad@kobe-u.ac.jp; Yamazaki, Youichi [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: y.yamazk@sahs.med.osaka-u.ac.jp; Nogami, Munenobu [Division of PET, Institute of Biomedical Research and Innovation, 2-2 MInamimachi, Minatojima, Chu0-ku, Kobe 650-0047 (Japan)], E-mail: aznogami@fbri.org; Kusaka, Akiko [Division of Radiology, Kobe University Hospital, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: a.kusaka@hosp.kobe-u.ac.jp; Murase, Kenya [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: murase@sahs.med.osaka-u.ac.jp; Sugimura, Kazuro [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: sugimura@med.kobe-u.ac.jp

2010-04-15

This study aimed the influences of reconstruction algorithm for quantitative assessments in interstitial pneumonia patients. A total of 25 collagen vascular disease patients (nine male patients and 16 female patients; mean age, 57.2 years; age range 32-77 years) underwent thin-section MDCT examinations, and MDCT data were reconstructed with three kinds of reconstruction algorithm (two high-frequencies [A and B] and one standard [C]). In reconstruction algorithm B, the effect of low- and middle-frequency space was suppressed compared with reconstruction algorithm A. As quantitative CT parameters, kurtosis, skewness, and mean lung density (MLD) were acquired from a frequency histogram of the whole lung parenchyma in each reconstruction algorithm. To determine the difference of quantitative CT parameters affected by reconstruction algorithms, these parameters were compared statistically. To determine the relationships with the disease severity, these parameters were correlated with PFTs. In the results, all the histogram parameters values had significant differences each other (p < 0.0001) and those of reconstruction algorithm C were the highest. All MLDs had fair or moderate correlation with all parameters of PFT (-0.64 < r < -0.45, p < 0.05). Though kurtosis and skewness in high-frequency reconstruction algorithm A had significant correlations with all parameters of PFT (-0.61 < r < -0.45, p < 0.05), there were significant correlations only with diffusing capacity of carbon monoxide (DLco) and total lung capacity (TLC) in reconstruction algorithm C and with forced expiratory volume in 1 s (FEV1), DLco and TLC in reconstruction algorithm B. In conclusion, reconstruction algorithm has influence to quantitative assessments on chest thin-section MDCT examination in interstitial pneumonia patients.

Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

Science.gov (United States)

Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

2018-05-01

Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions–comparison of glioblastomas and brain abscesses

Science.gov (United States)

Hoffmann, Karl-Titus; Garnov, Nikita; Vörkel, Cathrin; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Bäzner, Hansjörg; Gihr, Georg Alexander; Kalman, Marcell; Henkes, Elina; Henkes, Hans; Schob, Stefan

2018-01-01

Background Morphologically similar appearing ring enhancing lesions in the brain parenchyma can be caused by a number of distinct pathologies, however, they consistently represent life-threatening conditions. The two most frequently encountered diseases manifesting as such are glioblastoma multiforme (GBM) and brain abscess (BA), each requiring disparate therapeutical approaches. As a result of their morphological resemblance, essential treatment might be significantly delayed or even ommited, in case results of conventional imaging remain inconclusive. Therefore, our study aimed to investigate, whether ADC histogram profiling reliably can distinguish between both entities, thus enhancing the differential diagnostic process and preventing treatment failure in this highly critical context. Methods 103 patients (51 BA, 52 GBM) with histopathologically confirmed diagnosis were enrolled. Pretreatment diffusion weighted imaging (DWI) was obtained in a 1.5T system using b values of 0, 500, and 1000 s/mm2. Whole lesion ADC volumes were analyzed using a histogram-based approach. Statistical analysis was performed using SPSS version 23. Results All investigated parameters were statistically different in comparison of both groups. Most importantly, ADCp10 was able to differentiate reliably between BA and GBM with excellent accuracy (0.948) using a cutpoint value of 70 × 10−5 mm2 × s−1. Conclusions ADC whole lesion histogram profiling provides a valuable tool to differentiate between morphologically indistinguishable mass lesions. Among the investigated parameters, the 10th percentile of the ADC volume distinguished best between GBM and BA. PMID:29719596

The value of whole lesion ADC histogram profiling to differentiate between morphologically indistinguishable ring enhancing lesions-comparison of glioblastomas and brain abscesses.

Science.gov (United States)

Horvath-Rizea, Diana; Surov, Alexey; Hoffmann, Karl-Titus; Garnov, Nikita; Vörkel, Cathrin; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Bäzner, Hansjörg; Gihr, Georg Alexander; Kalman, Marcell; Henkes, Elina; Henkes, Hans; Schob, Stefan

2018-04-06

Morphologically similar appearing ring enhancing lesions in the brain parenchyma can be caused by a number of distinct pathologies, however, they consistently represent life-threatening conditions. The two most frequently encountered diseases manifesting as such are glioblastoma multiforme (GBM) and brain abscess (BA), each requiring disparate therapeutical approaches. As a result of their morphological resemblance, essential treatment might be significantly delayed or even ommited, in case results of conventional imaging remain inconclusive. Therefore, our study aimed to investigate, whether ADC histogram profiling reliably can distinguish between both entities, thus enhancing the differential diagnostic process and preventing treatment failure in this highly critical context. 103 patients (51 BA, 52 GBM) with histopathologically confirmed diagnosis were enrolled. Pretreatment diffusion weighted imaging (DWI) was obtained in a 1.5T system using b values of 0, 500, and 1000 s/mm 2 . Whole lesion ADC volumes were analyzed using a histogram-based approach. Statistical analysis was performed using SPSS version 23. All investigated parameters were statistically different in comparison of both groups. Most importantly, ADCp10 was able to differentiate reliably between BA and GBM with excellent accuracy (0.948) using a cutpoint value of 70 × 10 -5 mm 2 × s -1 . ADC whole lesion histogram profiling provides a valuable tool to differentiate between morphologically indistinguishable mass lesions. Among the investigated parameters, the 10th percentile of the ADC volume distinguished best between GBM and BA.

TaBoo SeArch Algorithm with a Modified Inverse Histogram for Reproducing Biologically Relevant Rare Events of Proteins.

Science.gov (United States)

Harada, Ryuhei; Takano, Yu; Shigeta, Yasuteru

2016-05-10

The TaBoo SeArch (TBSA) algorithm [ Harada et al. J. Comput. Chem. 2015 , 36 , 763 - 772 and Harada et al. Chem. Phys. Lett. 2015 , 630 , 68 - 75 ] was recently proposed as an enhanced conformational sampling method for reproducing biologically relevant rare events of a given protein. In TBSA, an inverse histogram of the original distribution, mapped onto a set of reaction coordinates, is constructed from trajectories obtained by multiple short-time molecular dynamics (MD) simulations. Rarely occurring states of a given protein are statistically selected as new initial states based on the inverse histogram, and resampling is performed by restarting the MD simulations from the new initial states to promote the conformational transition. In this process, the definition of the inverse histogram, which characterizes the rarely occurring states, is crucial for the efficiency of TBSA. In this study, we propose a simple modification of the inverse histogram to further accelerate the convergence of TBSA. As demonstrations of the modified TBSA, we applied it to (a) hydrogen bonding rearrangements of Met-enkephalin, (b) large-amplitude domain motions of Glutamine-Binding Protein, and (c) folding processes of the B domain of Staphylococcus aureus Protein A. All demonstrations numerically proved that the modified TBSA reproduced these biologically relevant rare events with nanosecond-order simulation times, although a set of microsecond-order, canonical MD simulations failed to reproduce the rare events, indicating the high efficiency of the modified TBSA.

Data Analysis and Graphing in an Introductory Physics Laboratory: Spreadsheet versus Statistics Suite

Science.gov (United States)

Peterlin, Primoz

2010-01-01

Two methods of data analysis are compared: spreadsheet software and a statistics software suite. Their use is compared analysing data collected in three selected experiments taken from an introductory physics laboratory, which include a linear dependence, a nonlinear dependence and a histogram. The merits of each method are compared. (Contains 7…

Breast density pattern characterization by histogram features and texture descriptors

OpenAIRE

Carneiro,Pedro Cunha; Franco,Marcelo Lemos Nunes; Thomaz,Ricardo de Lima; Patrocinio,Ana Claudia

2017-01-01

Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammo...

Color and Contrast Enhancement by Controlled Piecewise Affine Histogram Equalization

Directory of Open Access Journals (Sweden)

Jose-Luis Lisani

2012-10-01

Full Text Available This paper presents a simple contrast enhancement algorithm based on histogram equalization (HE. The proposed algorithm performs a piecewise affine transform of the intensity levels of a digital image such that the new cumulative distribution function will be approximately uniform (as with HE, but where the stretching of the range is locally controlled to avoid brutal noise enhancement. We call this algorithm Piecewise Affine Equalization (PAE. Several experiments show that, in general, the new algorithm improves HE results.

Accelerated weight histogram method for exploring free energy landscapes

Energy Technology Data Exchange (ETDEWEB)

Lindahl, V.; Lidmar, J.; Hess, B. [Department of Theoretical Physics and Swedish e-Science Research Center, KTH Royal Institute of Technology, 10691 Stockholm (Sweden)

2014-07-28

Calculating free energies is an important and notoriously difficult task for molecular simulations. The rapid increase in computational power has made it possible to probe increasingly complex systems, yet extracting accurate free energies from these simulations remains a major challenge. Fully exploring the free energy landscape of, say, a biological macromolecule typically requires sampling large conformational changes and slow transitions. Often, the only feasible way to study such a system is to simulate it using an enhanced sampling method. The accelerated weight histogram (AWH) method is a new, efficient extended ensemble sampling technique which adaptively biases the simulation to promote exploration of the free energy landscape. The AWH method uses a probability weight histogram which allows for efficient free energy updates and results in an easy discretization procedure. A major advantage of the method is its general formulation, making it a powerful platform for developing further extensions and analyzing its relation to already existing methods. Here, we demonstrate its efficiency and general applicability by calculating the potential of mean force along a reaction coordinate for both a single dimension and multiple dimensions. We make use of a non-uniform, free energy dependent target distribution in reaction coordinate space so that computational efforts are not wasted on physically irrelevant regions. We present numerical results for molecular dynamics simulations of lithium acetate in solution and chignolin, a 10-residue long peptide that folds into a β-hairpin. We further present practical guidelines for setting up and running an AWH simulation.

Efficient Scalable Median Filtering Using Histogram-Based Operations.

Science.gov (United States)

Green, Oded

2018-05-01

Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering window and taking the median of the sorted value. While using sorting algorithms allows for simple parallel implementations, the cost of the sorting becomes prohibitive as the filtering windows grow. This makes such algorithms, sequential and parallel alike, inefficient. In this work, we introduce the first software parallel median filtering that is non-sorting-based. The new algorithm uses efficient histogram-based operations. These reduce the computational requirements of the new algorithm while also accessing the image fewer times. We show an implementation of our algorithm for both the CPU and NVIDIA's CUDA supported graphics processing unit (GPU). The new algorithm is compared with several other leading CPU and GPU implementations. The CPU implementation has near perfect linear scaling with a speedup on a quad-core system. The GPU implementation is several orders of magnitude faster than the other GPU implementations for mid-size median filters. For small kernels, and , comparison-based approaches are preferable as fewer operations are required. Lastly, the new algorithm is open-source and can be found in the OpenCV library.

Clarification of the use of chi-square and likelihood functions in fits to histograms

International Nuclear Information System (INIS)

Baker, S.; Cousins, R.D.

1984-01-01

We consider the problem of fitting curves to histograms in which the data obey multinomial or Poisson statistics. Techniques commonly used by physicists are examined in light of standard results found in the statistics literature. We review the relationship between multinomial and Poisson distributions, and clarify a sufficient condition for equality of the area under the fitted curve and the number of events on the histogram. Following the statisticians, we use the likelihood ratio test to construct a general Z 2 statistic, Zsub(lambda) 2 , which yields parameter and error estimates identical to those of the method of maximum likelihood. The Zsub(lambda) 2 statistic is further useful for testing goodness-of-fit since the value of its minimum asymptotically obeys a classical chi-square distribution. One should be aware, however, of the potential for statistical bias, especially when the number of events is small. (orig.)

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis.

Science.gov (United States)

Nguyen-Kim, Thi Dan Linh; Maurer, Britta; Suliman, Yossra A; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-04-01

To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (Phistogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both Phistogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both Phistogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.

Histogram-Based Thresholding for Detection and Quantification of Hemorrhages in Retinal Images

Directory of Open Access Journals (Sweden)

Hussain Fadhel Hamdan Jaafar

2016-12-01

Full Text Available Retinal image analysis is commonly used for the detection and quantification of retinal diabetic retinopathy. In retinal images, dark lesions including hemorrhages and microaneurysms are the earliest warnings of vision loss. In this paper, new algorithm for extraction and quantification of hemorrhages in fundus images is presented. Hemorrhage candidates are extracted in a preliminary step as a coarse segmentation followed by a fine segmentation step. Local variation processes are applied in the coarse segmentation step to determine boundaries of all candidates with distinct edges. Fine segmentation processes are based on histogram thresholding to extract real hemorrhages from the segmented candidates locally. The proposed method was trained and tested using an image dataset of 153 manually labeled retinal images. At the pixel level, the proposed method could identify abnormal retinal images with 90.7% sensitivity and 85.1% predictive value. Due to its distinctive performance measurements, this technique demonstrates that it could be used for a computer-aided mass screening of retinal diseases.

Histogram-based automatic thresholding for bruise detection of apples by structured-illumination reflectance imaging

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Thresholding is an important step in the segmentation of image features, and the existing methods are not all effective when the image histogram exhibits a unimodal pattern, which is common in defect detection of fruit. This study was aimed at developing a general automatic thresholding methodology ...

Equivalent uniform dose concept evaluated by theoretical dose volume histograms for thoracic irradiation.

