Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

Science.gov (United States)

Favazza, Christopher P; Ferrero, Andrea; Yu, Lifeng; Leng, Shuai; McMillan, Kyle L; McCollough, Cynthia H

2017-07-01

The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.

Optimization of X-ray phase-contrast imaging based on in-line holography

International Nuclear Information System (INIS)

Wu Xizeng; Liu Hong; Yan Aimin

2005-01-01

This paper introduces a newly conceived formalism for clinical in-line phase-contrast X-ray imaging. The new formalism applies not only to ideal 'thin' objects analyzed in previous studies, but also applies to the real-world tissues used in actual clinical practice. Moreover we have identified the four clinically important factors that affect phase-contrast characteristics. These factors are: (1) body part attenuation (2) the spatial coherence of incident X-rays from an X-ray tube (3) the polychromatic nature of the X-ray source and (4) radiation dose to patients for clinical applications. Techniques of phase image-reconstruction based on the new X-ray in-line holography theory are discussed. Numerical simulations are described which were used to validate the theory. The design parameters of an optimal clinical phase-contrast mammographic imaging system which were determined based on the new theory, and validated in the simulations, are presented. The theory, image reconstruction algorithms, and numerical simulation techniques presented in this paper can be applied widely to clinical diagnostic X-ray imaging applications

PET image reconstruction: mean, variance, and optimal minimax criterion

International Nuclear Information System (INIS)

Liu, Huafeng; Guo, Min; Gao, Fei; Shi, Pengcheng; Xue, Liying; Nie, Jing

2015-01-01

Given the noise nature of positron emission tomography (PET) measurements, it is critical to know the image quality and reliability as well as expected radioactivity map (mean image) for both qualitative interpretation and quantitative analysis. While existing efforts have often been devoted to providing only the reconstructed mean image, we present a unified framework for joint estimation of the mean and corresponding variance of the radioactivity map based on an efficient optimal min–max criterion. The proposed framework formulates the PET image reconstruction problem to be a transformation from system uncertainties to estimation errors, where the minimax criterion is adopted to minimize the estimation errors with possibly maximized system uncertainties. The estimation errors, in the form of a covariance matrix, express the measurement uncertainties in a complete way. The framework is then optimized by ∞-norm optimization and solved with the corresponding H ∞ filter. Unlike conventional statistical reconstruction algorithms, that rely on the statistical modeling methods of the measurement data or noise, the proposed joint estimation stands from the point of view of signal energies and can handle from imperfect statistical assumptions to even no a priori statistical assumptions. The performance and accuracy of reconstructed mean and variance images are validated using Monte Carlo simulations. Experiments on phantom scans with a small animal PET scanner and real patient scans are also conducted for assessment of clinical potential. (paper)

Clinical evaluation of FMPSPGR sequence of the brain MR imaging

International Nuclear Information System (INIS)

Takahashi, Mitsuyuki; Hasegawa, Makoto; Mori, Naohiko; Yamanoguchi, Minoru; Matsubara, Tadashi

1998-01-01

In order to apply the FMPSPGR (fast multi planar spoiled GRASS) method to diagnose brain diseases, authors obtained the optimal condition for imaging by the phantom experiments and examined the clinical usefulness. Six kinds of the phantom, which were 4 of diluted Gd solution with different concentrations, olive oil and physiological saline solution were used. From the phantom experiments, TR/TE/FR=300/3.3/90 degrees was the optimal condition. The evaluation of the clinical images was performed on the same section by the ST method and the FMPSPGR method. Fifteen patients (9 men and 6 women, aged from 17 to 80 years) suspected of brain diseases were examined, including 8 of cerebral infarction, 1 of pontine infarction, 1 of brain contusion, 1 of intracerebral bleeding and 4 of brain tumors. Four cases of brain tumor were evaluated on the contrast imaging and the others were on the plain imaging. In the plain imaging, the FMPSPGR method was better than the SE method on the low signal region in the T1 weighted imaging. Furthermore, in the contrast imaging, it could give more clear images of the lesion in anterior cranial pit by suppressing artifacts of blood flow. The present results indicate that the FMPSPGR method is useful to diagnose brain diseases. (K.H.)

Availability of color calibration for consistent color display in medical images and optimization of reference brightness for clinical use

Science.gov (United States)

Iwai, Daiki; Suganami, Haruka; Hosoba, Minoru; Ohno, Kazuko; Emoto, Yutaka; Tabata, Yoshito; Matsui, Norihisa

2013-03-01

Color image consistency has not been accomplished yet except the Digital Imaging and Communication in Medicine (DICOM) Supplement 100 for implementing a color reproduction pipeline and device independent color spaces. Thus, most healthcare enterprises could not check monitor degradation routinely. To ensure color consistency in medical color imaging, monitor color calibration should be introduced. Using simple color calibration device . chromaticity of colors including typical color (Red, Green, Blue, Green and White) are measured as device independent profile connection space value called u'v' before and after calibration. In addition, clinical color images are displayed and visual differences are observed. In color calibration, monitor brightness level has to be set to quite lower value 80 cd/m2 according to sRGB standard. As Maximum brightness of most color monitors available currently for medical use have much higher brightness than 80 cd/m2, it is not seemed to be appropriate to use 80 cd/m2 level for calibration. Therefore, we propose that new brightness standard should be introduced while maintaining the color representation in clinical use. To evaluate effects of brightness to chromaticity experimentally, brightness level is changed in two monitors from 80 to 270cd/m2 and chromaticity value are compared with each brightness levels. As a result, there are no significant differences in chromaticity diagram when brightness levels are changed. In conclusion, chromaticity is close to theoretical value after color calibration. Moreover, chromaticity isn't moved when brightness is changed. The results indicate optimized reference brightness level for clinical use could be set at high brightness in current monitors .

Optimization for PET imaging based on phantom study and NECdensity

International Nuclear Information System (INIS)

Daisaki, Hiromitsu; Shimada, Naoki; Shinohara, Hiroyuki

2012-01-01

In consideration of the requirement for global standardization and quality control of PET imaging, the present studies gave an outline of phantom study to decide both scan and reconstruction parameters based on FDG-PET/CT procedure guideline in Japan, and optimization of scan duration based on NEC density was performed continuously. In the phantom study, scan and reconstruction parameters were decided by visual assessment and physical indexes (N 10mm , NEC phantom , Q H,10mm /N 10mm ) to visualize hot spot of 10 mm diameter with standardized uptake value (SUV)=4 explicitly. Simultaneously, Recovery Coefficient (RC) was evaluated to recognize that PET images had enough quantifiably. Scan durations were optimized by Body Mass Index (BMI) based on retrospective analysis of NEC density . Correlation between visual score in clinical FDG-PET images and NEC density fell after the optimization of scan duration. Both Inter-institution and inter-patient variability were decreased by performing the phantom study based on the procedure guideline and the optimization of scan duration based on NEC density which seem finally useful to practice highly precise examination and promote high-quality controlled study. (author)

Developing optimized CT scan protocols: Phantom measurements of image quality

International Nuclear Information System (INIS)

Zarb, Francis; Rainford, Louise; McEntee, Mark F.

2011-01-01

0-49% and 0-51% respectively. Below the optimization threshold, CR and noise were significantly affected (p ≤ 0.05) but not SR (p ≥ 0.083). The threshold value is the value below which CR and noise were affected. Conclusion: Optimization was effected through the establishment of the limits at which image quality is detrimentally reduced by dose reduction. This work established the mA, kV and pitch changes necessary to achieve the optimization thresholds, reducing the dose and the limit at which psychophysical image quality is significantly decreased. Further work will evaluate these settings in the clinical environment.

Optimizing color reproduction of natural images

NARCIS (Netherlands)

Yendrikhovskij, S.N.; Blommaert, F.J.J.; Ridder, de H.

1998-01-01

The paper elaborates on understanding, measuring and optimizing perceived color quality of natural images. We introduce a model for optimal color reproduction of natural scenes which is based on the assumption that color quality of natural images is constrained by perceived naturalness and

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

Energy Technology Data Exchange (ETDEWEB)

Andreozzi, Jacqueline M., E-mail: Jacqueline.M.Andreozzi.th@dartmouth.edu, E-mail: Lesley.A.Jarvis@hitchcock.org; Glaser, Adam K. [Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755 (United States); Zhang, Rongxiao [Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755 (United States); Gladstone, David J.; Williams, Benjamin B.; Jarvis, Lesley A., E-mail: Jacqueline.M.Andreozzi.th@dartmouth.edu, E-mail: Lesley.A.Jarvis@hitchcock.org [Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire 03766 (United States); Pogue, Brian W. [Thayer School of Engineering and Department of Physics and Astronomy, Dartmouth College, Hanover, New Hampshire 03755 (United States)

2016-02-15

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, composite images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R{sup 2} = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial

Image acquisition optimization of a limited-angle intrafraction verification (LIVE) system for lung radiotherapy.

Science.gov (United States)

Zhang, Yawei; Deng, Xinchen; Yin, Fang-Fang; Ren, Lei

2018-01-01

Limited-angle intrafraction verification (LIVE) has been previously developed for four-dimensional (4D) intrafraction target verification either during arc delivery or between three-dimensional (3D)/IMRT beams. Preliminary studies showed that LIVE can accurately estimate the target volume using kV/MV projections acquired over orthogonal view 30° scan angles. Currently, the LIVE imaging acquisition requires slow gantry rotation and is not clinically optimized. The goal of this study is to optimize the image acquisition parameters of LIVE for different patient respiratory periods and gantry rotation speeds for the effective clinical implementation of the system. Limited-angle intrafraction verification imaging acquisition was optimized using a digital anthropomorphic phantom (XCAT) with simulated respiratory periods varying from 3 s to 6 s and gantry rotation speeds varying from 1°/s to 6°/s. LIVE scanning time was optimized by minimizing the number of respiratory cycles needed for the four-dimensional scan, and imaging dose was optimized by minimizing the number of kV and MV projections needed for four-dimensional estimation. The estimation accuracy was evaluated by calculating both the center-of-mass-shift (COMS) and three-dimensional volume-percentage-difference (VPD) between the tumor in estimated images and the ground truth images. The robustness of LIVE was evaluated with varied respiratory patterns, tumor sizes, and tumor locations in XCAT simulation. A dynamic thoracic phantom (CIRS) was used to further validate the optimized imaging schemes from XCAT study with changes of respiratory patterns, tumor sizes, and imaging scanning directions. Respiratory periods, gantry rotation speeds, number of respiratory cycles scanned and number of kV/MV projections acquired were all positively correlated with the estimation accuracy of LIVE. Faster gantry rotation speed or longer respiratory period allowed less respiratory cycles to be scanned and less kV/MV projections

MO-FG-204-08: Optimization-Based Image Reconstruction From Unevenly Distributed Sparse Projection Views

International Nuclear Information System (INIS)

Xie, Huiqiao; Yang, Yi; Tang, Xiangyang; Niu, Tianye; Ren, Yi

2015-01-01

Purpose: Optimization-based reconstruction has been proposed and investigated for reconstructing CT images from sparse views, as such the radiation dose can be substantially reduced while maintaining acceptable image quality. The investigation has so far focused on reconstruction from evenly distributed sparse views. Recognizing the clinical situations wherein only unevenly sparse views are available, e.g., image guided radiation therapy, CT perfusion and multi-cycle cardiovascular imaging, we investigate the performance of optimization-based image reconstruction from unevenly sparse projection views in this work. Methods: The investigation is carried out using the FORBILD and an anthropomorphic head phantoms. In the study, 82 views, which are evenly sorted out from a full (360°) axial CT scan consisting of 984 views, form sub-scan I. Another 82 views are sorted out in a similar manner to form sub-scan II. As such, a CT scan with sparse (164) views at 1:6 ratio are formed. By shifting the two sub-scans relatively in view angulation, a CT scan with unevenly distributed sparse (164) views at 1:6 ratio are formed. An optimization-based method is implemented to reconstruct images from the unevenly distributed views. By taking the FBP reconstruction from the full scan (984 views) as the reference, the root mean square (RMS) between the reference and the optimization-based reconstruction is used to evaluate the performance quantitatively. Results: In visual inspection, the optimization-based method outperforms the FBP substantially in the reconstruction from unevenly distributed, which are quantitatively verified by the RMS gauged globally and in ROIs in both the FORBILD and anthropomorphic head phantoms. The RMS increases with increasing severity in the uneven angular distribution, especially in the case of anthropomorphic head phantom. Conclusion: The optimization-based image reconstruction can save radiation dose up to 12-fold while providing acceptable image quality

Comparison of 3 T and 7 T MRI clinical sequences for ankle imaging

Energy Technology Data Exchange (ETDEWEB)

Juras, Vladimir, E-mail: vladimir.juras@meduniwien.ac.at [Medical University of Vienna, Department of Radiology, Vienna General Hospital, Waeringer Guertel 18-20, A-1090 Vienna (Austria); Slovak Academy of Sciences, Institute of Measurement Science, Dubravska cesta 9, 84104 Bratislava (Slovakia); Welsch, Goetz, E-mail: welsch@bwh.harvard.edu [Medical University of Vienna, Department of Radiology, Vienna General Hospital, Waeringer Guertel 18-20, A-1090 Vienna (Austria); Baer, Peter, E-mail: baerpeter@siemens.com [Siemens Healthcare, Richard-Strauss-Strasse 76, D81679 Munich (Germany); Kronnerwetter, Claudia, E-mail: claudia.kronnerwetter@meduniwien.ac.at [Medical University of Vienna, Department of Radiology, Vienna General Hospital, Waeringer Guertel 18-20, A-1090 Vienna (Austria); Fujita, Hiroyuki, E-mail: hiroyuki.fujita@qualedyn.com [Quality Electrodynamics, LCC, 777 Beta Dr, Cleveland, OH 44143-2336 (United States); Trattnig, Siegfried, E-mail: siegfried.trattnig@meduniwien.ac.at [Medical University of Vienna, Department of Radiology, Vienna General Hospital, Waeringer Guertel 18-20, A-1090 Vienna (Austria)

2012-08-15

The purpose of this study was to compare 3 T and 7 T signal-to-noise and contrast-to noise ratios of clinical sequences for imaging of the ankles with optimized sequences and dedicated coils. Ten healthy volunteers were examined consecutively on both systems with three clinical sequences: (1) 3D gradient-echo, T{sub 1}-weighted; (2) 2D fast spin-echo, PD-weighted; and (3) 2D spin-echo, T{sub 1}-weighted. SNR was calculated for six regions: cartilage; bone; muscle; synovial fluid; Achilles tendon; and Kager's fat-pad. CNR was obtained for cartilage/bone, cartilage/fluid, cartilage/muscle, and muscle/fat-pad, and compared by a one-way ANOVA test for repeated measures. Mean SNR significantly increased at 7 T compared to 3 T for 3D GRE, and 2D TSE was 60.9% and 86.7%, respectively. In contrast, an average SNR decrease of almost 25% was observed in the 2D SE sequence. A CNR increase was observed in 2D TSE images, and in most 3D GRE images. There was a substantial benefit from ultra high-field MR imaging of ankles with routine clinical sequences at 7 T compared to 3 T. Higher SNR and CNR at ultra-high field MR scanners may be useful in clinical practice for ankle imaging. However, carefully optimized protocols and dedicated extremity coils are necessary to obtain optimal results.

Optimization of chest radiography. Experimental and clinical studies using rare earths screen

Energy Technology Data Exchange (ETDEWEB)

Bergonzini, R; Robecchi, D; Amato, M; Gallini, R; Giugni, V

1986-01-01

The optimization of chest radiography is a still unresolved problem, as it must answer to various clinical requirements. Even if sometimes the choice is not difficult, it becomes hard when the best film-screen combination is needed. In order to assess the optimization image quality and exposition, different experimental and clinical conditions have been investigated referring to the various combination of screen, film and tension. The Trimax system has been chosen for our investigations, performed in two different phases: the former on an anthropomorphous chest phantom, the latter on 25 patients affected by lung interstitial diseases, mainly nodular. The results are discussed.

Image registration via optimization over disjoint image regions

Science.gov (United States)

Pitts, Todd; Hathaway, Simon; Karelitz, David B.; Sandusky, John; Laine, Mark Richard

2018-02-06

Technologies pertaining to registering a target image with a base image are described. In a general embodiment, the base image is selected from a set of images, and the target image is an image in the set of images that is to be registered to the base image. A set of disjoint regions of the target image is selected, and a transform to be applied to the target image is computed based on the optimization of a metric over the selected set of disjoint regions. The transform is applied to the target image so as to register the target image with the base image.

Markerless motion estimation for motion-compensated clinical brain imaging

Science.gov (United States)

Kyme, Andre Z.; Se, Stephen; Meikle, Steven R.; Fulton, Roger R.

2018-05-01

Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon emission computed tomography (SPECT) and computed tomography (CT). However, motion-compensated imaging protocols are not in widespread clinical use for these modalities. A key reason for this seems to be the lack of a practical motion tracking technology that allows for smooth and reliable integration of motion-compensated imaging protocols in the clinical setting. We seek to address this problem by investigating the feasibility of a highly versatile optical motion tracking method for PET, SPECT and CT geometries. The method requires no attached markers, relying exclusively on the detection and matching of distinctive facial features. We studied the accuracy of this method in 16 volunteers in a mock imaging scenario by comparing the estimated motion with an accurate marker-based method used in applications such as image guided surgery. A range of techniques to optimize performance of the method were also studied. Our results show that the markerless motion tracking method is highly accurate (brain imaging and holds good promise for a practical implementation in clinical PET, SPECT and CT systems.

Optimization of dual-wavelength intravascular photoacoustic imaging of atherosclerotic plaques using Monte Carlo optical modeling

Science.gov (United States)

Dana, Nicholas; Sowers, Timothy; Karpiouk, Andrei; Vanderlaan, Donald; Emelianov, Stanislav

2017-10-01

Coronary heart disease (the presence of coronary atherosclerotic plaques) is a significant health problem in the industrialized world. A clinical method to accurately visualize and characterize atherosclerotic plaques is needed. Intravascular photoacoustic (IVPA) imaging is being developed to fill this role, but questions remain regarding optimal imaging wavelengths. We utilized a Monte Carlo optical model to simulate IVPA excitation in coronary tissues, identifying optimal wavelengths for plaque characterization. Near-infrared wavelengths (≤1800 nm) were simulated, and single- and dual-wavelength data were analyzed for accuracy of plaque characterization. Results indicate light penetration is best in the range of 1050 to 1370 nm, where 5% residual fluence can be achieved at clinically relevant depths of ≥2 mm in arteries. Across the arterial wall, fluence may vary by over 10-fold, confounding plaque characterization. For single-wavelength results, plaque segmentation accuracy peaked at 1210 and 1720 nm, though correlation was poor (blood, a primary and secondary wavelength near 1210 and 1350 nm, respectively, may offer the best implementation of dual-wavelength IVPA imaging. These findings could guide the development of a cost-effective clinical system by highlighting optimal wavelengths and improving plaque characterization.

Improved MR breast images by contrast optimization using artificial intelligence

International Nuclear Information System (INIS)

Konig, H.; Gohagan, J.; Laub, G.; Bachus, R.; Heywang, S.; Reinhardt, E.R.

1986-01-01

The clinical relevance of MR imaging of the breast is mainly related to the modelity's ability to differentiate among normal, benign, and malignant tissue and to yield prognostic information. In addition to the MR imaging parameters, morphologic features of these images are calculated. Based on statistical information of a comprehensive, labeled image and knowledge of a data base system, a numerical classifier is deduced. The application of this classifier to all cases leads to estimations of specific tissue types for each pixel. The method is sufficiently sensitive for grading a recognized tissue class. In this manner images with optimal contrast appropriate to particular diagnostic requirements are generated. The discriminant power of each MR imaging parameter as well as of a combination of parameters can be determined objectively with respect to tissue discrimination

Crowded Field Photometry and Moving Object Detection with Optimal Image Subtraction

Science.gov (United States)

Lee, Austin A. T.; Scheulen, F.; Sauro, C. M.; McMahon, C. T.; Berry, S. J.; Robinson, C. H.; Buie, M. W.; Little, P.