Science.gov (United States)

Dumas, J L; Lorchel, F; Perrot, Y; Aletti, P; Noel, A; Wolf, D; Courvoisier, P; Bosset, J F

2007-03-01

The goal of our study was to quantify the limits of the EUD models for use in score functions in inverse planning software, and for clinical application. We focused on oesophagus cancer irradiation. Our evaluation was based on theoretical dose volume histograms (DVH), and we analyzed them using volumetric and linear quadratic EUD models, average and maximum dose concepts, the linear quadratic model and the differential area between each DVH. We evaluated our models using theoretical and more complex DVHs for the above regions of interest. We studied three types of DVH for the target volume: the first followed the ICRU dose homogeneity recommendations; the second was built out of the first requirements and the same average dose was built in for all cases; the third was truncated by a small dose hole. We also built theoretical DVHs for the organs at risk, in order to evaluate the limits of, and the ways to use both EUD(1) and EUD/LQ models, comparing them to the traditional ways of scoring a treatment plan. For each volume of interest we built theoretical treatment plans with differences in the fractionation. We concluded that both volumetric and linear quadratic EUDs should be used. Volumetric EUD(1) takes into account neither hot-cold spot compensation nor the differences in fractionation, but it is more sensitive to the increase of the irradiated volume. With linear quadratic EUD/LQ, a volumetric analysis of fractionation variation effort can be performed.

Analisis gambaran histogramdan densitas kamar pulpa pada gigi suspek pulpitis reversibel dan ireversibel dengan menggunakan radiografi cone beam computed tomography (Histogram and density analysis of irreversible and reversible pulpitissuspected tooth using cone beam computed tomography radiography)

OpenAIRE

Lusi Epsilawati; Suhardjo Sitam; Sam Belly; Fahmi Oscandar

2014-01-01

Inflammation of the pulp is most common and difficult to diagnose. For it radiographs is necessary. One attempt to do is to assess its histogram and density. Radiography equipment that has the ability to analyze is cone beam computed tomography (CBCT). The purpose of this study is to analyze radiograph of the pulp chamber histogram: peak value, grayscale and trends , as well as the density on the condition reversible and irreversible pulpitis condition. The population of this ...

Online Data Monitoring Framework Based on Histogram Packaging in Network Distributed Data Acquisition Systems

International Nuclear Information System (INIS)

Konno, T; Ishitsuka, M; Kuze, M; Cabarera, A; Sakamoto, Y

2011-01-01

O nline monitor frameworkis a new general software framework for online data monitoring, which provides a way to collect information from online systems, including data acquisition, and displays them to shifters far from experimental sites. 'Monitor Server', a core system in this framework gathers the monitoring information from the online subsystems and the information is handled as collections of histograms named H istogram Package . Monitor Server broadcasts the histogram packages to 'Monitor Viewers', graphical user interfaces in the framework. We developed two types of the viewers with different technologies: Java and web browser. We adapted XML based file for the configuration of GUI components on the windows and graphical objects on the canvases. Monitor Viewer creates its GUIs automatically with the configuration files.This monitoring framework has been developed for the Double Chooz reactor neutrino oscillation experiment in France, but can be extended for general application to be used in other experiments. This document reports the structure of the online monitor framework with some examples from the adaption to the Double Chooz experiment.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

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Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

DIF Testing with an Empirical-Histogram Approximation of the Latent Density for Each Group

Science.gov (United States)

Woods, Carol M.

2011-01-01

This research introduces, illustrates, and tests a variation of IRT-LR-DIF, called EH-DIF-2, in which the latent density for each group is estimated simultaneously with the item parameters as an empirical histogram (EH). IRT-LR-DIF is used to evaluate the degree to which items have different measurement properties for one group of people versus…

Histogram plots and cutoff energies for nuclear discrete levels

International Nuclear Information System (INIS)

Belgya, T.; Molnar, G.; Fazekas, B.; Oestoer, J.

1997-05-01

Discrete level schemes for 1277 nuclei, from 6 Li through 251 Es, extracted from the Evaluated Nuclear Structure Data File were analyzed. Cutoff energies (U max ), indicating the upper limit of level scheme completeness, were deduced from the inspection of histograms of the cumulative number of levels. Parameters of the constant-temperature level density formula (nuclear temperature T and energy shift U 0 ) were obtained by means of the least square fit of the formula to the known levels below cutoff energy. The results are tabulated for all 1277 nuclei allowing for an easy and reliable application of the constant-temperature level density approach. A complete set of cumulative plots of discrete levels is also provided. (author). 5 figs, 2 tabs

The combination of a histogram-based clustering algorithm and support vector machine for the diagnosis of osteoporosis

International Nuclear Information System (INIS)

Heo, Min Suk; Kavitha, Muthu Subash; Asano, Akira; Taguchi, Akira

2013-01-01

To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis. We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion. The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck. Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.

Adaptive Kalman filtering for histogram-based appearance learning in infrared imagery.

Science.gov (United States)

Venkataraman, Vijay; Fan, Guoliang; Havlicek, Joseph P; Fan, Xin; Zhai, Yan; Yeary, Mark B

2012-11-01

Targets of interest in video acquired from imaging infrared sensors often exhibit profound appearance variations due to a variety of factors, including complex target maneuvers, ego-motion of the sensor platform, background clutter, etc., making it difficult to maintain a reliable detection process and track lock over extended time periods. Two key issues in overcoming this problem are how to represent the target and how to learn its appearance online. In this paper, we adopt a recent appearance model that estimates the pixel intensity histograms as well as the distribution of local standard deviations in both the foreground and background regions for robust target representation. Appearance learning is then cast as an adaptive Kalman filtering problem where the process and measurement noise variances are both unknown. We formulate this problem using both covariance matching and, for the first time in a visual tracking application, the recent autocovariance least-squares (ALS) method. Although convergence of the ALS algorithm is guaranteed only for the case of globally wide sense stationary process and measurement noises, we demonstrate for the first time that the technique can often be applied with great effectiveness under the much weaker assumption of piecewise stationarity. The performance advantages of the ALS method relative to the classical covariance matching are illustrated by means of simulated stationary and nonstationary systems. Against real data, our results show that the ALS-based algorithm outperforms the covariance matching as well as the traditional histogram similarity-based methods, achieving sub-pixel tracking accuracy against the well-known AMCOM closure sequences and the recent SENSIAC automatic target recognition dataset.

Apparent diffusion coefficient histogram metrics correlate with survival in diffuse intrinsic pontine glioma: a report from the Pediatric Brain Tumor Consortium

Science.gov (United States)

Poussaint, Tina Young; Vajapeyam, Sridhar; Ricci, Kelsey I.; Panigrahy, Ashok; Kocak, Mehmet; Kun, Larry E.; Boyett, James M.; Pollack, Ian F.; Fouladi, Maryam

2016-01-01

Background Diffuse intrinsic pontine glioma (DIPG) is associated with poor survival regardless of therapy. We used volumetric apparent diffusion coefficient (ADC) histogram metrics to determine associations with progression-free survival (PFS) and overall survival (OS) at baseline and after radiation therapy (RT). Methods Baseline and post-RT quantitative ADC histograms were generated from fluid-attenuated inversion recovery (FLAIR) images and enhancement regions of interest. Metrics assessed included number of peaks (ie, unimodal or bimodal), mean and median ADC, standard deviation, mode, skewness, and kurtosis. Results Based on FLAIR images, the majority of tumors had unimodal peaks with significantly shorter average survival. Pre-RT FLAIR mean, mode, and median values were significantly associated with decreased risk of progression; higher pre-RT ADC values had longer PFS on average. Pre-RT FLAIR skewness and standard deviation were significantly associated with increased risk of progression; higher pre-RT FLAIR skewness and standard deviation had shorter PFS. Nonenhancing tumors at baseline showed higher ADC FLAIR mean values, lower kurtosis, and higher PFS. For enhancing tumors at baseline, bimodal enhancement histograms had much worse PFS and OS than unimodal cases and significantly lower mean peak values. Enhancement in tumors only after RT led to significantly shorter PFS and OS than in patients with baseline or no baseline enhancement. Conclusions ADC histogram metrics in DIPG demonstrate significant correlations between diffusion metrics and survival, with lower diffusion values (increased cellularity), increased skewness, and enhancement associated with shorter survival, requiring future investigations in large DIPG clinical trials. PMID:26487690

Optimization of stereotactically-guided conformal treatment planning of sellar and parasellar tumors, based on normal brain dose volume histograms

International Nuclear Information System (INIS)

Perks, Julian R.; Jalali, Rakesh; Cosgrove, Vivian P.; Adams, Elizabeth J.; Shepherd, Stephen F.; Warrington, Alan P.; Brada, Michael

1999-01-01

Purpose: To investigate the optimal treatment plan for stereo tactically-guided conformal radiotherapy (SCRT) of sellar and parasellar lesions, with respect to sparing normal brain tissue, in the context of routine treatment delivery, based on dose volume histogram analysis. Methods and Materials: Computed tomography (CT) data sets for 8 patients with sellar- and parasellar-based tumors (6 pituitary adenomas and 2 meningiomas) have been used in this study. Treatment plans were prepared for 3-coplanar and 3-, 4-, 6-, and 30-noncoplanar-field arrangements to obtain 95% isodose coverage of the planning target volume (PTV) for each plan. Conformal shaping was achieved by customized blocks generated with the beams eye view (BEV) facility. Dose volume histograms (DVH) were calculated for the normal brain (excluding the PTV), and comparisons made for normal tissue sparing for all treatment plans at ≥80%, ≥60%, and ≥40% of the prescribed dose. Results: The mean volume of normal brain receiving ≥80% and ≥60% of the prescribed dose decreased by 22.3% (range 14.8-35.1%, standard deviation σ = 7.5%) and 47.6% (range 25.8-69.1%, σ 13.2%), respectively, with a 4-field noncoplanar technique when compared with a conventional 3-field coplanar technique. Adding 2 further fields, from 4-noncoplanar to 6-noncoplanar fields reduced the mean normal brain volume receiving ≥80% of the prescribed dose by a further 4.1% (range -6.5-11.8%, σ = 6.4%), and the volume receiving ≥60% by 3.3% (range -5.5-12.2%, σ = 5.4%), neither of which were statistically significant. Each case must be considered individually however, as a wide range is seen in the volume spared when increasing the number of fields from 4 to 6. Comparing the 4- and 6-field noncoplanar techniques to a 30-field conformal field approach (simulating a dynamic arc plan) revealed near-equivalent normal tissue sparing. Conclusion: Four to six widely spaced, fixed-conformal fields provide the optimum class solution

The incorporation of specific tissue/nuclide attenuation data into the Anderson method for producing brachytherapy volume-dose histograms

International Nuclear Information System (INIS)

Loft, S.M.; Dale, R.G.

1990-01-01

Anderson (1986) has proposed an analytical method for deriving volume-dose histograms relating to three-dimensional brachytherapy distributions. Because the mathematical transformation allows the otherwise dominant effects of the inverse-square fall-off about individual sources to be effectively suppressed, resulting histograms provide the potential for visually and numerically assessing overall quality of a brachytherapy treatment. In this paper the Anderson equations have been combined with the radial-dose polynomials of Dale, which are applicable to a number of tissue/nuclide combinations, and the predictions of the combined formalism used to further investigate the physical aspects of brachytherapy dosimetry. The problems associated with the dosimetry of low-energy γ-emitters such as 125 I are once again highlighted, as are potential advantages of using a radionuclide with an intermediate γ-ray energy. (author)

Temporal Evolution and Dose-Volume Histogram Predictors of Visual Acuity After Proton Beam Radiation Therapy of Uveal Melanoma

Energy Technology Data Exchange (ETDEWEB)

Polishchuk, Alexei L. [Department of Radiation Oncology, University of California, San Francisco, San Francisco, California (United States); Mishra, Kavita K., E-mail: Kavita.Mishra@ucsf.edu [Department of Radiation Oncology, University of California, San Francisco, San Francisco, California (United States); Weinberg, Vivian; Daftari, Inder K. [Department of Radiation Oncology, University of California, San Francisco, San Francisco, California (United States); Nguyen, Jacqueline M.; Cole, Tia B. [Tumori Foundation, San Francisco, California (United States); Quivey, Jeanne M.; Phillips, Theodore L. [Department of Radiation Oncology, University of California, San Francisco, San Francisco, California (United States); Char, Devron H. [Tumori Foundation, San Francisco, California (United States)

2017-01-01

Purpose: To perform an in-depth temporal analysis of visual acuity (VA) outcomes after proton beam radiation therapy (PBRT) in a large, uniformly treated cohort of uveal melanoma (UM) patients, to determine trends in VA evolution depending on pretreatment and temporally defined posttreatment VA measurements; and to investigate the relevance of specific patient, tumor and dose-volume parameters to posttreatment vision loss. Methods and Materials: Uveal melanoma patients receiving PBRT were identified from a prospectively maintained database. Included patients (n=645) received 56 GyE in 4 fractions, had pretreatment best corrected VA (BCVA) in the affected eye of count fingers (CF) or better, with posttreatment VA assessment at specified post-PBRT time point(s). Patients were grouped according to the pretreatment BCVA into favorable (≥20/40) or unfavorable (20/50-20/400) and poor (CF) strata. Temporal analysis of BCVA changes was described, and univariate and forward stepwise multivariate logistic regression analyses were performed to identify predictors for VA loss. Results: Median VA follow-up was 53 months (range, 3-213 months). At 60-month follow up, among evaluable treated eyes with favorable pretreatment BCVA, 45% retained BCVA ≥20/40, whereas among evaluable treated eyes with initially unfavorable/poor BCVA, 21% had vision ≥20/100. Among those with a favorable initial BCVA, attaining BCVA of ≥20/40 at any posttreatment time point was associated with subsequent maintenance of excellent BCVA. Multivariate analysis identified volume of the macula receiving 28GyE (P<.0001) and optic nerve (P=.0004) as independent dose-volume histogram predictors of 48-month post-PBRT vision loss among initially favorable treated eyes. Conclusions: Approximately half of PBRT-treated UM eyes with excellent pretreatment BCVA assessed at 5 years after treatment will retain excellent long-term vision. 28GyE macula and optic nerve dose-volume histogram parameters allow for

Directional Histogram Ratio at Random Probes: A Local Thresholding Criterion for Capillary Images

Science.gov (United States)

Lu, Na; Silva, Jharon; Gu, Yu; Gerber, Scott; Wu, Hulin; Gelbard, Harris; Dewhurst, Stephen; Miao, Hongyu

2013-01-01

With the development of micron-scale imaging techniques, capillaries can be conveniently visualized using methods such as two-photon and whole mount microscopy. However, the presence of background staining, leaky vessels and the diffusion of small fluorescent molecules can lead to significant complexity in image analysis and loss of information necessary to accurately quantify vascular metrics. One solution to this problem is the development of accurate thresholding algorithms that reliably distinguish blood vessels from surrounding tissue. Although various thresholding algorithms have been proposed, our results suggest that without appropriate pre- or post-processing, the existing approaches may fail to obtain satisfactory results for capillary images that include areas of contamination. In this study, we propose a novel local thresholding algorithm, called directional histogram ratio at random probes (DHR-RP). This method explicitly considers the geometric features of tube-like objects in conducting image binarization, and has a reliable performance in distinguishing small vessels from either clean or contaminated background. Experimental and simulation studies suggest that our DHR-RP algorithm is superior over existing thresholding methods. PMID:23525856

Optimization of the fractionated irradiation scheme considering physical doses to tumor and organ at risk based on dose–volume histograms

Energy Technology Data Exchange (ETDEWEB)

Sugano, Yasutaka [Graduate School of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, Hokkaido 060-0812 (Japan); Mizuta, Masahiro [Laboratory of Advanced Data Science, Information Initiative Center, Hokkaido University, Kita-11, Nishi-5, Kita-ku, Sapporo, Hokkaido 060-0811 (Japan); Takao, Seishin; Shirato, Hiroki; Sutherland, Kenneth L. [Department of Radiation Medicine, Graduate School of Medicine, Hokkaido University, Kita-15, Nishi-5, Kita-ku, Sapporo, Hokkaido 060-8638 (Japan); Date, Hiroyuki, E-mail: date@hs.hokudai.ac.jp [Faculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, Hokkaido 060-0812 (Japan)

2015-11-15

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of the tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.

Analysis of the early response to chemotherapy in lung cancer using ...

African Journals Online (AJOL)

Histogram analysis based on the whole-tumor ROI method is preferred for .... displayed on the y-axis. The histogram ... Wang H, Fei B. Diffusion-weighted MRI for monitoring ... Ahn SJ, Choi SH, Kim YJ, Kim KG, Sohn CH, Han MH,. Chang KH ...

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

Science.gov (United States)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

Directory of Open Access Journals (Sweden)

Iwan Setyawan

2011-12-01

Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.

Aerial radiometric and magnetic reconnaissance survey of the Delta Quadrangle, Utah. Volume 2. Maps, profiles, and histograms. Final report

International Nuclear Information System (INIS)

1978-11-01

Results of the interpretation of the gamma-ray spectrometric data in the form of a preferred anomaly map, along with significance-factor profile maps, stacked profiles, and histograms are presented in Volume 2

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

Science.gov (United States)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

Flow cytometric life cycle analysis in cellular radiation biology

International Nuclear Information System (INIS)

Wood, J.C.S.

1982-01-01

Three approaches to flow cytometric histogram analysis were developed: (1) differential histogram analysis, (2) DNA histogram analysis, and (3) multiparameter data analysis. These techniques were applied to an important unresolved problem in radiation biology. The initial responses to irradiation of a mammalian cell which occur during the first two cell cycles following the irradiation are of considerable interest to the radiation biologist. During the first two post-irradiation cell cycles, cells which ultimately will survive repair radiation-induced damage, while some cells begin to express some of the radiation-induced nuclear and chomatin damage. Caffeine- and thymidine-treated, and untreated gamma-irradiated cell populations were studied with respect to the radiation-induced G2 delay, deficient DNA synthesis, and the appearance of cells with abnormal DNA contents. It is hypothesized that the measured deficiency in DNA synthesis observed in the first post-irradiation cell cycle may be a result of daughter cells from abnormal first post-irradiation mitoses

Enhancement of Edge-based Image Quality Measures Using Entropy for Histogram Equalization-based Contrast Enhancement Techniques

Directory of Open Access Journals (Sweden)

H. T. R. Kurmasha

2017-12-01

Full Text Available An Edge-based image quality measure (IQM technique for the assessment of histogram equalization (HE-based contrast enhancement techniques has been proposed that outperforms the Absolute Mean Brightness Error (AMBE and Entropy which are the most commonly used IQMs to evaluate Histogram Equalization based techniques, and also the two prominent fidelity-based IQMs which are Multi-Scale Structural Similarity (MSSIM and Information Fidelity Criterion-based (IFC measures. The statistical evaluation results show that the Edge-based IQM, which was designed for detecting noise artifacts distortion, has a Person Correlation Coefficient (PCC > 0.86 while the others have poor or fair correlation to human opinion, considering the Human Visual Perception (HVP. Based on HVP, this paper propose an enhancement to classic Edge-based IQM by taking into account the brightness saturation distortion which is the most prominent distortion in HE-based contrast enhancement techniques. It is tested and found to have significantly well correlation (PCC > 0.87, Spearman rank order correlation coefficient (SROCC > 0.92, Root Mean Squared Error (RMSE < 0.1054, and Outlier Ratio (OR = 0%.

Classification of facial-emotion expression in the application of psychotherapy using Viola-Jones and Edge-Histogram of Oriented Gradient.

Science.gov (United States)

Candra, Henry; Yuwono, Mitchell; Rifai Chai; Nguyen, Hung T; Su, Steven

2016-08-01

Psychotherapy requires appropriate recognition of patient's facial-emotion expression to provide proper treatment in psychotherapy session. To address the needs this paper proposed a facial emotion recognition system using Combination of Viola-Jones detector together with a feature descriptor we term Edge-Histogram of Oriented Gradients (E-HOG). The performance of the proposed method is compared with various feature sources including the face, the eyes, the mouth, as well as both the eyes and the mouth. Seven classes of basic emotions have been successfully identified with 96.4% accuracy using Multi-class Support Vector Machine (SVM). The proposed descriptor E-HOG is much leaner to compute compared to traditional HOG as shown by a significant improvement in processing time as high as 1833.33% (p-value = 2.43E-17) with a slight reduction in accuracy of only 1.17% (p-value = 0.0016).

A dose-volume histogram based decision-support system for dosimetric comparison of radiotherapy treatment plans

International Nuclear Information System (INIS)

Alfonso, J. C. L.; Herrero, M. A.; Núñez, L.

2015-01-01

The choice of any radiotherapy treatment plan is usually made after the evaluation of a few preliminary isodose distributions obtained from different beam configurations. Despite considerable advances in planning techniques, such final decision remains a challenging task that would greatly benefit from efficient and reliable assessment tools. For any dosimetric plan considered, data on dose-volume histograms supplied by treatment planning systems are used to provide estimates on planning target coverage as well as on sparing of organs at risk and the remaining healthy tissue. These partial metrics are then combined into a dose distribution index (DDI), which provides a unified, easy-to-read score for each competing radiotherapy plan. To assess the performance of the proposed scoring system, DDI figures for fifty brain cancer patients were retrospectively evaluated. Patients were divided in three groups depending on tumor location and malignancy. For each patient, three tentative plans were designed and recorded during planning, one of which was eventually selected for treatment. We thus were able to compare the plans with better DDI scores and those actually delivered. When planning target coverage and organs at risk sparing are considered as equally important, the tentative plan with the highest DDI score is shown to coincide with that actually delivered in 32 of the 50 patients considered. In 15 (respectively 3) of the remaining 18 cases, the plan with highest DDI value still coincides with that actually selected, provided that organs at risk sparing is given higher priority (respectively, lower priority) than target coverage. DDI provides a straightforward and non-subjective tool for dosimetric comparison of tentative radiotherapy plans. In particular, DDI readily quantifies differences among competing plans with similar-looking dose-volume histograms and can be easily implemented for any tumor type and localization, irrespective of the planning system and

Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier.

Science.gov (United States)

Zhang, Baochang; Yang, Yun; Chen, Chen; Yang, Linlin; Han, Jungong; Shao, Ling

2017-10-01

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art.

Fast Graph Partitioning Active Contours for Image Segmentation Using Histograms

Directory of Open Access Journals (Sweden)

Nath SumitK

2009-01-01

Full Text Available Abstract We present a method to improve the accuracy and speed, as well as significantly reduce the memory requirements, for the recently proposed Graph Partitioning Active Contours (GPACs algorithm for image segmentation in the work of Sumengen and Manjunath (2006. Instead of computing an approximate but still expensive dissimilarity matrix of quadratic size, , for a 2D image of size and regular image tiles of size , we use fixed length histograms and an intensity-based symmetric-centrosymmetric extensor matrix to jointly compute terms associated with the complete dissimilarity matrix. This computationally efficient reformulation of GPAC using a very small memory footprint offers two distinct advantages over the original implementation. It speeds up convergence of the evolving active contour and seamlessly extends performance of GPAC to multidimensional images.

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

Energy Technology Data Exchange (ETDEWEB)

Jerome, Neil P.; Miyazaki, Keiko; Collins, David J.; Orton, Matthew R.; D' Arcy, James A.; Leach, Martin O. [Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London (United Kingdom); Wallace, Toni; Koh, Dow-Mu [Royal Marsden NHS Foundation Trust, Department of Radiology, Sutton, Surrey (United Kingdom); Moreno, Lucas [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Hospital Nino Jesus, Madrid (Spain); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom); Pearson, Andrew D.J.; Marshall, Lynley V.; Carceller, Fernando; Zacharoulis, Stergios [The Institute of Cancer Research, Paediatric Drug Development Team, Division of Cancer Therapeutics and Clinical Studies, London (United Kingdom); Royal Marsden NHS Foundation Trust, Paediatric Drug Development Unit, Children and Young People' s Unit, Sutton, Surrey (United Kingdom)

2017-01-15

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours. Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm{sup -2} s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians. The values for ADC, D, DDC{sub α}, α, and DDC{sub K} gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDC{sub α}, and DDC{sub K} were strongly correlated (ρ > 0.9), DDC{sub α} and α were not correlated (ρ = 0.083). Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDC{sub α} and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data. (orig.)

Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.

Science.gov (United States)

Naud, Richard; Gerstner, Wulfram

2012-01-01

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation. As a modeling framework, we use the spike response model, also known as the generalized linear neuron model. Because of refractoriness, the effect of the most recent spike on the spiking probability a few milliseconds later is very strong. The influence of the last spike needs therefore to be described with high precision, while the rest of the neuronal spiking history merely introduces an average self-inhibition or adaptation that depends on the expected number of past spikes but not on the exact spike timings. Based on these insights, we derive a 'quasi-renewal equation' which is shown to yield an excellent description of the firing rate of adapting neurons. We explore the domain of validity of the quasi-renewal equation and compare it with other rate equations for populations of spiking neurons. The problem of decoding the stimulus from the population response (or PSTH) is addressed analogously. We find that for small levels of activity and weak adaptation, a simple accumulator of the past activity is sufficient to decode the original input, but when refractory effects become large decoding becomes a non-linear function of the past activity. The results presented here can be applied to the mean-field analysis of coupled neuron networks, but also to arbitrary point processes with negative self-interaction.

Dose-volume histogram analysis of hepatic toxicity related to carbon ion radiation therapy of hepatocellular carcinoma

International Nuclear Information System (INIS)

Yasuda, Shigeo; Kato, Hirotoshi; Tsujii, Hitohiko; Mizoe, Junetsu

2005-01-01

The purpose of this study is to analyze the correlation of hepatic toxicity with dose-volume factors of carbon ion radiotherapy in the liver. Forty-nine patients with hepatocellular carcinoma were treated with carbon ion radiotherapy delivered in 4 fractions over 4 to 7 days. Six patients received a total dose of 48 GyE and 43 received 52.8 GyE. The correlation of various blood biochemistry data with dose-volume histogram (DVH) data in non-cancerous liver were evaluated. The strongest significant correlation was seen between percent volume of non-cancerous liver with radiation dose more than 11 GyE (V 11 GyE ) and elevation of serum glutamic oxaloacetic transaminase (GOT) level as early adverse response after carbon ion beam radiation therapy (p=0.0003). In addition, significant correlation between DVH data and change of several other blood biochemistry data were also revealed in early phase. In late phase after carbon ion radiotherapy, the strongest significant correlation was seen between decrease of platelet count and V 26GyE (p=0.015). There was no significant correlation between other blood biochemistry data and DVH data in the late phase. It was suggested that dose-volume factors of carbon ion radiotherapy influenced only transient aggravation of liver function, which improved in the long term after irradiation. (author)

Comparative risk analysis

International Nuclear Information System (INIS)

Niehaus, F.

1988-01-01

In this paper, the risks of various energy systems are discussed considering severe accidents analysis, particularly the probabilistic safety analysis, and probabilistic safety criteria, and the applications of these criteria and analysis. The comparative risk analysis has demonstrated that the largest source of risk in every society is from daily small accidents. Nevertheless, we have to be more concerned about severe accidents. The comparative risk analysis of five different energy systems (coal, oil, gas, LWR and STEC (Solar)) for the public has shown that the main sources of risks are coal and oil. The latest comparative risk study of various energy has been conducted in the USA and has revealed that the number of victims from coal is 42 as many than victims from nuclear. A study for severe accidents from hydro-dams in United States has estimated the probability of dam failures at 1 in 10,000 years and the number of victims between 11,000 and 260,000. The average occupational risk from coal is one fatal accident in 1,000 workers/year. The probabilistic safety analysis is a method that can be used to assess nuclear energy risks, and to analyze the severe accidents, and to model all possible accident sequences and consequences. The 'Fault tree' analysis is used to know the probability of failure of the different systems at each point of accident sequences and to calculate the probability of risks. After calculating the probability of failure, the criteria for judging the numerical results have to be developed, that is the quantitative and qualitative goals. To achieve these goals, several systems have been devised by various countries members of AIEA. The probabilistic safety ana-lysis method has been developed by establishing a computer program permit-ting to know different categories of safety related information. 19 tabs. (author)

GPU accelerated edge-region based level set evolution constrained by 2D gray-scale histogram.