2010-05-01

High precision photometry and moving object detection are essential in the study of Pluto and the Kuiper Belt. In particular, the New Horizons mission would benefit from an accurate and fast method of performing image subtraction to locate faint Kuiper Belt Objects (KBO) among large data sets. The optimal image subtraction (OIS) algorithm was optimized for IDL to decrease execution time by a factor of about 140 from a previous implementation (Miller 2008, PASP, 120, 449). In addition, a powerful image transformation and interpolation routine was written to provide OIS with well-aligned input images using astrometric fit data. The first half of this project is complete including the code optimization and the alignment routine. The second half of the project is focused on using these tools to search a 5 x 10 degree search area to find KBOs for possible targets for the New Horizons mission. We will present examples of how these tools work and along with resulting Pluto photometry and KBO target lists. The optimized OIS and transformation routines are available in Marc Buie's IDL library at http://www.boulder.swri.edu/ buie/idl/ as ois.pro and dewarp.pro. This project was conducted for Harvey Mudd College's Clinic Program with financial support from the NASA Planetary Astronomy Program grant number NNX09AB43G.

Clinical applications of cardiovascular magnetic resonance imaging

International Nuclear Information System (INIS)

Marcu, C.B.; Beek, A.M.; Van Rossum, A.C.

2006-01-01

Cardiovascular magnetic resonance imaging (MRI) has evolved from an effective research tool into a clinically proven, safe and comprehensive imaging modality. It provides anatomic and functional information in acquired and congenital heart disease and is the most precise technique for quantification of ventricular volumes, function and mass. Owing to its excellent interstudy reproducibility, cardiovascular MRI is the optimal method for assessment of changes in ventricular parameters after therapeutic intervention. Delayed contrast enhancement is an accurate and robust method used in the diagnosis of ischemic and nonischemic cardiomyopathies and less common diseases, such as cardiac sarcoidosis and myocarditis. First-pass magnetic contrast myocardial perfusion is becoming an alternative to radionuclide techniques for the detection of coronary atherosclerotic disease. In this review we outline the techniques used in cardiovascular MRI and discuss the most common clinical applications. (author)

Optimal Scale Edge Detection Utilizing Noise within Images

Directory of Open Access Journals (Sweden)

Adnan Khashman

2003-04-01

Full Text Available Edge detection techniques have common problems that include poor edge detection in low contrast images, speed of recognition and high computational cost. An efficient solution to the edge detection of objects in low to high contrast images is scale space analysis. However, this approach is time consuming and computationally expensive. These expenses can be marginally reduced if an optimal scale is found in scale space edge detection. This paper presents a new approach to detecting objects within images using noise within the images. The novel idea is based on selecting one optimal scale for the entire image at which scale space edge detection can be applied. The selection of an ideal scale is based on the hypothesis that "the optimal edge detection scale (ideal scale depends on the noise within an image". This paper aims at providing the experimental evidence on the relationship between the optimal scale and the noise within images.

Optimization of Butterworth filter for brain SPECT imaging

International Nuclear Information System (INIS)

Minoshima, Satoshi; Maruno, Hirotaka; Yui, Nobuharu

1993-01-01

A method has been described to optimize the cutoff frequency of the Butterworth filter for brain SPECT imaging. Since a computer simulation study has demonstrated that separation between an object signal and the random noise in projection images in a spatial-frequency domain is influenced by the total number of counts, the cutoff frequency of the Butterworth filter should be optimized for individual subjects according to total counts in a study. To reveal the relationship between the optimal cutoff frequencies and total counts in brain SPECT study, we used a normal volunteer and 99m Tc hexamethyl-propyleneamine oxime (HMPAO) to obtain projection sets with different total counts. High quality images were created from a projection set with an acquisition time of 300-seconds per projection. The filter was optimized by calculating mean square errors from high quality images visually inspecting filtered reconstructed images. Dependence between total counts and optimal cutoff frequencies was clearly demonstrated in a nomogram. Using this nomogram, the optimal cutoff frequency for each study can be estimated from total counts, maximizing visual image quality. The results suggest that the cutoff frequency of Butterworth filter should be determined by referring to total counts in each study. (author)

Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system.

Science.gov (United States)

Moore, C S; Wood, T J; Beavis, A W; Saunderson, J R

2013-07-01

The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system. The results of a previously published study, in which four experienced image evaluators graded computer-simulated postero-anterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson's correlation coefficient. Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R=0.87, pchest CR images acquired without an antiscatter grid. A statistically significant correlation has been found between the clinical and physical image quality in CR chest imaging. The results support the value of using CNR and eDE in the evaluation of quality in clinical thorax radiography.

Clinical implementation of x-ray phase-contrast imaging: Theoretical foundations and design considerations

International Nuclear Information System (INIS)

Wu Xizeng; Liu Hong

2003-01-01

Theoretical foundation and design considerations of a clinical feasible x-ray phase contrast imaging technique were presented in this paper. Different from the analysis of imaging phase object with weak absorption in literature, we proposed a new formalism for in-line phase-contrast imaging to analyze the effects of four clinically important factors on the phase contrast. These are the body parts attenuation, the spatial coherence of spherical waves from a finite-size focal spot, and polychromatic x-ray and radiation doses to patients for clinical applications. The theory presented in this paper can be applied widely in diagnostic x-ray imaging procedures. As an example, computer simulations were conducted and optimal design parameters were derived for clinical mammography. The results of phantom experiments were also presented which validated the theoretical analysis and computer simulations

Identification of threshold prostate specific antigen levels to optimize the detection of clinically significant prostate cancer by magnetic resonance imaging/ultrasound fusion guided biopsy.

Science.gov (United States)

Shakir, Nabeel A; George, Arvin K; Siddiqui, M Minhaj; Rothwax, Jason T; Rais-Bahrami, Soroush; Stamatakis, Lambros; Su, Daniel; Okoro, Chinonyerem; Raskolnikov, Dima; Walton-Diaz, Annerleim; Simon, Richard; Turkbey, Baris; Choyke, Peter L; Merino, Maria J; Wood, Bradford J; Pinto, Peter A

2014-12-01

Prostate specific antigen sensitivity increases with lower threshold values but with a corresponding decrease in specificity. Magnetic resonance imaging/ultrasound targeted biopsy detects prostate cancer more efficiently and of higher grade than standard 12-core transrectal ultrasound biopsy but the optimal population for its use is not well defined. We evaluated the performance of magnetic resonance imaging/ultrasound targeted biopsy vs 12-core biopsy across a prostate specific antigen continuum. We reviewed the records of all patients enrolled in a prospective trial who underwent 12-core transrectal ultrasound and magnetic resonance imaging/ultrasound targeted biopsies from August 2007 through February 2014. Patients were stratified by each of 4 prostate specific antigen cutoffs. The greatest Gleason score using either biopsy method was compared in and across groups as well as across the population prostate specific antigen range. Clinically significant prostate cancer was defined as Gleason 7 (4 + 3) or greater. Univariate and multivariate analyses were performed. A total of 1,003 targeted and 12-core transrectal ultrasound biopsies were performed, of which 564 diagnosed prostate cancer for a 56.2% detection rate. Targeted biopsy led to significantly more upgrading to clinically significant disease compared to 12-core biopsy. This trend increased more with increasing prostate specific antigen, specifically in patients with prostate specific antigen 4 to 10 and greater than 10 ng/ml. Prostate specific antigen 5.2 ng/ml or greater captured 90% of upgrading by targeted biopsy, corresponding to 64% of patients who underwent multiparametric magnetic resonance imaging and subsequent fusion biopsy. Conversely a greater proportion of clinically insignificant disease was detected by 12-core vs targeted biopsy overall. These differences persisted when controlling for potential confounders on multivariate analysis. Prostate cancer upgrading with targeted biopsy increases

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research

OpenAIRE

Milchenko, Mikhail; Snyder, Abraham Z.; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L.; Fouke, Sarah Jost; Marcus, Daniel S.

2016-01-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis.

Optimizing CT radiation dose based on patient size and image quality: the size-specific dose estimate method

Energy Technology Data Exchange (ETDEWEB)

Larson, David B. [Stanford University School of Medicine, Department of Radiology, Stanford, CA (United States)

2014-10-15

The principle of ALARA (dose as low as reasonably achievable) calls for dose optimization rather than dose reduction, per se. Optimization of CT radiation dose is accomplished by producing images of acceptable diagnostic image quality using the lowest dose method available. Because it is image quality that constrains the dose, CT dose optimization is primarily a problem of image quality rather than radiation dose. Therefore, the primary focus in CT radiation dose optimization should be on image quality. However, no reliable direct measure of image quality has been developed for routine clinical practice. Until such measures become available, size-specific dose estimates (SSDE) can be used as a reasonable image-quality estimate. The SSDE method of radiation dose optimization for CT abdomen and pelvis consists of plotting SSDE for a sample of examinations as a function of patient size, establishing an SSDE threshold curve based on radiologists' assessment of image quality, and modifying protocols to consistently produce doses that are slightly above the threshold SSDE curve. Challenges in operationalizing CT radiation dose optimization include data gathering and monitoring, managing the complexities of the numerous protocols, scanners and operators, and understanding the relationship of the automated tube current modulation (ATCM) parameters to image quality. Because CT manufacturers currently maintain their ATCM algorithms as secret for proprietary reasons, prospective modeling of SSDE for patient populations is not possible without reverse engineering the ATCM algorithm and, hence, optimization by this method requires a trial-and-error approach. (orig.)

Optimization of Synthetic Aperture Image Quality

DEFF Research Database (Denmark)

Moshavegh, Ramin; Jensen, Jonas; Villagómez Hoyos, Carlos Armando

2016-01-01

Synthetic Aperture (SA) imaging produces high-quality images and velocity estimates of both slow and fast flow at high frame rates. However, grating lobe artifacts can appear both in transmission and reception. These affect the image quality and the frame rate. Therefore optimization of parameter...

Unique roles of SPET brain imaging in clinical and research studies

International Nuclear Information System (INIS)

Seibyl, J.; Jennings, D.; Tabamo, R.; Marek, K.

2005-01-01

The increasing availability of PET imaging in Nuclear medicine expands the armamentarium of clinical and research tools for improving diagnosis and treatment of neuropsychiatric disorders. Nonetheless, the role of SPEC imaging remains critical to both research and clinical practice. The development of rational strategies for guiding the selection of imaging modalities flows from primarily the nature of the clinical or research question and the availability of appropriate radiopharmaceuticals. There has been extensive SPECT and PET work in Parkinson's disease (PD) which highlights the value of both these scintigraphic modalities. Three main areas of interest in PD include imaging for improving diagnostic accuracy, for monitoring the progression of disease, and for assessing the therapeutic efficacy of drugs with neoroprotective potential. The demands of the clinical or research question posed to imaging dictates the selection of radiotracer and imaging modality. Diagnosis of PD represents the easiest challenge with many imaging bio markers showing high sensitivity for detecting abnormal reduction of dopaminergic function based on qualitative review of images. On the other hand, using imaging to evaluate treatments which purportedly slow the rate of disease progression, indicated by the reduction of the rate of loss in a quantitative imaging signal in patients studied over time, represents the most rigorous requirement of the imaging measure. In each of these applications presynaptic markers of dopaminergic function using SPECT and PET have been extremely valuable. Review of neuroimaging studies of PD provides a useful example of optimized approaches to clinical and research studies in neuropsychiatric disorders

Companion diagnostics and molecular imaging-enhanced approaches for oncology clinical trials.