Science.gov (United States)

Balla-Arabé, Souleymane; Gao, Xinbo; Wang, Bin

2013-07-01

Due to its intrinsic nature which allows to easily handle complex shapes and topological changes, the level set method (LSM) has been widely used in image segmentation. Nevertheless, LSM is computationally expensive, which limits its applications in real-time systems. For this purpose, we propose a new level set algorithm, which uses simultaneously edge, region, and 2D histogram information in order to efficiently segment objects of interest in a given scene. The computational complexity of the proposed LSM is greatly reduced by using the highly parallelizable lattice Boltzmann method (LBM) with a body force to solve the level set equation (LSE). The body force is the link with image data and is defined from the proposed LSE. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. The new algorithm is effective, robust against noise, independent to the initial contour, fast, and highly parallelizable. The edge and region information enable to detect objects with and without edges, and the 2D histogram information enable the effectiveness of the method in a noisy environment. Experimental results on synthetic and real images demonstrate subjectively and objectively the performance of the proposed method.

Underwater image quality enhancement of sea cucumbers based on improved histogram equalization and wavelet transform

Directory of Open Access Journals (Sweden)

Xi Qiao

2017-09-01

Full Text Available Sea cucumbers usually live in an environment where lighting and visibility are generally not controllable, which cause the underwater image of sea cucumbers to be distorted, blurred, and severely attenuated. Therefore, the valuable information from such an image cannot be fully extracted for further processing. To solve the problems mentioned above and improve the quality of the underwater images of sea cucumbers, pre-processing of a sea cucumber image is attracting increasing interest. This paper presents a new method based on contrast limited adaptive histogram equalization and wavelet transform (CLAHE-WT to enhance the sea cucumber image quality. CLAHE was used to process the underwater image for increasing contrast based on the Rayleigh distribution, and WT was used for de-noising based on a soft threshold. Qualitative analysis indicated that the proposed method exhibited better performance in enhancing the quality and retaining the image details. For quantitative analysis, the test with 120 underwater images showed that for the proposed method, the mean square error (MSE, peak signal to noise ratio (PSNR, and entropy were 49.2098, 13.3909, and 6.6815, respectively. The proposed method outperformed three established methods in enhancing the visual quality of sea cucumber underwater gray image.

Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance

Science.gov (United States)

Helmer, K. G.; Chou, M-C.; Preciado, R. I.; Gimi, B.; Rollins, N. K.; Song, A.; Turner, J.; Mori, S.

2016-01-01

MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables. PMID:27350723

Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance.

Science.gov (United States)

Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S

2016-02-27

MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables.

Parameters of proteome evolution from histograms of amino-acid sequence identities of paralogous proteins

Directory of Open Access Journals (Sweden)

Yan Koon-Kiu

2007-11-01

KjabbwgaLjabbYgaSbqaaiabgEHiQaaaaaa@325B@ which include gene copies that will be removed soon after the duplication event and their dramatically reduced long-term counterparts rdup, rdel. High deletion rate among recently duplicated proteins is consistent with a scenario in which they didn't have enough time to significantly change their functional roles and thus are to a large degree disposable. Systematic trends of each of the four duplication/deletion rates with the total number of genes in the genome were analyzed. All but the deletion rate of recent duplicates rdel∗ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGacaGaaiaabeqaaeqabiWaaaGcbaGaemOCai3aa0baaSqaaiabbsgaKjabbwgaLjabbYgaSbqaaiabgEHiQaaaaaa@325B@ were shown to systematically increase with Ngenes. Abnormally flat shapes of sequence identity histograms observed for yeast and human are consistent with lineages leading to these organisms undergoing one or more whole-genome duplications. This interpretation is corroborated by our analysis of the genome of Paramecium tetraurelia where the p-4 profile of the histogram is gradually restored by the successive removal of paralogs generated in its four known whole-genome duplication events.

Comparing non-parametric methods for ungrouping coarsely aggregated age-specific distributions

DEFF Research Database (Denmark)

Rizzi, Silvia; Thinggaard, Mikael; Vaupel, James W.

2016-01-01

Demographers have often access to vital statistics that are less than ideal for the purpose of their research. In many instances demographic data are reported in coarse histograms, where the values given are only the summation of true latent values, thereby making detailed analysis troublesome. O...

Treatment and Combination of Data Quality Monitoring Histograms to Perform Data vs. Monte Carlo Validation

CERN Document Server

Colin, Nolan

2013-01-01

In CMS's automated data quality validation infrastructure, it is not currently possible to assess how well Monte Carlo simulations describe data from collisions, if at all. In order to guarantee high quality data, a novel work flow was devised to perform `data vs. Monte Carlo' validation. Support for this comparison was added by allowing distributions from several Monte Carlo samples to be combined, matched to the data and then displayed in a histogram stack, overlaid with the experimental data.

Off-line analysis of positron annihilation spectra. II. Defining crystal frame origin

International Nuclear Information System (INIS)

Adam, Gh.; Adam, S.

1997-01-01

This paper is devoted to the consistent definition of the origin Γ of the crystal frame (CF) of an n-axis-projected histogram (where n-vector denotes a principal crystallographic axis) obtained by the technique of the two dimensional angular correlation of positron-electron annihilation radiation (2D-ACAR). This is shown to need agreement with each other of two alternative definitions of Γ as center of symmetry and center of gravity of areas entering the signature of crystal symmetry (SCS) of the spectrum defined in a previous paper. This requirement singles out the projection of the first Brillouin zone onto the histogram plane as the area containing the information which is the least distorted by the instrumental artifacts. The derivation of Γ involves two steps described in Section 2 and 3, respectively. Consistency with each other of the obtained solutions provides a first family of validation tests. The CF validation is to be decided from the analysis of the artifact distribution in the Cf histogram. The histogram reformulation in the crystal frame is legitimate provided the Euler angle θ relating the crystal and laboratory frames is negligible . Among the criteria for the validation of the analysis of primary importance is the requirement of close agreement between the two alternative definitions of the zero-momentum projection of the momentum distribution onto the histogram plane. The histogram redefinition in the crystal frame results in specific discretization errors. To check there magnitude the SCS values are computed again and the derivation CF parameters repeated the convergence of this iterative refinement of the CF parameters offers a supplementary insight into the crystal-detector alignment and crystal quality. The described procedure is applied to three 2D-ACAR histograms

Dose-Volume Histogram Analysis of the Safety of Proton Beam Therapy for Unresectable Hepatocellular Carcinoma

International Nuclear Information System (INIS)

Kawashima, Mitsuhiko; Kohno, Ryosuke; Nakachi, Kohei; Nishio, Teiji; Mitsunaga, Shuichi; Ikeda, Masafumi; Konishi, Masaru; Takahashi, Shinichiro; Gotohda, Naoto; Arahira, Satoko; Zenda, Sadamoto; Ogino, Takashi; Kinoshita, Taira

2011-01-01

Purpose: To evaluate the safety and efficacy of radiotherapy using proton beam (PRT) for unresectable hepatocellular carcinoma. Methods and Materials: Sixty consecutive patients who underwent PRT between May 1999 and July 2007 were analyzed. There were 42 males and 18 females, with a median age of 70 years (48-92 years). All but 1 patient had a single lesion with a median diameter of 45 mm (20-100 mm). Total PRT dose/fractionation was 76-cobalt Gray equivalent (CGE)/20 fractions in 46 patients, 65 CGE/26 fractions in 11 patients, and 60 CGE/10 fractions in 3 patients. The risk of developing proton-induced hepatic insufficiency (PHI) was estimated using dose-volume histograms and an indocyanine-green retention rate at 15 minutes (ICG R15). Results: None of the 20 patients with ICG R15 of less than 20% developed PHI, whereas 6 of 8 patients with ICG R15 values of 50% or higher developed PHI. Among 32 patients whose ICG R15 ranged from 20% to 49.9%, PHI was observed only in patients who had received 30 CGE (V30) to more than 25% of the noncancerous parts of the liver (n = 5) Local progression-free and overall survival rates at 3 years were 90% (95% confidence interval [CI], 80-99%) and 56% (95% CI, 43-69%), respectively. A gastrointestinal toxicity of Grade ≥2 was observed in 3 patients. Conclusions: ICG R15 and V30 are recommended as useful predictors for the risk of developing PHI, which should be incorporated into multidisciplinary treatment plans for patients with this disease.

First impressions of 3D visual tools and dose volume histograms for plan evaluation

International Nuclear Information System (INIS)

Rattray, G.; Simitcioglu, A.; Parkinson, M.; Biggs, J.

1999-01-01

Converting from 2D to 3D treatment planning offers numerous challenges. The practices that have evolved in the 2D environment may not be applicable when translated into the 3D environment. One such practice is the methods used to evaluate a plan. In 2D planning a plane by plane comparison method is generally practiced. This type of evaluation method would not be appropriate for plans produced by a 3D planning system. To this end 3D dose displays and Dose Volume Histograms (DVHs) have been developed to facilitate the evaluation of such plans. A survey was conducted to determine the impressions of Radiation Therapists as they used these tools for the first time. The survey involved comparing a number of plans for a small group of patients and selecting the best plan for each patient. Three evaluation methods were assessed. These included the traditional plane by plane, 3D dose display, and DVHs. Those surveyed found the DVH to be the easiest of the three methods to use, with the 3D display being the next easiest. Copyright (1999) Blackwell Science Pty Ltd

Gastrointestinal Dose-Histogram Effects in the Context of Dose-Volume–Constrained Prostate Radiation Therapy: Analysis of Data From the RADAR Prostate Radiation Therapy Trial

Energy Technology Data Exchange (ETDEWEB)

Ebert, Martin A., E-mail: Martin.Ebert@health.wa.gov.au [Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia (Australia); School of Physics, University of Western Australia, Perth, Western Australia (Australia); Foo, Kerwyn [Sydney Medical School, University of Sydney, Sydney, New South Wales (Australia); Haworth, Annette [Department of Physical Sciences, Peter MacCallum Cancer Centre, East Melbourne, Victoria (Australia); Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria (Australia); Gulliford, Sarah L. [Joint Department of Physics, Institute of Cancer Research and Royal Marsden National Health Service Foundation Trust, Sutton, Surrey (United Kingdom); Kennedy, Angel [Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia (Australia); Joseph, David J. [Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia (Australia); School of Surgery, University of Western Australia, Perth, Western Australia (Australia); Denham, James W. [School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales (Australia)

2015-03-01

Purpose: To use a high-quality multicenter trial dataset to determine dose-volume effects for gastrointestinal (GI) toxicity following radiation therapy for prostate carcinoma. Influential dose-volume histogram regions were to be determined as functions of dose, anatomical location, toxicity, and clinical endpoint. Methods and Materials: Planning datasets for 754 participants in the TROG 03.04 RADAR trial were available, with Late Effects of Normal Tissues (LENT) Subjective, Objective, Management, and Analytic (SOMA) toxicity assessment to a median of 72 months. A rank sum method was used to define dose-volume cut-points as near-continuous functions of dose to 3 GI anatomical regions, together with a comprehensive assessment of significance. Univariate and multivariate ordinal regression was used to assess the importance of cut-points at each dose. Results: Dose ranges providing significant cut-points tended to be consistent with those showing significant univariate regression odds-ratios (representing the probability of a unitary increase in toxicity grade per percent relative volume). Ranges of significant cut-points for rectal bleeding validated previously published results. Separation of the lower GI anatomy into complete anorectum, rectum, and anal canal showed the impact of mid-low doses to the anal canal on urgency and tenesmus, completeness of evacuation and stool frequency, and mid-high doses to the anorectum on bleeding and stool frequency. Derived multivariate models emphasized the importance of the high-dose region of the anorectum and rectum for rectal bleeding and mid- to low-dose regions for diarrhea and urgency and tenesmus, and low-to-mid doses to the anal canal for stool frequency, diarrhea, evacuation, and bleeding. Conclusions: Results confirm anatomical dependence of specific GI toxicities. They provide an atlas summarizing dose-histogram effects and derived constraints as functions of anatomical region, dose, toxicity, and endpoint for

Gastrointestinal Dose-Histogram Effects in the Context of Dose-Volume–Constrained Prostate Radiation Therapy: Analysis of Data From the RADAR Prostate Radiation Therapy Trial

International Nuclear Information System (INIS)

Ebert, Martin A.; Foo, Kerwyn; Haworth, Annette; Gulliford, Sarah L.; Kennedy, Angel; Joseph, David J.; Denham, James W.

2015-01-01

Purpose: To use a high-quality multicenter trial dataset to determine dose-volume effects for gastrointestinal (GI) toxicity following radiation therapy for prostate carcinoma. Influential dose-volume histogram regions were to be determined as functions of dose, anatomical location, toxicity, and clinical endpoint. Methods and Materials: Planning datasets for 754 participants in the TROG 03.04 RADAR trial were available, with Late Effects of Normal Tissues (LENT) Subjective, Objective, Management, and Analytic (SOMA) toxicity assessment to a median of 72 months. A rank sum method was used to define dose-volume cut-points as near-continuous functions of dose to 3 GI anatomical regions, together with a comprehensive assessment of significance. Univariate and multivariate ordinal regression was used to assess the importance of cut-points at each dose. Results: Dose ranges providing significant cut-points tended to be consistent with those showing significant univariate regression odds-ratios (representing the probability of a unitary increase in toxicity grade per percent relative volume). Ranges of significant cut-points for rectal bleeding validated previously published results. Separation of the lower GI anatomy into complete anorectum, rectum, and anal canal showed the impact of mid-low doses to the anal canal on urgency and tenesmus, completeness of evacuation and stool frequency, and mid-high doses to the anorectum on bleeding and stool frequency. Derived multivariate models emphasized the importance of the high-dose region of the anorectum and rectum for rectal bleeding and mid- to low-dose regions for diarrhea and urgency and tenesmus, and low-to-mid doses to the anal canal for stool frequency, diarrhea, evacuation, and bleeding. Conclusions: Results confirm anatomical dependence of specific GI toxicities. They provide an atlas summarizing dose-histogram effects and derived constraints as functions of anatomical region, dose, toxicity, and endpoint for

Parallel-Sequential Texture Analysis

NARCIS (Netherlands)

van den Broek, Egon; Singh, Sameer; Singh, Maneesha; van Rikxoort, Eva M.; Apte, Chid; Perner, Petra

2005-01-01

Color induced texture analysis is explored, using two texture analysis techniques: the co-occurrence matrix and the color correlogram as well as color histograms. Several quantization schemes for six color spaces and the human-based 11 color quantization scheme have been applied. The VisTex texture

A statistic to estimate the variance of the histogram-based mutual information estimator based on dependent pairs of observations

NARCIS (Netherlands)

Moddemeijer, R

In the case of two signals with independent pairs of observations (x(n),y(n)) a statistic to estimate the variance of the histogram based mutual information estimator has been derived earlier. We present such a statistic for dependent pairs. To derive this statistic it is necessary to avail of a

Online: a program to display histograms and control monitor processes on the WA62 VAX data acquisition system at CERN

International Nuclear Information System (INIS)

Hand, R.P.

1981-02-01

ONLINE is a program which can be launched from any terminal on the WA62 experiment's DEC VAX 11/780 computer when the Native mode data acquisition system is running. It is used to display histograms produced by the various experiment monitor processes running under the system and can establish links with such processes to allow the user to issue monitor commands and change internal monitor process parameters. This report describes the criteria used in the design of ONLINE and shows some of the features of the VAX/VMS Operating System which are used to access histograms produced by monitor processes, to establish communications links with monitor processes and to provide the user with an easy to learn system for the examination of online experimental data in a graphical form. Also given, is a brief account of the way monitor processes are structured and how this structure facilitates user-monitor dialogue. (author)

Gender Perception From Faces Using Boosted LBPH (Local Binary Patten Histograms

Directory of Open Access Journals (Sweden)

U. U. Tariq

2013-06-01

Full Text Available Automatic Gender classification from faces has several applications such as surveillance, human computer interaction, targeted advertisement etc. Humans can recognize gender from faces quite accurately but for computer vision it is a difficult task. Many studies have targeted this problem but most of these studies used images of faces taken under constrained conditions. Real-world applications however require to process images from real-world, that have significant variation in lighting and pose, which makes the gender classification task very difficult. We have examined the problem of automatic gender classification from faces on real-world images. Using a face detector faces from images are extracted aligned and represented using Local binary pattern histogram. Discriminative features are selected using Adaboost and the boosted LBP features are used to train a support vector machine that provides a recognition rate of 93.29%.

REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION

Directory of Open Access Journals (Sweden)

D. Sathish Kumar

2013-05-01

Full Text Available Face recognition is one of the intensive areas of research in computer vision and pattern recognition but many of which are focused on recognition of faces under varying facial expressions and pose variation. A constrained optical flow algorithm discussed in this paper, recognizes facial images involving various expressions based on motion vector computation. In this paper, an optical flow computation algorithm which computes the frames of varying facial gestures, and integrating with synthesized image in a probabilistic environment has been proposed. Also Histogram Equalization technique has been used to overcome the effect of illuminations while capturing the input data using camera devices. It also enhances the contrast of the image for better processing. The experimental results confirm that the proposed face recognition system is more robust and recognizes the facial images under varying expressions and pose variations more accurately.

Analysis on Longitudinal Dose according to Change of Field Width

International Nuclear Information System (INIS)

Jung, Won Seok; Shin, Ryung Mi; Oh, Byung Cheon; Jo, Jun Young; Kim, Gi Chul; Choi, Tae Gu; Back, Jong Geal

2011-01-01

To analyze the accuracy of tumor volume dose following field width change, to check the difference of dose change by using self-made moving car, and to evaluate practical delivery tumor dose when tomotherapy in the treatment of organ influenced by breathing. By using self-made moving car, the difference of longitudinal movement (0.0 cm, 1.0 cm, 1.5 cm, 2.0 cm) was applied and compared calculated dose with measured dose according to change of field width (1.05 cm, 2.50 cm, 5.02 cm) and apprehended margin of error. Then done comparative analysis in degree of photosensitivity of DQA film measured by using Gafchromic EBT film. Dose profile and Gamma histogram were used to measure degree of photosensitivity of DQA film. When field width were 1.05 cm, 2.50 cm, 5.02 cm, margin of error of dose delivery coefficient was -2.00%, -0.39%, -2.55%. In dose profile of Gafchromic EBT film's analysis, the movement of moving car had greater motion toward longitudinal direction and as field width was narrower, big error increased considerably at high dose part compared to calculated dose. The more field width was narrowed, gamma index had a large considerable influence of moving at gamma histogram. We could check the difference of longitudinal dose of moving organ. In order to small field width and minimize organ moving due to breathing, it is thought to be needed to develop breathing control unit and fixation tool.

Prostate position variability and dose-volume histograms in radiotherapy for prostate cancer with full and empty bladder

International Nuclear Information System (INIS)

Pinkawa, Michael; Asadpour, Branka; Gagel, Bernd; Piroth, Marc D.; Holy, Richard; Eble, Michael J.

2006-01-01

Purpose: To evaluate prostate position variability and dose-volume histograms in prostate radiotherapy with full bladder (FB) and empty bladder (EB). Methods and Materials: Thirty patients underwent planning computed tomography scans in a supine position with FB and EB before and after 4 and 8 weeks of radiation therapy. The scans were matched by alignment of pelvic bones. Displacements of the prostate/seminal vesicle organ borders and center of mass were determined. Treatment plans (FB vs. EB) were compared. Results: Compared with the primary scan, FB volume varied more than EB volume (standard deviation, 106 cm 3 vs. 47 cm 3 ), but the prostate/seminal vesicle center of mass position variability was the same (>3 mm deviation in right-left, anterior-posterior, and superior-inferior directions in 0, 41%, and 33%, respectively, with FB vs. 0, 44%, and 33% with EB). The bladder volume treated with 90% of the prescription dose was significantly larger with EB (39% ± 14% vs. 22% ± 10%; p < 0.01). Bowel loops received ≥90% of prescription dose in 37% (3% with FB; p < 0.01). Conclusion: Despite the larger variability of bladder filling, prostate position stability was the same with FB compared with EB. An increased amount of bladder volume in the high-dose region and a higher dose to bowel loops result from treatment plans with EB

Histogram-driven cupping correction (HDCC) in CT

Science.gov (United States)

Kyriakou, Y.; Meyer, M.; Lapp, R.; Kalender, W. A.

2010-04-01

Typical cupping correction methods are pre-processing methods which require either pre-calibration measurements or simulations of standard objects to approximate and correct for beam hardening and scatter. Some of them require the knowledge of spectra, detector characteristics, etc. The aim of this work was to develop a practical histogram-driven cupping correction (HDCC) method to post-process the reconstructed images. We use a polynomial representation of the raw-data generated by forward projection of the reconstructed images; forward and backprojection are performed on graphics processing units (GPU). The coefficients of the polynomial are optimized using a simplex minimization of the joint entropy of the CT image and its gradient. The algorithm was evaluated using simulations and measurements of homogeneous and inhomogeneous phantoms. For the measurements a C-arm flat-detector CT (FD-CT) system with a 30×40 cm2 detector, a kilovoltage on board imager (radiation therapy simulator) and a micro-CT system were used. The algorithm reduced cupping artifacts both in simulations and measurements using a fourth-order polynomial and was in good agreement to the reference. The minimization algorithm required less than 70 iterations to adjust the coefficients only performing a linear combination of basis images, thus executing without time consuming operations. HDCC reduced cupping artifacts without the necessity of pre-calibration or other scan information enabling a retrospective improvement of CT image homogeneity. However, the method can work with other cupping correction algorithms or in a calibration manner, as well.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study

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Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias

2018-01-01

Abstract Objective To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) (“living” network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Design Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Data sources Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Eligibility criteria for study selection Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (Pmeta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. Results 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided strong evidence against the null hypothesis (P=0.002). The median time to strong evidence against the null hypothesis was 19 years with living network meta-analysis and 23 years with living pairwise meta-analysis (hazard ratio 2.78, 95% confidence interval 1.00 to 7.72, P=0.05). Studies directly comparing

Bleeding detection in wireless capsule endoscopy using adaptive colour histogram model and support vector classification

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Mackiewicz, Michal W.; Fisher, Mark; Jamieson, Crawford

2008-03-01

Wireless Capsule Endoscopy (WCE) is a colour imaging technology that enables detailed examination of the interior of the gastrointestinal tract. A typical WCE examination takes ~ 8 hours and captures ~ 40,000 useful images. After the examination, the images are viewed as a video sequence, which generally takes a clinician over an hour to analyse. The manufacturers of the WCE provide certain automatic image analysis functions e.g. Given Imaging offers in their Rapid Reader software: The Suspected Blood Indicator (SBI), which is designed to report the location in the video of areas of active bleeding. However, this tool has been reported to have insufficient specificity and sensitivity. Therefore it does not free the specialist from reviewing the entire footage and was suggested only to be used as a fast screening tool. In this paper we propose a method of bleeding detection that uses in its first stage Hue-Saturation-Intensity colour histograms to track a moving background and bleeding colour distributions over time. Such an approach addresses the problem caused by drastic changes in blood colour distribution that occur when it is altered by gastrointestinal fluids and allow detection of other red lesions, which although are usually "less red" than fresh bleeding, they can still be detected when the difference between their colour distributions and the background is large enough. In the second stage of our method, we analyse all candidate blood frames, by extracting colour (HSI) and texture (LBP) features from the suspicious image regions (obtained in the first stage) and their neighbourhoods and classifying them using Support Vector Classifier into Bleeding, Lesion and Normal classes. We show that our algorithm compares favourably with the SBI on the test set of 84 full length videos.

Cluster analysis of quantitative parametric maps from DCE-MRI: application in evaluating heterogeneity of tumor response to antiangiogenic treatment.

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Longo, Dario Livio; Dastrù, Walter; Consolino, Lorena; Espak, Miklos; Arigoni, Maddalena; Cavallo, Federica; Aime, Silvio

2015-07-01

The objective of this study was to compare a clustering approach to conventional analysis methods for assessing changes in pharmacokinetic parameters obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) during antiangiogenic treatment in a breast cancer model. BALB/c mice bearing established transplantable her2+ tumors were treated with a DNA-based antiangiogenic vaccine or with an empty plasmid (untreated group). DCE-MRI was carried out by administering a dose of 0.05 mmol/kg of Gadocoletic acid trisodium salt, a Gd-based blood pool contrast agent (CA) at 1T. Changes in pharmacokinetic estimates (K(trans) and vp) in a nine-day interval were compared between treated and untreated groups on a voxel-by-voxel analysis. The tumor response to therapy was assessed by a clustering approach and compared with conventional summary statistics, with sub-regions analysis and with histogram analysis. Both the K(trans) and vp estimates, following blood-pool CA injection, showed marked and spatial heterogeneous changes with antiangiogenic treatment. Averaged values for the whole tumor region, as well as from the rim/core sub-regions analysis were unable to assess the antiangiogenic response. Histogram analysis resulted in significant changes only in the vp estimates (pclustering approach depicted marked changes in both the K(trans) and vp estimates, with significant spatial heterogeneity in vp maps in response to treatment (pclustered in three or four sub-regions. This study demonstrated the value of cluster analysis applied to pharmacokinetic DCE-MRI parametric maps for assessing tumor response to antiangiogenic therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation and comparison of signal to noise ratio according to histogram equalization of heart shadow on chest image

International Nuclear Information System (INIS)

Kim, Ki Won; Lee, Eul Kyu; Jeong, Hoi Woun; Kang, Byung Sam; Kim, Hyun Soo; Min, Jung Whan; Son, Jin Hyun

2017-01-01

The purpose of this study was to measure signal to noise ratio (SNR) according to change of equalization from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 87 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using Image. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p < 0.05). In SNR results, with the quality of distributions in the order of original chest image, original chest image heart shadow and equalization chest image, equalization chest image heart shadow(p < 0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the histogram equalization chest image

Evaluation and comparison of signal to noise ratio according to histogram equalization of heart shadow on chest image

Energy Technology Data Exchange (ETDEWEB)

Kim, Ki Won [Dept. of Radiology, Kyung Hee University Hospital at Gang-dong, Seoul (Korea, Republic of); Lee, Eul Kyu [Inje Paik University Hospital at Jeo-dong, Seoul (Korea, Republic of); Jeong, Hoi Woun [The Baekseok Culture University, Cheonan (Korea, Republic of); Kang, Byung Sam; Kim, Hyun Soo; Min, Jung Whan; Son, Jin Hyun [The Shingu University, Seongnam (Korea, Republic of)

2017-06-15

The purpose of this study was to measure signal to noise ratio (SNR) according to change of equalization from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 87 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using Image. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p < 0.05). In SNR results, with the quality of distributions in the order of original chest image, original chest image heart shadow and equalization chest image, equalization chest image heart shadow(p < 0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the histogram equalization chest image.

SUPERVISED AUTOMATIC HISTOGRAM CLUSTERING AND WATERSHED SEGMENTATION. APPLICATION TO MICROSCOPIC MEDICAL COLOR IMAGES

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Olivier Lezoray

2011-05-01

Full Text Available In this paper, an approach to the segmentation of microscopic color images is addressed, and applied to medical images. The approach combines a clustering method and a region growing method. Each color plane is segmented independently relying on a watershed based clustering of the plane histogram. The marginal segmentation maps intersect in a label concordance map. The latter map is simplified based on the assumption that the color planes are correlated. This produces a simplified label concordance map containing labeled and unlabeled pixels. The formers are used as an image of seeds for a color watershed. This fast and robust segmentation scheme is applied to several types of medical images.