Science.gov (United States)

Van Heertum, Ronald L; Scarimbolo, Robert; Ford, Robert; Berdougo, Eli; O'Neal, Michael

2015-01-01

In the era of personalized medicine, diagnostic approaches are helping pharmaceutical and biotechnology sponsors streamline the clinical trial process. Molecular assays and diagnostic imaging are routinely being used to stratify patients for treatment, monitor disease, and provide reliable early clinical phase assessments. The importance of diagnostic approaches in drug development is highlighted by the rapidly expanding global cancer diagnostics market and the emergent attention of regulatory agencies worldwide, who are beginning to offer more structured platforms and guidance for this area. In this paper, we highlight the key benefits of using companion diagnostics and diagnostic imaging with a focus on oncology clinical trials. Nuclear imaging using widely available radiopharmaceuticals in conjunction with molecular imaging of oncology targets has opened the door to more accurate disease assessment and the modernization of standard criteria for the evaluation, staging, and treatment responses of cancer patients. Furthermore, the introduction and validation of quantitative molecular imaging continues to drive and optimize the field of oncology diagnostics. Given their pivotal role in disease assessment and treatment, the validation and commercialization of diagnostic tools will continue to advance oncology clinical trials, support new oncology drugs, and promote better patient outcomes.

Cross-layer Energy Optimization Under Image Quality Constraints for Wireless Image Transmissions.

Science.gov (United States)

Yang, Na; Demirkol, Ilker; Heinzelman, Wendi

2012-01-01

Wireless image transmission is critical in many applications, such as surveillance and environment monitoring. In order to make the best use of the limited energy of the battery-operated cameras, while satisfying the application-level image quality constraints, cross-layer design is critical. In this paper, we develop an image transmission model that allows the application layer (e.g., the user) to specify an image quality constraint, and optimizes the lower layer parameters of transmit power and packet length, to minimize the energy dissipation in image transmission over a given distance. The effectiveness of this approach is evaluated by applying the proposed energy optimization to a reference ZigBee system and a WiFi system, and also by comparing to an energy optimization study that does not consider any image quality constraint. Evaluations show that our scheme outperforms the default settings of the investigated commercial devices and saves a significant amount of energy at middle-to-large transmission distances.

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

Energy Technology Data Exchange (ETDEWEB)

Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc [German Cancer Research Center, Heidelberg (Germany).

2017-10-01

Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

International Nuclear Information System (INIS)

Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc

2017-01-01

Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

Imaging: Guiding the Clinical Translation of Cardiac Stem Cell Therapy

Science.gov (United States)

Nguyen, Patricia K.; Lan, Feng; Wang, Yongming; Wu, Joseph C.

2011-01-01

Stem cells have been touted as the holy grail of medical therapy with promises to regenerate cardiac tissue, but it appears the jury is still out on this novel therapy. Using advanced imaging technology, scientists have discovered that these cells do not survive nor engraft long-term. In addition, only marginal benefit has been observed in large animal studies and human trials. However, all is not lost. Further application of advanced imaging technology will help scientists unravel the mysteries of stem cell therapy and address the clinical hurdles facing its routine implementation. In this review, we will discuss how advanced imaging technology will help investigators better define the optimal delivery method, improve survival and engraftment, and evaluate efficacy and safety. Insights gained from this review may direct the development of future preclinical investigations and clinical trials. PMID:21960727

Optimized nonorthogonal transforms for image compression.

Science.gov (United States)

Guleryuz, O G; Orchard, M T

1997-01-01

The transform coding of images is analyzed from a common standpoint in order to generate a framework for the design of optimal transforms. It is argued that all transform coders are alike in the way they manipulate the data structure formed by transform coefficients. A general energy compaction measure is proposed to generate optimized transforms with desirable characteristics particularly suited to the simple transform coding operation of scalar quantization and entropy coding. It is shown that the optimal linear decoder (inverse transform) must be an optimal linear estimator, independent of the structure of the transform generating the coefficients. A formulation that sequentially optimizes the transforms is presented, and design equations and algorithms for its computation provided. The properties of the resulting transform systems are investigated. In particular, it is shown that the resulting basis are nonorthogonal and complete, producing energy compaction optimized, decorrelated transform coefficients. Quantization issues related to nonorthogonal expansion coefficients are addressed with a simple, efficient algorithm. Two implementations are discussed, and image coding examples are given. It is shown that the proposed design framework results in systems with superior energy compaction properties and excellent coding results.

Design of an optimization algorithm for clinical use

International Nuclear Information System (INIS)

Gustafsson, Anders

1995-01-01

Radiation therapy optimization has received much attention in the past few years. In combination with biological objective functions, the different optimization schemes has shown a potential to considerably increase the treatment outcome. With improved radiobiological models and increased computer capacity, radiation therapy optimization has now reached a stage where implementation in a clinical treatment planning system is realistic. A radiation therapy optimization method has been investigated with respect to its feasibility as a tool in a clinical 3D treatment planning system. The optimization algorithm is a constrained iterative gradient method. Photon dose calculation is performed using the clinically validated pencil-beam based algorithm of the clinical treatment planning system. Dose calculation within the optimization scheme is very time consuming and measures are required to decrease the calculation time. Different methods for more effective dose calculation within the optimization scheme have been investigated. The optimization results for adaptive sampling of calculation points, and secondary effect approximations in the dose calculation algorithm are compared with the optimization result for accurate dose calculation in all voxels of interest

Joint optimization of collimator and reconstruction parameters in SPECT imaging for lesion quantification

International Nuclear Information System (INIS)

McQuaid, Sarah J; Southekal, Sudeepti; Kijewski, Marie Foley; Moore, Stephen C

2011-01-01

Obtaining the best possible task performance using reconstructed SPECT images requires optimization of both the collimator and reconstruction parameters. The goal of this study is to determine how to perform this optimization, namely whether the collimator parameters can be optimized solely from projection data, or whether reconstruction parameters should also be considered. In order to answer this question, and to determine the optimal collimation, a digital phantom representing a human torso with 16 mm diameter hot lesions (activity ratio 8:1) was generated and used to simulate clinical SPECT studies with parallel-hole collimation. Two approaches to optimizing the SPECT system were then compared in a lesion quantification task: sequential optimization, where collimation was optimized on projection data using the Cramer–Rao bound, and joint optimization, which simultaneously optimized collimator and reconstruction parameters. For every condition, quantification performance in reconstructed images was evaluated using the root-mean-squared-error of 400 estimates of lesion activity. Compared to the joint-optimization approach, the sequential-optimization approach favoured a poorer resolution collimator, which, under some conditions, resulted in sub-optimal estimation performance. This implies that inclusion of the reconstruction parameters in the optimization procedure is important in obtaining the best possible task performance; in this study, this was achieved with a collimator resolution similar to that of a general-purpose (LEGP) collimator. This collimator was found to outperform the more commonly used high-resolution (LEHR) collimator, in agreement with other task-based studies, using both quantification and detection tasks.

Diagnostic Performance of Three Phase Bone Scan for Complex Regional Pain Syndrome Type 1 with Optimally Modified Image Criteria

Energy Technology Data Exchange (ETDEWEB)

Kwon, Hyun Woo; Paeng, Jin Chul; Nahm, Francins Sahngun; Kim, Seog Gyun; Zehra, Tanzeel; Oh, So Won; Lee, Hyo Sang; Kang, Keon Wook; Chung, June Key; Lee, Myung Chul; Lee, Dong Soo [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

2011-12-15

Although the three phase bone scan (TBPS) is one of the widely used imaging studies for diagnosing complex regional pain syndrome type 1 (CRPS 1), there is some controversy regarding the TPBS image criteria for CRPS 1. In this study, we modified the image criteria using image pattern and quantitative analysis in the patients diagnosed using the most recent consensus clinical diagnostic criteria. The study included 140 patients with suspected CRPS 1 (CRPS 1, n=79; non CRPS, n=61; mean age 39{+-}15 years) who underwent TPBS. The clinical diagnostic criteria for CRPS 1 revised by the Budapest consensus group were used for confirmative diagnosis. Patients were classified according to flow/pool and delayed uptake (DU) image patterns, and the time interval between the initiating event and TPBS (TI{sup eventscan)}. Quantitative analysis for lesion to contralateral ratio (LCR) was performed. Modified TPBS image criteria were created and evaluated for optimal diagnostic performance. Both increased and decreased periarticular DU were significant image findings for CRPS 1 (CRPS 1 positive rate=73% in the increased DU group, 75% in the decreased DU group). The TI{sup eventscand}id not differ significantly between the different image pattern groups. Quantitative analysis revealed an LCR of 1.43 was the optimal cutoff value for CRPS 1 and diagnostic performance was significantly improved in the increased DU group (area under the curve=0.732). Given the modified image criteria, the sensitivity and specificity of TPBS for diagnosing CRPS 1 were 80% and 72%, respectively. Optimally modified TPBS image criteria for CRPS 1 were suggested using image pattern and quantitative analysis. With the criteria, TPBS is an effective imaging study for CRPS 1 even with the most recent consensus clinical diagnostic criteria.