The analysis of correlation between changes of myocardial enzymes level in serum before and after radiation and dose-volume histogram parameters of the heart

International Nuclear Information System (INIS)

Ding Xiuping; Li Hongjun; Li Baosheng; Wang Dongqing

2012-01-01

Objective: To analyze the correlation between the changes of myocardial enzyme level in serum before and after radiotherapy and dose - volume histogram (DVH) parameters of the heart. Methods: A total of 102 patients with 68 cases of lung cancer and 34 cases of esophageal cancer were recruited. All patients received three-dimensional conformal radiotherapy (3DCRT) or intensity-modulated radiotherapy (IMRT), with the radiation beams passing through the heart. Aspartate aminotransferase (AST), creatine kinase (CK), creatine kinase isozyme (CK-MB), lactate dehydrogenase (LDH), α-hydroxybutyrate dehydrogenase (α-HBDH) were determined in the serum before and after radiotherapy. All the enzyme levels before and after radiotherapy were compared through paired t-test. Independent sample t-test was conducted between sub-groups. And the dose-volume histogram (DVH) parameters of the heart were calculated (the volume percentage of heart receiving dose equal to or exceeding x Gy (V x ). The correlation between myocardial enzyme level and DVH parameters was analyzed through Pearson method. Results: Serum AST, CK-MB, LDH, α-HBDH levels increased significantly after radiotherapy (19.42: 27.89, 14.72:19.57, 178.80 : 217.57, 140.32 : 176.25, t =-3.39 - -6.92, all P=0.000). In Group IMRT, significant correlations between the increase of myocardial enzyme concentration and DVH parameters of the heart are found, AST with V 20 , V 25 , V 30 of heart ( r=0.302 - 0.431, P =0.039 - 0.003), CK with V 30 of heart (r=0.345, P=0.013), and CK-MB, LDH, α-HBDH with V 25 , V 30 (r=0.465 -0.376, P=0.001-0.005). In Group CRT, there are significant correlations between changes of CK-MB, LDH level and V 30 of heart (r =0.330, 0.274, P=0.014, 0.033), α-HBDH and V 25 , V 30 , and V 35 of heart (r=0.270-0.331, P=0.046-0.014). When the irradiation dose was more than 50 Gy, significant correlations were found between the concentration changes of AST, LDH, α-HBDH and V 25 , V 30 of heart (r=0

Serial quantitative CT evaluation for patients with idiopathic pulmonary fibrosis (IPF) using Gaussian Histogram Normalized Correlation (GHNC)

International Nuclear Information System (INIS)

Iwasawa, Tae; Ogura, Takashi; Nishimura, Junichi; Asakura, Akira; Gotoh, Toshiyuki; Yazawa, Takuya; Inoue, Tomio

2006-01-01

We assessed serial changes in high-resolution CT findings quantitatively using originally developed software Gaussian Histogram Normalized Correlation (GHNC) in 15 patients with idiopathic pulmonary fibrosis (IPF). Mean follow-up period was 1.4 years. The volume of honeycombing increased with 0.8±0.9%TLC (predicted Total lung capacity) per year, the normal lung volume reduced by 4.1±7.3%TLC per year. GHNC is useful for the quantitative evaluation. (author)

Histogram-based ionogram displays and their application to autoscaling

Science.gov (United States)

Lynn, Kenneth J. W.

2018-03-01

A simple method is described for displaying and auto scaling the basic ionogram parameters foF2 and h'F2 as well as some additional layer parameters from digital ionograms. The technique employed is based on forming frequency and height histograms in each ionogram. This technique has now been applied specifically to ionograms produced by the IPS5D ionosonde developed and operated by the Australian Space Weather Service (SWS). The SWS ionograms are archived in a cleaned format and readily available from the SWS internet site. However, the method is applicable to any ionosonde which produces ionograms in a digital format at a useful signal-to-noise level. The most novel feature of the technique for autoscaling is its simplicity and the avoidance of the mathematical imaging and line fitting techniques often used. The program arose from the necessity to display many days of ionogram output to allow the location of specific types of ionospheric event such as ionospheric storms, travelling ionospheric disturbances and repetitive ionospheric height changes for further investigation and measurement. Examples and applications of the method are given including the removal of sporadic E and spread F.

Modular routing interface for simoultaneous list mode and histogramming mode storage of coincident data

International Nuclear Information System (INIS)

D'Achard van Eschut, J.F.M.; Nationaal Inst. voor Kernfysica en Hoge-Energiefysica

1985-01-01

A routing interface has been developed and built for successive storage of the digital output of four 13-bit ADCs, within 6 μs, into selected parts of two 16K CAMAC histogramming modules and, if an event trigger is applied, simultaneously into four 64-words deep (16-bit) first-in first-out (FIFO) CAMAC modules. In this way it is possible to accumulate on-line single spectra and, at the same time, write coincident data in list mode to magnetic tape under control of a computer. Additional routing interfaces can be used in parallel so that extensive data-collecting systems can be set up to store multi-parameter events. (orig.)

Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms

International Nuclear Information System (INIS)

Conson, Manuel; Cella, Laura; Pacelli, Roberto; Comerci, Marco; Liuzzi, Raffaele; Salvatore, Marco; Quarantelli, Mario

2014-01-01

Purpose: To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). Patients and methods: 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient – DSC). Dosimetric parameters from dose–volume-histograms were also generated and compared. Results: Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSC ABAS = 1 (95% CI, 0.97–1.0) vs. DSC MANUAL = 0.90 (0.73–0.98)], acceptable accuracy [DSC ABAS = 0.81 (0.68–0.94) vs. DSC MANUAL = 0.90 (0.76–0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. Conclusions: The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose–volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures

Landmark Detection in Orbital Images Using Salience Histograms

Science.gov (United States)

Wagstaff, Kiri L.; Panetta, Julian; Schorghofer, Norbert; Greeley, Ronald; PendletonHoffer, Mary; bunte, Melissa

2010-01-01

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Properties of the histogram location approach and the extent and change of downward nominal wage rigidity in the EU

Directory of Open Access Journals (Sweden)

Andreas Behr

2006-06-01

Full Text Available The histogram location approach has been proposed by Kahn (1997 to estimate the fraction of wage cuts prevented by downward nominal wage rigidity. In this paper, we analyze the validity of the approach by means of a simulation study which yielded evidence of unbiasedness but also of potential underestimation of rigidity parameter uncertainty and therefore of potential anticonservative inference. We apply the histogram location approach to estimate the extent of downward nominal wage rigidity across the EU for 1995-2001. Our data base is the User Data Base (UDB of the European Community Household Panel (ECHP. The results show wide variation in the fraction of wage cuts prevented by nominal wage rigidity across the EU. The lowest rigidity parameters are found for the UK, Spain and Ireland, the largest for Portugal and Italy. Analyzing the change of rigidity between sub periods 1995-1997 and 1999-2001 even shows an widening of the differences in nominal wage rigidity. Due to the finding of large differences across the EU, the results imply that the costs of low inflation policies across the EU differ substantially.

Correlation of 18F-FDG PET and MRI Apparent Diffusion Coefficient Histogram Metrics with Survival in Diffuse Intrinsic Pontine Glioma: A Report from the Pediatric Brain Tumor Consortium.

Science.gov (United States)

Zukotynski, Katherine A; Vajapeyam, Sridhar; Fahey, Frederic H; Kocak, Mehmet; Brown, Douglas; Ricci, Kelsey I; Onar-Thomas, Arzu; Fouladi, Maryam; Poussaint, Tina Young

2017-08-01

The purpose of this study was to describe baseline 18 F-FDG PET voxel characteristics in pediatric diffuse intrinsic pontine glioma (DIPG) and to correlate these metrics with baseline MRI apparent diffusion coefficient (ADC) histogram metrics, progression-free survival (PFS), and overall survival. Methods: Baseline brain 18 F-FDG PET and MRI scans were obtained in 33 children from Pediatric Brain Tumor Consortium clinical DIPG trials. 18 F-FDG PET images, postgadolinium MR images, and ADC MR images were registered to baseline fluid attenuation inversion recovery MR images. Three-dimensional regions of interest on fluid attenuation inversion recovery MR images and postgadolinium MR images and 18 F-FDG PET and MR ADC histograms were generated. Metrics evaluated included peak number, skewness, and kurtosis. Correlation between PET and MR ADC histogram metrics was evaluated. PET pixel values within the region of interest for each tumor were plotted against MR ADC values. The association of these imaging markers with survival was described. Results: PET histograms were almost always unimodal (94%, vs. 6% bimodal). None of the PET histogram parameters (skewness or kurtosis) had a significant association with PFS, although a higher PET postgadolinium skewness tended toward a less favorable PFS (hazard ratio, 3.48; 95% confidence interval [CI], 0.75-16.28 [ P = 0.11]). There was a significant association between higher MR ADC postgadolinium skewness and shorter PFS (hazard ratio, 2.56; 95% CI, 1.11-5.91 [ P = 0.028]), and there was the suggestion that this also led to shorter overall survival (hazard ratio, 2.18; 95% CI, 0.95-5.04 [ P = 0.067]). Higher MR ADC postgadolinium kurtosis tended toward shorter PFS (hazard ratio, 1.30; 95% CI, 0.98-1.74 [ P = 0.073]). PET and MR ADC pixel values were negatively correlated using the Pearson correlation coefficient. Further, the level of PET and MR ADC correlation was significantly positively associated with PFS; tumors with higher

Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

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Inhye Yoon

2015-03-01

Full Text Available Since incoming light to an unmanned aerial vehicle (UAV platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i image segmentation based on geometric classes; (ii generation of the context-adaptive transmission map; and (iii intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

Science.gov (United States)

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-03-19

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

Elucidating the effects of adsorbent flexibility on fluid adsorption using simple models and flat-histogram sampling methods

International Nuclear Information System (INIS)

Shen, Vincent K.; Siderius, Daniel W.

2014-01-01

Using flat-histogram Monte Carlo methods, we investigate the adsorptive behavior of the square-well fluid in two simple slit-pore-like models intended to capture fundamental characteristics of flexible adsorbent materials. Both models require as input thermodynamic information about the flexible adsorbent material itself. An important component of this work involves formulating the flexible pore models in the appropriate thermodynamic (statistical mechanical) ensembles, namely, the osmotic ensemble and a variant of the grand-canonical ensemble. Two-dimensional probability distributions, which are calculated using flat-histogram methods, provide the information necessary to determine adsorption thermodynamics. For example, we are able to determine precisely adsorption isotherms, (equilibrium) phase transition conditions, limits of stability, and free energies for a number of different flexible adsorbent materials, distinguishable as different inputs into the models. While the models used in this work are relatively simple from a geometric perspective, they yield non-trivial adsorptive behavior, including adsorption-desorption hysteresis solely due to material flexibility and so-called “breathing” of the adsorbent. The observed effects can in turn be tied to the inherent properties of the bare adsorbent. Some of the effects are expected on physical grounds while others arise from a subtle balance of thermodynamic and mechanical driving forces. In addition, the computational strategy presented here can be easily applied to more complex models for flexible adsorbents

Comparative analysis of human and bovine teeth: radiographic density

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Jefferson Luis Oshiro Tanaka

2008-12-01

Full Text Available Since bovine teeth have been used as substitutes for human teeth in in vitro dental studies, the aim of this study was to compare the radiographic density of bovine teeth with that of human teeth to evaluate their usability for radiographic studies. Thirty bovine and twenty human teeth were cut transversally in 1 millimeter-thick slices. The slices were X-rayed using a digital radiographic system and an intraoral X-ray machine at 65 kVp and 7 mA. The exposure time (0.08 s and the target-sensor distance (40 cm were standardized for all the radiographs. The radiographic densities of the enamel, coronal dentin and radicular dentin of each slice were obtained separately using the "histogram" tool of Adobe Photoshop 7.0 software. The mean radiographic densities of the enamel, coronal dentin and radicular dentin were calculated by the arithmetic mean of the slices of each tooth. One-way ANOVA demonstrated statistically significant differences for the densities of bovine and human enamel (p 0.05. Based on the results, the authors concluded that: a the radiographic density of bovine enamel is significantly higher than that of human enamel; b the radiodensity of bovine coronal dentin is statistically lower than the radiodensity of human coronal dentin; bovine radicular dentin is also less radiodense than human radicular dentin, although this difference was not statistically significant; c bovine teeth should be used with care in radiographic in vitro studies.

MO-FG-202-06: Improving the Performance of Gamma Analysis QA with Radiomics- Based Image Analysis

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Wootton, L; Nyflot, M; Ford, E [University of Washington Department of Radiation Oncology, Seattle, WA (United States); Chaovalitwongse, A [University of Washington Department of Industrial and Systems Engineering, Seattle, Washington (United States); University of Washington Department of Radiology, Seattle, WA (United States); Li, N [University of Washington Department of Industrial and Systems Engineering, Seattle, Washington (United States)

2016-06-15

Purpose: The use of gamma analysis for IMRT quality assurance has well-known limitations. Traditionally, a simple thresholding technique is used to evaluated passing criteria. However, like any image the gamma distribution is rich in information which thresholding mostly discards. We therefore propose a novel method of analyzing gamma images that uses quantitative image features borrowed from radiomics, with the goal of improving error detection. Methods: 368 gamma images were generated from 184 clinical IMRT beams. For each beam the dose to a phantom was measured with EPID dosimetry and compared to the TPS dose calculated with and without normally distributed (2mm sigma) errors in MLC positions. The magnitude of 17 intensity histogram and size-zone radiomic features were derived from each image. The features that differed most significantly between image sets were determined with ROC analysis. A linear machine-learning model was trained on these features to classify images as with or without errors on 180 gamma images.The model was then applied to an independent validation set of 188 additional gamma distributions, half with and half without errors. Results: The most significant features for detecting errors were histogram kurtosis (p=0.007) and three size-zone metrics (p<1e-6 for each). The sizezone metrics detected clusters of high gamma-value pixels under mispositioned MLCs. The model applied to the validation set had an AUC of 0.8, compared to 0.56 for traditional gamma analysis with the decision threshold restricted to 98% or less. Conclusion: A radiomics-based image analysis method was developed that is more effective in detecting error than traditional gamma analysis. Though the pilot study here considers only MLC position errors, radiomics-based methods for other error types are being developed, which may provide better error detection and useful information on the source of detected errors. This work was partially supported by a grant from the Agency for

Dose-volume histogram analysis for risk factors of radiation-induced rib fracture after hypofractionated proton beam therapy for hepatocellular carcinoma

International Nuclear Information System (INIS)

Kanemoto, Ayae

2013-01-01

Background: Radiation-induced rib fracture has been reported as a late complication after external radiotherapy to the chest. The purpose of this study was to clarify the characteristics and risk factors of rib fracture after hypofractionated proton beam therapy (PBT). Material and methods: The retrospective study comprised 67 patients with hepatocellular carcinoma who were treated using PBT of 66 Cobalt-Gray-equivalents [Gy (RBE)] in 10 fractions. We analyzed the patients' characteristics and determined dose-volume histograms (DVHs) for the irradiated ribs, and then estimated relationships between risk of fracture and several dose-volume parameters. An irradiated rib was defined to be any rib included in the area irradiated by PBT as determined by treatment-planning computed tomography. Results. Among the 67 patients, a total of 310 ribs were identified as irradiated ribs. Twenty-seven (8.7%) of the irradiated ribs developed fractures in 11 patients (16.4%). No significant relationships were seen between incidence of fracture and characteristics of patients, including sex, age, tumor size, tumor site, and follow-up period (p ≥ 0.05). The results of receiver operating characteristic curve analysis using DVH parameters demonstrated that the largest area under the curve (AUC) was observed for the volume of rib receiving a biologically effective dose of more than 60 Gy 3 (RBE) (V60) [The equivalent dose in 2 Gy fractions (EQD2); 36 Gy 3 ] and the AUCs of V30 to V120 (EQD2; 18-72 Gy 3 ) and D max to D 1 0 cm 3 were similar to that of V60. No significant relationships were seen for DVH parameters and intervals from PBT to incidence of fracture. Conclusion. DVH parameters are useful in predicting late adverse events of rib irradiation. This study identified that V60 was a most statistically significant parameter, and V30 to V120 and D max to D 1 0 cm 3 were also significant and clinically useful for estimating the risk of rib fracture after hypofractionated PBT

Dose-volume histogram analysis for risk factors of radiation-induced rib fracture after hypofractionated proton beam therapy for hepatocellular carcinoma

Energy Technology Data Exchange (ETDEWEB)

Kanemoto, Ayae [Proton Medical Research Center and Dept. of Radiation Oncology, Univ. of Tsukuba, Ibaraki (Japan)], e-mail: ayaek@pmrc.tsukuba.ac.jp [and others

2013-04-15

Background: Radiation-induced rib fracture has been reported as a late complication after external radiotherapy to the chest. The purpose of this study was to clarify the characteristics and risk factors of rib fracture after hypofractionated proton beam therapy (PBT). Material and methods: The retrospective study comprised 67 patients with hepatocellular carcinoma who were treated using PBT of 66 Cobalt-Gray-equivalents [Gy (RBE)] in 10 fractions. We analyzed the patients' characteristics and determined dose-volume histograms (DVHs) for the irradiated ribs, and then estimated relationships between risk of fracture and several dose-volume parameters. An irradiated rib was defined to be any rib included in the area irradiated by PBT as determined by treatment-planning computed tomography. Results. Among the 67 patients, a total of 310 ribs were identified as irradiated ribs. Twenty-seven (8.7%) of the irradiated ribs developed fractures in 11 patients (16.4%). No significant relationships were seen between incidence of fracture and characteristics of patients, including sex, age, tumor size, tumor site, and follow-up period (p {>=} 0.05). The results of receiver operating characteristic curve analysis using DVH parameters demonstrated that the largest area under the curve (AUC) was observed for the volume of rib receiving a biologically effective dose of more than 60 Gy{sub 3} (RBE) (V60) [The equivalent dose in 2 Gy fractions (EQD2); 36 Gy{sub 3}] and the AUCs of V30 to V120 (EQD2; 18-72 Gy{sub 3}) and D{sub max} to D{sub 1}0{sub cm}{sup 3} were similar to that of V60. No significant relationships were seen for DVH parameters and intervals from PBT to incidence of fracture. Conclusion. DVH parameters are useful in predicting late adverse events of rib irradiation. This study identified that V60 was a most statistically significant parameter, and V30 to V120 and D{sub max} to D{sub 1}0{sub cm}{sup 3} were also significant and clinically useful for estimating

A powerful, low-cost histogramming memory for digital radiography with multi-wire proportional counters

International Nuclear Information System (INIS)

Bateman, J.E.; Locke, C.E.R.; Ferrari, C.A.

1986-01-01

A powerful, low-cost histogramming memory for digital radiograph with multi-wire proportional counter is described. The memory is based on a commercial video display device coupled to an Apple II microcomputer which, at a total cost of around 2500 pounds gives a system with 512 x 512 pixel resolution and a counting range of 4095 counts per pixel. The system can take data at rates of up to 5000 Hz while providing a live-time display. No hardware modifications are necessary, the comprehensive storage and display facilities being implemented in a combined package of BASIC and ASSEMBLER software. An ACCELERATOR coprocessor card is used to enhance the performance of the system. (author)

Classification of amyloid status using machine learning with histograms of oriented 3D gradients

Directory of Open Access Journals (Sweden)

Liam Cattell

2016-01-01

Full Text Available Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using standardised uptake value ratios. Using these ratios as an adjunct to visual image assessment has been shown to improve inter-reader reliability, however, the amyloid positivity threshold is dependent on the tracer and specific image regions used to calculate the uptake ratio. To address this problem, we propose a machine learning approach to amyloid status classification, which is independent of tracer and does not require a specific set of regions of interest. Our method extracts feature vectors from amyloid images, which are based on histograms of oriented three-dimensional gradients. We optimised our method on 133 18F-florbetapir brain volumes, and applied it to a separate test set of 131 volumes. Using the same parameter settings, we then applied our method to 209 11C-PiB images and 128 18F-florbetaben images. We compared our method to classification results achieved using two other methods: standardised uptake value ratios and a machine learning method based on voxel intensities. Our method resulted in the largest mean distances between the subjects and the classification boundary, suggesting that it is less likely to make low-confidence classification decisions. Moreover, our method obtained the highest classification accuracy for all three tracers, and consistently achieved above 96% accuracy.

Efficiency of quantitative echogenicity for investigating supraspinatus tendinopathy by the gray-level histogram of two ultrasound devices.

Science.gov (United States)

Hsu, Jiun-Cheng; Chen, Po-Han; Huang, Kuo-Chin; Tsai, Yao-Hung; Hsu, Wei-Hsiu

2017-10-01

The gray-level histogram of ultrasound is a promising tool for scanning the hypoechogenic appearance of supraspinatus tendinopathy, and the aim of this study was to test the hypothesis that the gray-level value of the supraspinatus tendon in the painful shoulder has a lower value on B-mode images even though in different ultrasound devices. Sixty-seven patients who had unilateral shoulder pain with rotator cuff tendinopathy underwent bilateral shoulder ultrasonography, and we compared the mean gray-level values of painful shoulders and contralateral shoulders without any pain in each patient using two ultrasound devices. The echogenicity ratio (symptomatic/asymptomatic side) of two ultrasound devices was compared. A significant difference existed between the symptomatic shoulder and contralateral asymptomatic shoulder (p level value measurements of each device. The symptomatic-to-asymptomatic tendon echogenicity ratio of device A was 0.919 ± 0.090 in the transverse plane and 0.937 ± 0.081 in the longitudinal plane, and the echogenicity ratio of device B was 0.899 ± 0.113 in the transverse plane and 0.940 ± 0.113 in the longitudinal plane. The decline of the mean gray-level value and the echogenicity ratio of the supraspinatus tendon in the painful shoulder may be utilized as a useful sonographic reference of unilateral rotator cuff lesions. Diagnostic level III.

Living network meta-analysis compared with pairwise meta-analysis in comparative effectiveness research: empirical study.

Science.gov (United States)

Nikolakopoulou, Adriani; Mavridis, Dimitris; Furukawa, Toshi A; Cipriani, Andrea; Tricco, Andrea C; Straus, Sharon E; Siontis, George C M; Egger, Matthias; Salanti, Georgia

2018-02-28

To examine whether the continuous updating of networks of prospectively planned randomised controlled trials (RCTs) ("living" network meta-analysis) provides strong evidence against the null hypothesis in comparative effectiveness of medical interventions earlier than the updating of conventional, pairwise meta-analysis. Empirical study of the accumulating evidence about the comparative effectiveness of clinical interventions. Database of network meta-analyses of RCTs identified through searches of Medline, Embase, and the Cochrane Database of Systematic Reviews until 14 April 2015. Network meta-analyses published after January 2012 that compared at least five treatments and included at least 20 RCTs. Clinical experts were asked to identify in each network the treatment comparison of greatest clinical interest. Comparisons were excluded for which direct and indirect evidence disagreed, based on side, or node, splitting test (Pmeta-analyses were performed for each selected comparison. Monitoring boundaries of statistical significance were constructed and the evidence against the null hypothesis was considered to be strong when the monitoring boundaries were crossed. A significance level was defined as α=5%, power of 90% (β=10%), and an anticipated treatment effect to detect equal to the final estimate from the network meta-analysis. The frequency and time to strong evidence was compared against the null hypothesis between pairwise and network meta-analyses. 49 comparisons of interest from 44 networks were included; most (n=39, 80%) were between active drugs, mainly from the specialties of cardiology, endocrinology, psychiatry, and rheumatology. 29 comparisons were informed by both direct and indirect evidence (59%), 13 by indirect evidence (27%), and 7 by direct evidence (14%). Both network and pairwise meta-analysis provided strong evidence against the null hypothesis for seven comparisons, but for an additional 10 comparisons only network meta-analysis provided

Modeling the dark current histogram induced by gold contamination in complementary-metal-oxide-semiconductor image sensors

Energy Technology Data Exchange (ETDEWEB)

Domengie, F., E-mail: florian.domengie@st.com; Morin, P. [STMicroelectronics Crolles 2 (SAS), 850 Rue Jean Monnet, 38926 Crolles Cedex (France); Bauza, D. [CNRS, IMEP-LAHC - Grenoble INP, Minatec: 3, rue Parvis Louis Néel, CS 50257, 38016 Grenoble Cedex 1 (France)

2015-07-14

We propose a model for dark current induced by metallic contamination in a CMOS image sensor. Based on Shockley-Read-Hall kinetics, the expression of dark current proposed accounts for the electric field enhanced emission factor due to the Poole-Frenkel barrier lowering and phonon-assisted tunneling mechanisms. To that aim, we considered the distribution of the electric field magnitude and metal atoms in the depth of the pixel. Poisson statistics were used to estimate the random distribution of metal atoms in each pixel for a given contamination dose. Then, we performed a Monte-Carlo-based simulation for each pixel to set the number of metal atoms the pixel contained and the enhancement factor each atom underwent, and obtained a histogram of the number of pixels versus dark current for the full sensor. Excellent agreement with the dark current histogram measured on an ion-implanted gold-contaminated imager has been achieved, in particular, for the description of the distribution tails due to the pixel regions in which the contaminant atoms undergo a large electric field. The agreement remains very good when increasing the temperature by 15 °C. We demonstrated that the amplification of the dark current generated for the typical electric fields encountered in the CMOS image sensors, which depends on the nature of the metal contaminant, may become very large at high electric field. The electron and hole emissions and the resulting enhancement factor are described as a function of the trap characteristics, electric field, and temperature.

Quantitative CT analysis of pulmonary pure ground-glass nodule predicts histological invasiveness

Energy Technology Data Exchange (ETDEWEB)

Li, Qiong, E-mail: liqiongsmmu2008@qq.com [Department of Radiology, Changzheng Hospital, Second Military Medical University, NO. 415, Fengyang Road, Shanghai 200003 (China); Fan, Li, E-mail: fanli0930@163.com [Department of Radiology, Changzheng Hospital, Second Military Medical University, NO. 415, Fengyang Road, Shanghai 200003 (China); Cao, En-Tao, E-mail: cet123cs@126.com [Department of Radiology, Suzhou Municipal Hospital (East District), No.16 West Baita Road, Suzhu, Jiangsu Province 215001 (China); Li, Qing-Chu, E-mail: Wudi327@hotmail.com [Department of Radiology, Changzheng Hospital, Second Military Medical University, NO. 415, Fengyang Road, Shanghai 200003 (China); Gu, Ya-Feng, E-mail: 2528473557@qq.com [Department of Radiology, Changzheng Hospital, Second Military Medical University, NO. 415, Fengyang Road, Shanghai 200003 (China); Liu, Shi−Yuan, E-mail: liusy1186@163.com [Department of Radiology, Changzheng Hospital, Second Military Medical University, NO. 415, Fengyang Road, Shanghai 200003 (China)

2017-04-15

Objective: To assess whether quantitative computed tomography (CT) can help predict histological invasiveness of pulmonary adenocarcinoma appearing as pure ground glass nodules (pGGNs). Methods: A total of 110 pulmonary pGGNs were retrospectively evaluated, and pathologically classified as pre-invasive lesions, minimally invasive adenocarcinoma (MIA) and invasive pulmonary adenocarcinoma (IPA). Maximum nodule diameters, largest cross-sectional areas, volumes, mean CT values, weights, and CT attenuation values at the 0th,2th,5th, 25th, 50th,75th, 95th, 98th and100th percentiles on histogram, as well as 2th to 98th, 5th to 95th, 25th to 75th,and 0th to 100thslopes, respectively, were compared among the three groups. Results: Of the 110 pGGNs, 50, 28, and 32 were pre-invasive lesions, MIA, and IPA, respectively. Maximum nodule diameters, largest cross-sectional areas, andmass weights were significantly larger in the IPA group than in pre-invasive lesions. The 95th, 98th, 100th percentiles, and 2th to 98th, 25th to 75th, and 0th to 100thslopes were significantly different between pre-invasive lesions and MIA or IPA. Logistic regression analysis showed that the maximum nodule diameter (OR = 1.21, 95%CI: 1.071–1.366, p < 0.01) and 100th percentile on histogram (OR = 1.02, 95%CI: 1.009–1.032, p < 0.001) independently predicted histological invasiveness. Conclusions: Quantitative analysis of CT imaging can predict histological invasiveness of pGGNs, especiallythe maximum nodule diameter and 100th percentile on CT number histogram; this can instruct the long-term follow-up and selective surgical management.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

Science.gov (United States)

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

Science.gov (United States)

Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multicenter study of quantitative computed tomography analysis using a computer-aided three-dimensional system in patients with idiopathic pulmonary fibrosis.