Diagnostic Performance of Three Phase Bone Scan for Complex Regional Pain Syndrome Type 1 with Optimally Modified Image Criteria

International Nuclear Information System (INIS)

Kwon, Hyun Woo; Paeng, Jin Chul; Nahm, Francins Sahngun; Kim, Seog Gyun; Zehra, Tanzeel; Oh, So Won; Lee, Hyo Sang; Kang, Keon Wook; Chung, June Key; Lee, Myung Chul; Lee, Dong Soo

2011-01-01

Although the three phase bone scan (TBPS) is one of the widely used imaging studies for diagnosing complex regional pain syndrome type 1 (CRPS 1), there is some controversy regarding the TPBS image criteria for CRPS 1. In this study, we modified the image criteria using image pattern and quantitative analysis in the patients diagnosed using the most recent consensus clinical diagnostic criteria. The study included 140 patients with suspected CRPS 1 (CRPS 1, n=79; non CRPS, n=61; mean age 39±15 years) who underwent TPBS. The clinical diagnostic criteria for CRPS 1 revised by the Budapest consensus group were used for confirmative diagnosis. Patients were classified according to flow/pool and delayed uptake (DU) image patterns, and the time interval between the initiating event and TPBS (TI eventscan) . Quantitative analysis for lesion to contralateral ratio (LCR) was performed. Modified TPBS image criteria were created and evaluated for optimal diagnostic performance. Both increased and decreased periarticular DU were significant image findings for CRPS 1 (CRPS 1 positive rate=73% in the increased DU group, 75% in the decreased DU group). The TI eventscand id not differ significantly between the different image pattern groups. Quantitative analysis revealed an LCR of 1.43 was the optimal cutoff value for CRPS 1 and diagnostic performance was significantly improved in the increased DU group (area under the curve=0.732). Given the modified image criteria, the sensitivity and specificity of TPBS for diagnosing CRPS 1 were 80% and 72%, respectively. Optimally modified TPBS image criteria for CRPS 1 were suggested using image pattern and quantitative analysis. With the criteria, TPBS is an effective imaging study for CRPS 1 even with the most recent consensus clinical diagnostic criteria.

Optimization of Segmentation Quality of Integrated Circuit Images

Directory of Open Access Journals (Sweden)

Gintautas Mušketas

2012-04-01

Full Text Available The paper presents investigation into the application of genetic algorithms for the segmentation of the active regions of integrated circuit images. This article is dedicated to a theoretical examination of the applied methods (morphological dilation, erosion, hit-and-miss, threshold and describes genetic algorithms, image segmentation as optimization problem. The genetic optimization of the predefined filter sequence parameters is carried out. Improvement to segmentation accuracy using a non optimized filter sequence makes 6%.Artcile in Lithuanian

Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

Energy Technology Data Exchange (ETDEWEB)

Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl [Siemens AG, Healthcare Sector, Siemensstrasse 1, 91301 Forchheim (Germany); Flohr, Thomas [Siemens AG, Healthcare Sector, Siemensstrasse 1, 91301 Forchheim (Germany); Institute of Diagnostic Radiology, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany)

2013-03-15

Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phase (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum

Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

International Nuclear Information System (INIS)

Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl; Flohr, Thomas

2013-01-01

Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phase (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum

Optimization of T2-weighted imaging for shoulder magnetic resonance arthrography by synthetic magnetic resonance imaging.

Science.gov (United States)

Lee, Seung Hyun; Lee, Young Han; Hahn, Seok; Yang, Jaemoon; Song, Ho-Taek; Suh, Jin-Suck

2017-01-01

Background Synthetic magnetic resonance imaging (MRI) allows reformatting of various synthetic images by adjustment of scanning parameters such as repetition time (TR) and echo time (TE). Optimized MR images can be reformatted from T1, T2, and proton density (PD) values to achieve maximum tissue contrast between joint fluid and adjacent soft tissue. Purpose To demonstrate the method for optimization of TR and TE by synthetic MRI and to validate the optimized images by comparison with conventional shoulder MR arthrography (MRA) images. Material and Methods Thirty-seven shoulder MRA images acquired by synthetic MRI were retrospectively evaluated for PD, T1, and T2 values at the joint fluid and glenoid labrum. Differences in signal intensity between the fluid and labrum were observed between TR of 500-6000 ms and TE of 80-300 ms in T2-weighted (T2W) images. Conventional T2W and synthetic images were analyzed for diagnostic agreement of supraspinatus tendon abnormalities (kappa statistics) and image quality scores (one-way analysis of variance with post-hoc analysis). Results Optimized mean values of TR and TE were 2724.7 ± 1634.7 and 80.1 ± 0.4, respectively. Diagnostic agreement for supraspinatus tendon abnormalities between conventional and synthetic MR images was excellent (κ = 0.882). The mean image quality score of the joint space in optimized synthetic images was significantly higher compared with those in conventional and synthetic images (2.861 ± 0.351 vs. 2.556 ± 0.607 vs. 2.750 ± 0.439; P optimized TR and TE for shoulder MRA enables optimization of soft-tissue contrast.

TH-B-207B-00: Pediatric Image Quality Optimization

International Nuclear Information System (INIS)

2016-01-01

This imaging educational program will focus on solutions to common pediatric image quality optimization challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. One of the most commonly encountered pediatric imaging requirements for the non-specialist hospital is pediatric CT in the emergency room setting. Thus, this educational program will begin with optimization of pediatric CT in the emergency department. Though pediatric cardiovascular MRI may be less common in the non-specialist hospitals, low pediatric volumes and unique cardiovascular anatomy make optimization of these techniques difficult. Therefore, our second speaker will review best practices in pediatric cardiovascular MRI based on experiences from a children’s hospital with a large volume of cardiac patients. Learning Objectives: To learn techniques for optimizing radiation dose and image quality for CT of children in the emergency room setting. To learn solutions for consistently high quality cardiovascular MRI of children

TH-B-207B-00: Pediatric Image Quality Optimization

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

This imaging educational program will focus on solutions to common pediatric image quality optimization challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. One of the most commonly encountered pediatric imaging requirements for the non-specialist hospital is pediatric CT in the emergency room setting. Thus, this educational program will begin with optimization of pediatric CT in the emergency department. Though pediatric cardiovascular MRI may be less common in the non-specialist hospitals, low pediatric volumes and unique cardiovascular anatomy make optimization of these techniques difficult. Therefore, our second speaker will review best practices in pediatric cardiovascular MRI based on experiences from a children’s hospital with a large volume of cardiac patients. Learning Objectives: To learn techniques for optimizing radiation dose and image quality for CT of children in the emergency room setting. To learn solutions for consistently high quality cardiovascular MRI of children.

MO-PIS-Exhibit Hall-01: Imaging: CT Dose Optimization Technologies I

Energy Technology Data Exchange (ETDEWEB)

Denison, K; Smith, S [GE Healthcare, Waukesha, WI (United States)

2014-06-15

Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The imaging topic this year is CT scanner dose optimization capabilities. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Dose Optimization Capabilities of GE Computed Tomography Scanners Presentation Time: 11:15 – 11:45 AM GE Healthcare is dedicated to the delivery of high quality clinical images through the development of technologies, which optimize the application of ionizing radiation. In computed tomography, dose management solutions fall into four categories: employs projection data and statistical modeling to decrease noise in the reconstructed image - creating an opportunity for mA reduction in the acquisition of diagnostic images. Veo represents true Model Based Iterative Reconstruction (MBiR). Using high-level algorithms in tandem with advanced computing power, Veo enables lower pixel noise standard deviation and improved spatial resolution within a single image. Advanced Adaptive Image Filters allow for maintenance of spatial resolution while reducing image noise. Examples of adaptive image space filters include Neuro 3-D filters and Cardiac Noise Reduction Filters. AutomA adjusts mA along the z-axis and is the CT equivalent of auto exposure control in conventional x-ray systems. Dynamic Z-axis Tracking offers an additional opportunity for dose reduction in helical acquisitions while SmartTrack Z-axis Tracking serves to ensure beam, collimator and detector alignment during tube rotation. SmartmA provides angular mA modulation. ECG Helical Modulation reduces mA during the systolic phase of the heart cycle. SmartBeam optimization uses bowtie beam-shaping hardware and software to filter off-axis x-rays - minimizing dose and reducing x-ray scatter. The

MO-PIS-Exhibit Hall-01: Imaging: CT Dose Optimization Technologies I

International Nuclear Information System (INIS)

Denison, K; Smith, S

2014-01-01

Partners in Solutions is an exciting new program in which AAPM partners with our vendors to present practical “hands-on” information about the equipment and software systems that we use in our clinics. The imaging topic this year is CT scanner dose optimization capabilities. Note that the sessions are being held in a special purpose room built on the Exhibit Hall Floor, to encourage further interaction with the vendors. Dose Optimization Capabilities of GE Computed Tomography Scanners Presentation Time: 11:15 – 11:45 AM GE Healthcare is dedicated to the delivery of high quality clinical images through the development of technologies, which optimize the application of ionizing radiation. In computed tomography, dose management solutions fall into four categories: employs projection data and statistical modeling to decrease noise in the reconstructed image - creating an opportunity for mA reduction in the acquisition of diagnostic images. Veo represents true Model Based Iterative Reconstruction (MBiR). Using high-level algorithms in tandem with advanced computing power, Veo enables lower pixel noise standard deviation and improved spatial resolution within a single image. Advanced Adaptive Image Filters allow for maintenance of spatial resolution while reducing image noise. Examples of adaptive image space filters include Neuro 3-D filters and Cardiac Noise Reduction Filters. AutomA adjusts mA along the z-axis and is the CT equivalent of auto exposure control in conventional x-ray systems. Dynamic Z-axis Tracking offers an additional opportunity for dose reduction in helical acquisitions while SmartTrack Z-axis Tracking serves to ensure beam, collimator and detector alignment during tube rotation. SmartmA provides angular mA modulation. ECG Helical Modulation reduces mA during the systolic phase of the heart cycle. SmartBeam optimization uses bowtie beam-shaping hardware and software to filter off-axis x-rays - minimizing dose and reducing x-ray scatter. The

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Science.gov (United States)

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K; Schad, Lothar R; Zöllner, Frank Gerrit

2015-01-01

Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

A Degree Distribution Optimization Algorithm for Image Transmission

Science.gov (United States)

Jiang, Wei; Yang, Junjie

2016-09-01

Luby Transform (LT) code is the first practical implementation of digital fountain code. The coding behavior of LT code is mainly decided by the degree distribution which determines the relationship between source data and codewords. Two degree distributions are suggested by Luby. They work well in typical situations but not optimally in case of finite encoding symbols. In this work, the degree distribution optimization algorithm is proposed to explore the potential of LT code. Firstly selection scheme of sparse degrees for LT codes is introduced. Then probability distribution is optimized according to the selected degrees. In image transmission, bit stream is sensitive to the channel noise and even a single bit error may cause the loss of synchronization between the encoder and the decoder. Therefore the proposed algorithm is designed for image transmission situation. Moreover, optimal class partition is studied for image transmission with unequal error protection. The experimental results are quite promising. Compared with LT code with robust soliton distribution, the proposed algorithm improves the final quality of recovered images obviously with the same overhead.