Science.gov (United States)

Iwasawa, Tae; Kanauchi, Tetsu; Hoshi, Toshiko; Ogura, Takashi; Baba, Tomohisa; Gotoh, Toshiyuki; Oba, Mari S

2016-01-01

To evaluate the feasibility of automated quantitative analysis with a three-dimensional (3D) computer-aided system (i.e., Gaussian histogram normalized correlation, GHNC) of computed tomography (CT) images from different scanners. Each institution's review board approved the research protocol. Informed patient consent was not required. The participants in this multicenter prospective study were 80 patients (65 men, 15 women) with idiopathic pulmonary fibrosis. Their mean age was 70.6 years. Computed tomography (CT) images were obtained by four different scanners set at different exposures. We measured the extent of fibrosis using GHNC, and used Pearson's correlation analysis, Bland-Altman plots, and kappa analysis to directly compare the GHNC results with manual scoring by radiologists. Multiple linear regression analysis was performed to determine the association between the CT data and forced vital capacity (FVC). For each scanner, the extent of fibrosis as determined by GHNC was significantly correlated with the radiologists' score. In multivariate analysis, the extent of fibrosis as determined by GHNC was significantly correlated with FVC (p < 0.001). There was no significant difference between the results obtained using different CT scanners. Gaussian histogram normalized correlation was feasible, irrespective of the type of CT scanner used.

MycoCAP - Mycobacterium Comparative Analysis Platform.

Science.gov (United States)

Choo, Siew Woh; Ang, Mia Yang; Dutta, Avirup; Tan, Shi Yang; Siow, Cheuk Chuen; Heydari, Hamed; Mutha, Naresh V R; Wee, Wei Yee; Wong, Guat Jah

2015-12-15

Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

Science.gov (United States)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms

Science.gov (United States)

Babier, Aaron; Boutilier, Justin J.; Sharpe, Michael B.; McNiven, Andrea L.; Chan, Timothy C. Y.

2018-05-01

We developed and evaluated a novel inverse optimization (IO) model to estimate objective function weights from clinical dose-volume histograms (DVHs). These weights were used to solve a treatment planning problem to generate ‘inverse plans’ that had similar DVHs to the original clinical DVHs. Our methodology was applied to 217 clinical head and neck cancer treatment plans that were previously delivered at Princess Margaret Cancer Centre in Canada. Inverse plan DVHs were compared to the clinical DVHs using objective function values, dose-volume differences, and frequency of clinical planning criteria satisfaction. Median differences between the clinical and inverse DVHs were within 1.1 Gy. For most structures, the difference in clinical planning criteria satisfaction between the clinical and inverse plans was at most 1.4%. For structures where the two plans differed by more than 1.4% in planning criteria satisfaction, the difference in average criterion violation was less than 0.5 Gy. Overall, the inverse plans were very similar to the clinical plans. Compared with a previous inverse optimization method from the literature, our new inverse plans typically satisfied the same or more clinical criteria, and had consistently lower fluence heterogeneity. Overall, this paper demonstrates that DVHs, which are essentially summary statistics, provide sufficient information to estimate objective function weights that result in high quality treatment plans. However, as with any summary statistic that compresses three-dimensional dose information, care must be taken to avoid generating plans with undesirable features such as hotspots; our computational results suggest that such undesirable spatial features were uncommon. Our IO-based approach can be integrated into the current clinical planning paradigm to better initialize the planning process and improve planning efficiency. It could also be embedded in a knowledge-based planning or adaptive radiation therapy framework to

Identification of column edges of DNA fragments by using K-means clustering and mean algorithm on lane histograms of DNA agarose gel electrophoresis images

Science.gov (United States)

Turan, Muhammed K.; Sehirli, Eftal; Elen, Abdullah; Karas, Ismail R.

2015-07-01

Gel electrophoresis (GE) is one of the most used method to separate DNA, RNA, protein molecules according to size, weight and quantity parameters in many areas such as genetics, molecular biology, biochemistry, microbiology. The main way to separate each molecule is to find borders of each molecule fragment. This paper presents a software application that show columns edges of DNA fragments in 3 steps. In the first step the application obtains lane histograms of agarose gel electrophoresis images by doing projection based on x-axis. In the second step, it utilizes k-means clustering algorithm to classify point values of lane histogram such as left side values, right side values and undesired values. In the third step, column edges of DNA fragments is shown by using mean algorithm and mathematical processes to separate DNA fragments from the background in a fully automated way. In addition to this, the application presents locations of DNA fragments and how many DNA fragments exist on images captured by a scientific camera.

Use of fractional dose–volume histograms to model risk of acute rectal toxicity among patients treated on RTOG 94-06

International Nuclear Information System (INIS)

Tucker, Susan L.; Michalski, Jeff M.; Bosch, Walter R.; Mohan, Radhe; Dong, Lei; Winter, Kathryn; Purdy, James A.; Cox, James D.

2012-01-01

Background and purpose: For toxicities occurring during the course of radiotherapy, it is conceptually inaccurate to perform normal-tissue complication probability analyses using the complete dose–volume histogram. The goal of this study was to analyze acute rectal toxicity using a novel approach in which the fit of the Lyman–Kutcher–Burman (LKB) model is based on the fractional rectal dose–volume histogram (DVH). Materials and methods: Grade ⩾2 acute rectal toxicity was analyzed in 509 patients treated on Radiation Therapy Oncology Group (RTOG) protocol 94-06. These patients had no field reductions or treatment-plan revisions during therapy, allowing the fractional rectal DVH to be estimated from the complete rectal DVH based on the total number of dose fractions delivered. Results: The majority of patients experiencing Grade ⩾2 acute rectal toxicity did so before completion of radiotherapy (70/80 = 88%). Acute rectal toxicity depends on fractional mean rectal dose, with no significant improvement in the LKB model fit when the volume parameter differs from n = 1. The incidence of toxicity was significantly lower for patients who received hormone therapy (P = 0.024). Conclusions: Variations in fractional mean dose explain the differences in incidence of acute rectal toxicity, with no detectable effect seen here for differences in numbers of dose fractions delivered.

Brachytherapy dose-volume histogram computations using optimized stratified sampling methods

International Nuclear Information System (INIS)

Karouzakis, K.; Lahanas, M.; Milickovic, N.; Giannouli, S.; Baltas, D.; Zamboglou, N.

2002-01-01

A stratified sampling method for the efficient repeated computation of dose-volume histograms (DVHs) in brachytherapy is presented as used for anatomy based brachytherapy optimization methods. The aim of the method is to reduce the number of sampling points required for the calculation of DVHs for the body and the PTV. From the DVHs are derived the quantities such as Conformity Index COIN and COIN integrals. This is achieved by using partial uniform distributed sampling points with a density in each region obtained from a survey of the gradients or the variance of the dose distribution in these regions. The shape of the sampling regions is adapted to the patient anatomy and the shape and size of the implant. For the application of this method a single preprocessing step is necessary which requires only a few seconds. Ten clinical implants were used to study the appropriate number of sampling points, given a required accuracy for quantities such as cumulative DVHs, COIN indices and COIN integrals. We found that DVHs of very large tissue volumes surrounding the PTV, and also COIN distributions, can be obtained using a factor of 5-10 times smaller the number of sampling points in comparison with uniform distributed points

Rotation Invariant Color Retrieval

OpenAIRE

Swapna Borde; Udhav Bhosle

2013-01-01

The new technique for image retrieval using the color features extracted from images based on LogHistogram is proposed. The proposed technique is compared with Global color histogram and histogram ofcorners .It has been observed that number of histogram bins used for retrieval comparison of proposedtechnique (Log Histogram)is less as compared to Global Color Histogram and Histogram of corners. Theexperimental results on a database of 792 images with 11 classes indicate that proposed method (L...

A Comparative Study on Error Analysis

DEFF Research Database (Denmark)

Wu, Xiaoli; Zhang, Chun

2015-01-01

Title: A Comparative Study on Error Analysis Subtitle: - Belgian (L1) and Danish (L1) learners’ use of Chinese (L2) comparative sentences in written production Xiaoli Wu, Chun Zhang Abstract: Making errors is an inevitable and necessary part of learning. The collection, classification and analysis...... the occurrence of errors either in linguistic or pedagogical terms. The purpose of the current study is to demonstrate the theoretical and practical relevance of error analysis approach in CFL by investigating two cases - (1) Belgian (L1) learners’ use of Chinese (L2) comparative sentences in written production...... of errors in the written and spoken production of L2 learners has a long tradition in L2 pedagogy. Yet, in teaching and learning Chinese as a foreign language (CFL), only handful studies have been made either to define the ‘error’ in a pedagogically insightful way or to empirically investigate...

Comparing Results from Constant Comparative and Computer Software Methods: A Reflection about Qualitative Data Analysis

Science.gov (United States)

Putten, Jim Vander; Nolen, Amanda L.

2010-01-01

This study compared qualitative research results obtained by manual constant comparative analysis with results obtained by computer software analysis of the same data. An investigated about issues of trustworthiness and accuracy ensued. Results indicated that the inductive constant comparative data analysis generated 51 codes and two coding levels…

Comparative Genome Viewer

International Nuclear Information System (INIS)

Molineris, I.; Sales, G.

2009-01-01

The amount of information about genomes, both in the form of complete sequences and annotations, has been exponentially increasing in the last few years. As a result there is the need for tools providing a graphical representation of such information that should be comprehensive and intuitive. Visual representation is especially important in the comparative genomics field since it should provide a combined view of data belonging to different genomes. We believe that existing tools are limited in this respect as they focus on a single genome at a time (conservation histograms) or compress alignment representation to a single dimension. We have therefore developed a web-based tool called Comparative Genome Viewer (Cgv): it integrates a bidimensional representation of alignments between two regions, both at small and big scales, with the richness of annotations present in other genome browsers. We give access to our system through a web-based interface that provides the user with an interactive representation that can be updated in real time using the mouse to move from region to region and to zoom in on interesting details.

Pedestrian detection in crowded scenes with the histogram of gradients principle

Science.gov (United States)

Sidla, O.; Rosner, M.; Lypetskyy, Y.

2006-10-01

This paper describes a close to real-time scale invariant implementation of a pedestrian detector system which is based on the Histogram of Oriented Gradients (HOG) principle. Salient HOG features are first selected from a manually created very large database of samples with an evolutionary optimization procedure that directly trains a polynomial Support Vector Machine (SVM). Real-time operation is achieved by a cascaded 2-step classifier which uses first a very fast linear SVM (with the same features as the polynomial SVM) to reject most of the irrelevant detections and then computes the decision function with a polynomial SVM on the remaining set of candidate detections. Scale invariance is achieved by running the detector of constant size on scaled versions of the original input images and by clustering the results over all resolutions. The pedestrian detection system has been implemented in two versions: i) fully body detection, and ii) upper body only detection. The latter is especially suited for very busy and crowded scenarios. On a state-of-the-art PC it is able to run at a frequency of 8 - 20 frames/sec.

A computational comparison of theory and practice of scale intonation in Byzantine chant

DEFF Research Database (Denmark)

Panteli, Maria; Purwins, Hendrik

2013-01-01

Byzantine Chant performance practice is quantitatively compared to the Chrysanthine theory. The intonation of scale degrees is quantified, based on pitch class profiles. An analysis procedure is introduced that consists of the following steps: 1) Pitch class histograms are calculated via non-parametric...... kernel smoothing. 2) Histogram peaks are detected. 3) Phrase ending analysis aids the finding of the tonic to align histogram peaks. 4) The theoretical scale degrees are mapped to the practical ones. 5) A schema of statistical tests detects significant deviations of theoretical scale tuning from...... the estimated ones in performance practice. The analysis of 94 echoi shows a tendency of the singer to level theoretic particularities of the echos that stand out of the general norm in the octoechos: theoretically extremely large scale steps are diminished in performance....

[The value of spectral frequency analysis by Doppler examination (author's transl)].

Science.gov (United States)

Boccalon, H; Reggi, M; Lozes, A; Canal, C; Jausseran, J M; Courbier, R; Puel, P; Enjalbert, A

1981-01-01

Arterial stenoses of moderate extent may involve modifications of the blood flow. Arterial shading is not always examined at the best incident angle to assess the extent of the stenosis. Spectral frequency analysis by Doppler examination is a good means of evaluating the effect of moderate arterial lesions. The present study was carried out with a Doppler effect having an acoustic spectrum, which is shown in a histogram having 16 frequency bands. The values were recorded on the two femoral arteries. A study was also made of 49 normal subjects so as to establish a normal envelope histogram, taking into account the following parameters: maximum peak (800 Hz), low cut-off frequency (420 Hz), high cut-off frequency (2,600 Hz); the first peak was found to be present in 81 % of the subjects (at 375 Hz) and the second peak in 75 % of the subjects (2,020 Hz). Thirteen patients with iliac lesions of different extent were included in the study; details of these lesions were established in all cases by aortography. None of the recorded frequency histograms were located within the normal envelope. Two cases of moderate iliac stenoses were noted ( Less Than 50 % of the diameter) which interfered with the histogram, even though the femoral velocity signal was normal.