Optimized workflow and imaging protocols for whole-body oncologic PET/MRI.

Science.gov (United States)

Ishii, Shirou; Hara, Takamitsu; Nanbu, Takeyuki; Suenaga, Hiroki; Sugawara, Shigeyasu; Kuroiwa, Daichi; Sekino, Hirofumi; Miyajima, Masayuki; Kubo, Hitoshi; Oriuchi, Noboru; Ito, Hiroshi

2016-11-01

Although PET/MRI has the advantages of a simultaneous acquisition of PET and MRI, high soft-tissue contrast of the MRI images, and reduction of radiation exposure, its low profitability and long acquisition time are significant problems in clinical settings. Thus, MRI protocols that meet oncological purposes need to be used in order to reduce examination time while securing detectability. Currently, half-Fourier acquisition single-shot turbo spin echo and 3D-T1 volumetric interpolated breath-hold examination may be the most commonly used sequences for whole-body imaging due to their shorter acquisition time and higher diagnostic accuracy. Although there have been several reports that adding diffusion weighted image (DWI) to PET/MRI protocol has had no effect on tumor detection to date, in cases of liver, kidney, bladder, and prostate cancer, the use of DWI may be beneficial in detecting lesions. Another possible option is to scan each region with different MRI sequences instead of scanning the whole body using one sequence continuously. We herein report a workflow and imaging protocols for whole-body oncologic PET/MRI using an integrated system in the clinical routine, designed for the detection, for example by cancer screening, of metastatic lesions, in order to help future users optimize their workflow and imaging protocols.

Dual optimization based prostate zonal segmentation in 3D MR images.

Science.gov (United States)

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2014-05-01

Efficient and accurate segmentation of the prostate and two of its clinically meaningful sub-regions: the central gland (CG) and peripheral zone (PZ), from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, a novel multi-region segmentation approach is proposed to simultaneously segment the prostate and its two major sub-regions from only a single 3D T2-weighted (T2w) MR image, which makes use of the prior spatial region consistency and incorporates a customized prostate appearance model into the segmentation task. The formulated challenging combinatorial optimization problem is solved by means of convex relaxation, for which a novel spatially continuous max-flow model is introduced as the dual optimization formulation to the studied convex relaxed optimization problem with region consistency constraints. The proposed continuous max-flow model derives an efficient duality-based algorithm that enjoys numerical advantages and can be easily implemented on GPUs. The proposed approach was validated using 18 3D prostate T2w MR images with a body-coil and 25 images with an endo-rectal coil. Experimental results demonstrate that the proposed method is capable of efficiently and accurately extracting both the prostate zones: CG and PZ, and the whole prostate gland from the input 3D prostate MR images, with a mean Dice similarity coefficient (DSC) of 89.3±3.2% for the whole gland (WG), 82.2±3.0% for the CG, and 69.1±6.9% for the PZ in 3D body-coil MR images; 89.2±3.3% for the WG, 83.0±2.4% for the CG, and 70.0±6.5% for the PZ in 3D endo-rectal coil MR images. In addition, the experiments of intra- and inter-observer variability introduced by user initialization indicate a good reproducibility of the proposed approach in terms of volume difference (VD) and coefficient-of-variation (CV) of DSC. Copyright © 2014 Elsevier B.V. All rights reserved.

Clinical imaging of the pancreas

International Nuclear Information System (INIS)

May, G.; Gardiner, R.

1987-01-01

Featuring more than 300 high-quality radiographs and scan images, clinical imaging of the pancreas systematically reviews all appropriate imaging modalities for diagnosing and evaluating a variety of commonly encountered pancreatic disorders. After presenting a succinct overview of pancreatic embryology, anatomy, and physiology, the authors establish the clinical indications-including postoperative patient evaluation-for radiologic examination of the pancreas. The diagnostic capabilities and limitations of currently available imaging techniques for the pancreas are thoroughly assessed, with carefully selected illustrations depicting the types of images and data obtained using these different techniques. The review of acute and chronic pancreatitis considers the clinical features and possible complications of their variant forms and offers guidance in selecting appropriate imaging studies

Challenges in clinical studies with multiple imaging probes

International Nuclear Information System (INIS)

Krohn, Kenneth A.; O'Sullivan, Finbarr; Crowley, John; Eary, Janet F.; Linden, Hannah M.; Link, Jeanne M.; Mankoff, David A.; Muzi, Mark; Rajendran, Joseph G.; Spence, Alexander M.; Swanson, Kristin R.

2007-01-01

This article addresses two related issues: (a) When a new imaging agent is proposed, how does the imager integrate it with other biomarkers, either sampled or imaged? (b) When we have multiple imaging agents, is the information additive or duplicative and how is this objectively determined? Molecular biology is leading to new treatment options with reduced normal tissue toxicity, and imaging should have a role in objectively evaluating new treatments. There are two roles for molecular characterization of disease. Molecular imaging measurements before therapy help predict the aggressiveness of disease and identify therapeutic targets and, therefore, help choose the optimal therapy for an individual. Measurements of specific biochemical processes made during or after therapy should be sensitive measures of tumor response. The rules of evidence are not fully developed for the prognostic role of imaging biomarkers, but the potential of molecular imaging provides compelling motivation to push forward with convincing validation studies. New imaging procedures need to be characterized for their effectiveness under realistic clinical conditions to improve the management of patients and achieve a better outcome. The purpose of this article is to promote a critical discussion within the molecular imaging community because our future value to the overall biomedical community will be in supporting better treatment outcomes rather than in detection

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

International Nuclear Information System (INIS)

Chawla, Amarpreet S.; Lo, Joseph Y.; Baker, Jay A.; Samei, Ehsan

2009-01-01

Breast tomosynthesis has been an exciting new development in the field of breast imaging. While the diagnostic improvement via tomosynthesis is notable, the full potential of tomosynthesis has not yet been realized. This may be attributed to the dependency of the diagnostic quality of tomosynthesis on multiple variables, each of which needs to be optimized. Those include dose, number of angular projections, and the total angular span of those projections. In this study, the authors investigated the effects of these acquisition parameters on the overall diagnostic image quality of breast tomosynthesis in both the projection and reconstruction space. Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of each specimen were acquired at 6.2 times typical single-view clinical dose level. Images at lower dose levels were then simulated using a noise modification routine. Each projection image was supplemented with 84 simulated 3 mm 3D lesions embedded at the center of 84 nonoverlapping ROIs. The projection images were then reconstructed using a filtered backprojection algorithm at different combinations of acquisition parameters to investigate which of the many possible combinations maximizes the performance. Performance was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion detectability. The analysis was also performed without reconstruction by combining the model results from projection images using Bayesian decision fusion algorithm. The effect of acquisition parameters on projection images and reconstructed slices were then compared to derive an optimization rule for tomosynthesis. The results indicated that projection images yield comparable but higher performance than reconstructed images. Both modes, however, offered similar trends: Performance improved with an increase in the total acquisition dose level and the angular span. Using a constant dose level and angular

Circular SAR Optimization Imaging Method of Buildings

Directory of Open Access Journals (Sweden)

Wang Jian-feng

2015-12-01

Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.

ProxImaL: efficient image optimization using proximal algorithms

KAUST Repository

Heide, Felix

2016-07-11

Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.

Usefulness and limitation of functional MRI with echo planar imaging using clinical MR apparatus

International Nuclear Information System (INIS)

Kusunoki, Katsusuke; Zenke, Kiichiro; Saito, Masahiro; Sadamoto, Kazuhiko; Ohue, Shiro; Sakaki, Saburo; Kumon, Yoshiaki; Kabasawa, Hiroyuki; Nagasawa, Kiyoshi

1998-01-01

We studied blood oxygen level-dependent (BOLD) functional MRI (fMRI) with EPI sequence in 21 normal volunteers and 8 presurgical clinical patients using a 1.5 T clinical MRI apparatus. To optimize the imaging parameters, we compared the fMRI images obtained by GFE-EPI and by SE-EPI in normal volunteers while each squeezed a sponge ball. We identified the motor cortex in 85.7% of normal volunteers by GFE-EPI in contrast to only 28.6% by SE-EPI. In addition, our clinical MR apparatus, using optimized parameters, maximally provides 15 slices per 5 seconds. In patients with brain tumor close to the sensorimotor cortex, we attempted to identify the motor cortex preoperatively by this procedure and found a significant increase of signal intensity in the motor cortex in 5 of 8 patients. In conclusion, fMRI using EPI may be useful for identifying the motor cortex preoperatively. However, further development of the apparatus is needed to obtain better temporal and spatial resolution for clinical applications. (author)

Random mask optimization for fast neutron coded aperture imaging

Energy Technology Data Exchange (ETDEWEB)

McMillan, Kyle [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Univ. of California, Los Angeles, CA (United States); Marleau, Peter [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Brubaker, Erik [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2015-05-01

In coded aperture imaging, one of the most important factors determining the quality of reconstructed images is the choice of mask/aperture pattern. In many applications, uniformly redundant arrays (URAs) are widely accepted as the optimal mask pattern. Under ideal conditions, thin and highly opaque masks, URA patterns are mathematically constructed to provide artifact-free reconstruction however, the number of URAs for a chosen number of mask elements is limited and when highly penetrating particles such as fast neutrons and high-energy gamma-rays are being imaged, the optimum is seldom achieved. In this case more robust mask patterns that provide better reconstructed image quality may exist. Through the use of heuristic optimization methods and maximum likelihood expectation maximization (MLEM) image reconstruction, we show that for both point and extended neutron sources a random mask pattern can be optimized to provide better image quality than that of a URA.

Dynamic contrast-enhanced MR imaging of endometrial cancer. Optimizing the imaging delay for tumour-myometrium contrast

International Nuclear Information System (INIS)

Park, Sung Bin; Moon, Min Hoan; Sung, Chang Kyu; Oh, Sohee; Lee, Young Ho

2014-01-01

To investigate the optimal imaging delay time of dynamic contrast-enhanced magnetic resonance (MR) imaging in women with endometrial cancer. This prospective single-institution study was approved by the institutional review board, and informed consent was obtained from the participants. Thirty-five women (mean age, 54 years; age range, 29-66 years) underwent dynamic contrast-enhanced MR imaging with a temporal resolution of 25-40 seconds. The signal intensity difference ratios between the myometrium and endometrial cancer were analyzed to investigate the optimal imaging delay time using single change-point analysis. The optimal imaging delay time for appropriate tumour-myometrium contrast ranged from 31.7 to 268.1 seconds. The median optimal imaging delay time was 91.3 seconds, with an interquartile range of 46.2 to 119.5 seconds. The median signal intensity difference ratios between the myometrium and endometrial cancer were 0.03, with an interquartile range of -0.01 to 0.06, on the pre-contrast MR imaging and 0.20, with an interquartile range of 0.15 to 0.25, on the post-contrast MR imaging. An imaging delay of approximately 90 seconds after initiating contrast material injection may be optimal for obtaining appropriate tumour-myometrium contrast in women with endometrial cancer. (orig.)

Investigation of Optimal Integrated Circuit Raster Image Vectorization Method

Directory of Open Access Journals (Sweden)

Leonas Jasevičius

2011-03-01

Full Text Available Visual analysis of integrated circuit layer requires raster image vectorization stage to extract layer topology data to CAD tools. In this paper vectorization problems of raster IC layer images are presented. Various line extraction from raster images algorithms and their properties are discussed. Optimal raster image vectorization method was developed which allows utilization of common vectorization algorithms to achieve the best possible extracted vector data match with perfect manual vectorization results. To develop the optimal method, vectorized data quality dependence on initial raster image skeleton filter selection was assessed.Article in Lithuanian

Optimization of contrast of MR images in imaging of knee joint

International Nuclear Information System (INIS)

Szyblinski, K.; Bacic, G.

1994-01-01

The work describes the method of contrast optimization in magnetic resonance imaging. Computer program presented in the report allows analysis of contrast in selected tissues as a function of experiment parameters. Application to imaging of knee joint is presented

Toward optimal color image quality of television display

Science.gov (United States)

MacDonald, Lindsay W.; Endrikhovski, Sergej N.; Bech, Soren; Jensen, Kaj

1999-12-01

A general framework and first experimental results are presented for the `OPTimal IMage Appearance' (OPTIMA) project, which aims to develop a computational model for achieving optimal color appearance of natural images on adaptive CRT television displays. To achieve this goal we considered the perceptual constraints determining quality of displayed images and how they could be quantified. The practical value of the notion of optimal image appearance was translated from the high level of the perceptual constraints into a method for setting the display's parameters at the physical level. In general, the whole framework of quality determination includes: (1) evaluation of perceived quality; (2) evaluation of the individual perceptual attributes; and (3) correlation between the physical measurements, psychometric parameters and the subjective responses. We performed a series of psychophysical experiments, with observers viewing a series of color images on a high-end consumer television display, to investigate the relationships between Overall Image Quality and four quality-related attributes: Brightness Rendering, Chromatic Rendering, Visibility of Details and Overall Naturalness. The results of the experiments presented in this paper suggest that these attributes are highly inter-correlated.

Detection and optimization of image quality and dose in digital mammography systems

International Nuclear Information System (INIS)

Semturs, F.

2015-01-01

Background and purpose: During the last few years, mammography institutes have replaced their conventional mammography systems (FSM) with digital mammography systems (FFDM). This happened mainly in direction to digital computed radiography systems (FFDM-CR), where the mammography device could be kept in operation. Consequently also the AEC-parameters have not been changed and therefore the same dose as for FFM was used. Following the main theme of the thesis "Optimization of image quality and dose", also measurements with such CR-Systems have been performed in relation to image quality and dose behavior. Optimization in this context means - in following the ALARA principle - the reduction of dose while ensuring required clinical image quality. With other words - image quality is of higher value compared to dose. Considering this, it has been found out through measurements during this thesis, that FFDM-CR Systems need considerable more dose for achieving image quality comparable with FFM. On the other hand, it has been shown with measurements during this thesis, that the newest FFDM-CR technology (needle structure) supports dose reduction (optimization) to a certain degree without compromising image quality. Dose increase, as recommended in this thesis, could also increase the danger of more radiation induced carcinoma. There are several studies (which are also discussed in this thesis), which show that the benefit of not missing cancers because of higher dose dramatically overrides any health concerns. Such an optimization of image quality and dose is now described in more detail by comparing the new CR needle technology with the older power based CR technology. Material and Methods: The image quality and dose behavior for multiple breast thicknesses (simulated with PMMA slabs) of a CR needle crystal detector system is optimized by considering also different beam qualities. Technical image quality is determined with a low contrast phantom (CDMAM phantom) and from

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Directory of Open Access Journals (Sweden)

Jakob Nikolas Kather

Full Text Available Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions.In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images.To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images.Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images.

Science.gov (United States)

Wang, Yuliang; Zhang, Zaicheng; Wang, Huimin; Bi, Shusheng

2015-01-01

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.

Breast imaging using the Twente photoacoustic mammoscope (PAM): new clinical measurements

Science.gov (United States)

Heijblom, Michelle; Piras, Daniele; Ten Tije, Ellen; Xia, Wenfeng; van Hespen, Johan; Klaase, Joost; van den Engh, Frank; van Leeuwen, Ton; Steenbergen, Wiendelt; Manohar, Srirang

2011-07-01

Worldwide, yearly about 450,000 women die from the consequences of breast cancer. Current imaging modalities are not optimal in discriminating benign from malignant tissue. Visualizing the malignancy-associated increased hemoglobin concentration might significantly improve early diagnosis of breast cancer. Since photoacoustic imaging can visualize hemoglobin in tissue with optical contrast and ultrasound-like resolution, it is potentially an ideal method for early breast cancer imaging. The Twente Photoacoustic Mammoscope (PAM) has been developed specifically for breast imaging. Recently, a large clinical study has been started in the Medisch Spectrum Twente in Oldenzaal using PAM. In PAM, the breast is slightly compressed between a window for laser light illumination and a flat array ultrasound detector. The measurements are performed using a Q-switched Nd:YAG laser, pulsed at 1064 nm and a 1 MHz unfocused ultrasound detector array. Three-dimensional data are reconstructed using a delay and sum reconstruction algorithm. Those reconstructed images are compared with conventional imaging and histopathology. In the first phase of the study 12 patients with a malignant lesion and 2 patients with a benign cyst have been measured. The results are used to guide developments in photoacoustic mammography in order to pave the way towards an optimal technique for early diagnosis of breast cancer.

A new optimal seam method for seamless image stitching

Science.gov (United States)

Xue, Jiale; Chen, Shengyong; Cheng, Xu; Han, Ying; Zhao, Meng

2017-07-01

A novel optimal seam method which aims to stitch those images with overlapping area more seamlessly has been propos ed. Considering the traditional gradient domain optimal seam method and fusion algorithm result in bad color difference measurement and taking a long time respectively, the input images would be converted to HSV space and a new energy function is designed to seek optimal stitching path. To smooth the optimal stitching path, a simplified pixel correction and weighted average method are utilized individually. The proposed methods exhibit performance in eliminating the stitching seam compared with the traditional gradient optimal seam and high efficiency with multi-band blending algorithm.

Diffusion weighted imaging demystified. The technique and potential clinical applications for soft tissue imaging

International Nuclear Information System (INIS)

Ahlawat, Shivani; Fayad, Laura M.

2018-01-01

Diffusion-weighted imaging (DWI) is a fast, non-contrast technique that is readily available and easy to integrate into an existing imaging protocol. DWI with apparent diffusion coefficient (ADC) mapping offers a quantitative metric for soft tissue evaluation and provides information regarding the cellularity of a region of interest. There are several available methods of performing DWI, and artifacts and pitfalls must be considered when interpreting DWI studies. This review article will review the various techniques of DWI acquisition and utility of qualitative as well as quantitative methods of image interpretation, with emphasis on optimal methods for ADC measurement. The current clinical applications for DWI are primarily related to oncologic evaluation: For the assessment of de novo soft tissue masses, ADC mapping can serve as a useful adjunct technique to routine anatomic sequences for lesion characterization as cyst or solid and, if solid, benign or malignant. For treated soft tissue masses, the role of DWI/ADC mapping in the assessment of treatment response as well as recurrent or residual neoplasm in the setting of operative management is discussed, especially when intravenous contrast medium cannot be given. Emerging DWI applications for non-neoplastic clinical indications are also reviewed. (orig.)

Diffusion weighted imaging demystified. The technique and potential clinical applications for soft tissue imaging

Energy Technology Data Exchange (ETDEWEB)

Ahlawat, Shivani [The Johns Hopkins Medical Institutions, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD (United States); Fayad, Laura M. [The Johns Hopkins Medical Institutions, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD (United States); The Johns Hopkins Medical Institutions, Department of Oncology, Baltimore, MD (United States); The Johns Hopkins Medical Institutions, Department of Orthopaedic Surgery, Baltimore, MD (United States)

2018-03-15

Diffusion-weighted imaging (DWI) is a fast, non-contrast technique that is readily available and easy to integrate into an existing imaging protocol. DWI with apparent diffusion coefficient (ADC) mapping offers a quantitative metric for soft tissue evaluation and provides information regarding the cellularity of a region of interest. There are several available methods of performing DWI, and artifacts and pitfalls must be considered when interpreting DWI studies. This review article will review the various techniques of DWI acquisition and utility of qualitative as well as quantitative methods of image interpretation, with emphasis on optimal methods for ADC measurement. The current clinical applications for DWI are primarily related to oncologic evaluation: For the assessment of de novo soft tissue masses, ADC mapping can serve as a useful adjunct technique to routine anatomic sequences for lesion characterization as cyst or solid and, if solid, benign or malignant. For treated soft tissue masses, the role of DWI/ADC mapping in the assessment of treatment response as well as recurrent or residual neoplasm in the setting of operative management is discussed, especially when intravenous contrast medium cannot be given. Emerging DWI applications for non-neoplastic clinical indications are also reviewed. (orig.)

Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding

Directory of Open Access Journals (Sweden)

Linguo Li

2017-01-01

Full Text Available The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO, which improves on the optimal solution updating mechanism of the search agent by the weights. Taking Kapur’s entropy as the optimized function and based on the discreteness of threshold in image segmentation, the paper firstly discretizes the grey wolf optimizer (GWO and then proposes a new attack strategy by using the weight coefficient to replace the search formula for optimal solution used in the original algorithm. The experimental results show that MDGWO can search out the optimal thresholds efficiently and precisely, which are very close to the result examined by exhaustive searches. In comparison with the electromagnetism optimization (EMO, the differential evolution (DE, the Artifical Bee Colony (ABC, and the classical GWO, it is concluded that MDGWO has advantages over the latter four in terms of image segmentation quality and objective function values and their stability.

Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET

International Nuclear Information System (INIS)

Ahn, Sangtae; Asma, Evren; Cheng, Lishui; Manjeshwar, Ravindra M; Ross, Steven G; Miao, Jun; Jin, Xiao; Wollenweber, Scott D

2015-01-01

Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality. Preliminary clinical studies have demonstrated visual image quality including lesion conspicuity in images reconstructed by the PL algorithm is better than or at least as good as that in OSEM images. In this paper we evaluate lesion quantitation accuracy of the PL algorithm with the relative difference penalty compared to OSEM by using various data sets including phantom data acquired with an anthropomorphic torso phantom, an extended oval phantom and the NEMA image quality phantom; clinical data; and hybrid clinical data generated by adding simulated lesion data to clinical data. We focus on mean standardized uptake values and compare them for PL and OSEM using both time-of-flight (TOF) and non-TOF data. The results demonstrate improvements of PL in lesion quantitation accuracy compared to OSEM with a particular improvement in cold background regions such as lungs. (paper)

Imaging of cystic fibrosis lung disease and clinical interpretation

Energy Technology Data Exchange (ETDEWEB)

Wielpuetz, M.O.; Eichinger, M.; Kauczor, H.U. [Heidelberg University Hospital (Germany). Dept. of Diagnostic and Interventional Radiology; Translational Lung Research Center Heidelberg (TLRC) (Germany); Heidelberg University Hospital (Germany). Dept. of Diagnostic and Interventional Radiology with Nuclear Medicine; Biederer, J. [Heidelberg University Hospital (Germany). Dept. of Diagnostic and Interventional Radiology; Translational Lung Research Center Heidelberg (TLRC) (Germany); Gross-Gerau Community Hospital (Germany). Radiologie Darmstadt; Wege, S. [Heidelberg University Hospital (Germany). Dept. of Pulmonology and Respiratory Medicine; Stahl, M.; Sommerburg, O. [Translational Lung Research Center Heidelberg (TLRC) (Germany); Heidelberg University Hospital (Germany). Div. of Pediatric Pulmonology and Allergy and Cystic Fibrosis Center; Mall, M.A. [Translational Lung Research Center Heidelberg (TLRC) (Germany); Heidelberg University Hospital (Germany). Div. of Pediatric Pulmonology and Allergy and Cystic Fibrosis Center; Heidelberg University Hospital (Germany). Dept. of Translational Pulmonology; Puderbach, M. [Heidelberg University Hospital (Germany). Dept. of Diagnostic and Interventional Radiology; Translational Lung Research Center Heidelberg (TLRC) (Germany); Heidelberg University Hospital (Germany). Dept. of Diagnostic and Interventional Radiology with Nuclear Medicine; Hufeland Hospital, Bad Langensalza (Germany). Dept. of Diagnostic and Interventional Radiology

2016-09-15

Progressive lung disease in cystic fibrosis (CF) is the life-limiting factor of this autosomal recessive genetic disorder. Increasing implementation of CF newborn screening allows for a diagnosis even in pre-symptomatic stages. Improvements in therapy have led to a significant improvement in survival, the majority now being of adult age. Imaging provides detailed information on the regional distribution of CF lung disease, hence longitudinal imaging is recommended for disease monitoring in the clinical routine. Chest X-ray (CXR), computed tomography (CT) and magnetic resonance imaging (MRI) are now available as routine modalities, each with individual strengths and drawbacks, which need to be considered when choosing the optimal modality adapted to the clinical situation of the patient. CT stands out with the highest morphological detail and has often been a substitute for CXR for regular severity monitoring at specialized centers. Multidetector CT data can be post-processed with dedicated software for a detailed measurement of airway dimensions and bronchiectasis and potentially a more objective and precise grading of disease severity. However, changing to CT was inseparably accompanied by an increase in radiation exposure of CF patients, a young population with high sensitivity to ionizing radiation and lifetime accumulation of dose. MRI as a cross-sectional imaging modality free of ionizing radiation can depict morphological hallmarks of CF lung disease at lower spatial resolution but excels with comprehensive functional lung imaging, with time-resolved perfusion imaging currently being most valuable.

Heuristic optimization in penumbral image for high resolution reconstructed image

International Nuclear Information System (INIS)

Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.

2010-01-01

Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.

Optimized protocols for cardiac magnetic resonance imaging in patients with thoracic metallic implants

Energy Technology Data Exchange (ETDEWEB)

Olivieri, Laura J.; Ratnayaka, Kanishka [Children' s National Health System, Division of Cardiology, Washington, DC (United States); National Institutes of Health, National Heart, Lung and Blood Institute, Bethesda, MD (United States); Cross, Russell R.; O' Brien, Kendall E. [Children' s National Health System, Division of Cardiology, Washington, DC (United States); Hansen, Michael S. [National Institutes of Health, National Heart, Lung and Blood Institute, Bethesda, MD (United States)

2015-09-15

Cardiac magnetic resonance (MR) imaging is a valuable tool in congenital heart disease; however patients frequently have metal devices in the chest from the treatment of their disease that complicate imaging. Methods are needed to improve imaging around metal implants near the heart. Basic sequence parameter manipulations have the potential to minimize artifact while limiting effects on image resolution and quality. Our objective was to design cine and static cardiac imaging sequences to minimize metal artifact while maintaining image quality. Using systematic variation of standard imaging parameters on a fluid-filled phantom containing commonly used metal cardiac devices, we developed optimized sequences for steady-state free precession (SSFP), gradient recalled echo (GRE) cine imaging, and turbo spin-echo (TSE) black-blood imaging. We imaged 17 consecutive patients undergoing routine cardiac MR with 25 metal implants of various origins using both standard and optimized imaging protocols for a given slice position. We rated images for quality and metal artifact size by measuring metal artifact in two orthogonal planes within the image. All metal artifacts were reduced with optimized imaging. The average metal artifact reduction for the optimized SSFP cine was 1.5+/-1.8 mm, and for the optimized GRE cine the reduction was 4.6+/-4.5 mm (P < 0.05). Quality ratings favored the optimized GRE cine. Similarly, the average metal artifact reduction for the optimized TSE images was 1.6+/-1.7 mm (P < 0.05), and quality ratings favored the optimized TSE imaging. Imaging sequences tailored to minimize metal artifact are easily created by modifying basic sequence parameters, and images are superior to standard imaging sequences in both quality and artifact size. Specifically, for optimized cine imaging a GRE sequence should be used with settings that favor short echo time, i.e. flow compensation off, weak asymmetrical echo and a relatively high receiver bandwidth. For static

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

International Nuclear Information System (INIS)

Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M

2016-01-01

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

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Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M [UCLA Radiological Sciences, Los Angeles, CA (United States)

2016-06-15

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

International Nuclear Information System (INIS)

Qiu, J; Li, H. Harlod; Zhang, T; Yang, D; Ma, F

2015-01-01

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

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Qiu, J [Taishan Medical University, Taian, Shandong (China); Washington University in St Louis, St Louis, MO (United States); Li, H. Harlod; Zhang, T; Yang, D [Washington University in St Louis, St Louis, MO (United States); Ma, F [Taishan Medical University, Taian, Shandong (China)

2015-06-15

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.

Tool development for organ dose optimization taking into account the image quality in Computed Tomography

International Nuclear Information System (INIS)

Adrien-Decoene, Camille

2015-01-01

Due to the significant rise of computed tomography (CT) exams in the past few years and the increase of the collective dose due to medical exams, dose estimation in CT imaging has become a major public health issue. However dose optimization cannot be considered without taking into account the image quality which has to be good enough for radiologists. In clinical practice, optimization is obtained through empirical index and image quality using measurements performed on specific phantoms like the CATPHAN. Based on this kind of information, it is thus difficult to correctly optimize protocols regarding organ doses and radiologist criteria. Therefore our goal is to develop a tool allowing the optimization of the patient dose while preserving the image quality needed for diagnosis. The work is divided into two main parts: (i) the development of a Monte Carlo dose simulator based on the PENELOPE code, and (ii) the assessment of an objective image quality criterion. For that purpose, the GE Lightspeed VCT 64 CT tube was modelled with information provided by the manufacturer technical note and by adapting the method proposed by Turner et al (Med. Phys. 36: 2154-2164). The axial and helical movements of the X-ray tube were then implemented into the MC tool. To improve the efficiency of the simulation, two variance reduction techniques were used: a circular and a translational splitting. The splitting algorithms allow a uniform particle distribution along the gantry path to simulate the continuous gantry motion in a discrete way. Validations were performed in homogeneous conditions using a home-made phantom and the well-known CTDI phantoms. Then, dose values were measured in CIRS ATOM anthropomorphic phantom using both optically stimulated luminescence dosimeters for point doses and XR-QA Gafchromic films for relative dose maps. Comparisons between measured and simulated values enabled us to validate the MC tool used for dosimetric purposes. Finally, organ doses for

Computationally-optimized bone mechanical modeling from high-resolution structural images.

Directory of Open Access Journals (Sweden)

Jeremy F Magland

Full Text Available Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time, which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM. To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging.

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images.

Directory of Open Access Journals (Sweden)

Yuliang Wang

Full Text Available Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.

2D sparse array transducer optimization for 3D ultrasound imaging

International Nuclear Information System (INIS)

Choi, Jae Hoon; Park, Kwan Kyu

2014-01-01

A 3D ultrasound image is desired in many medical examinations. However, the implementation of a 2D array, which is needed for a 3D image, is challenging with respect to fabrication, interconnection and cabling. A 2D sparse array, which needs fewer elements than a dense array, is a realistic way to achieve 3D images. Because the number of ways the elements can be placed in an array is extremely large, a method for optimizing the array configuration is needed. Previous research placed the target point far from the transducer array, making it impossible to optimize the array in the operating range. In our study, we focused on optimizing a 2D sparse array transducer for 3D imaging by using a simulated annealing method. We compared the far-field optimization method with the near-field optimization method by analyzing a point-spread function (PSF). The resolution of the optimized sparse array is comparable to that of the dense array.

Practical Considerations for Clinical PET/MR Imaging.

Science.gov (United States)

Galgano, Samuel; Viets, Zachary; Fowler, Kathryn; Gore, Lael; Thomas, John V; McNamara, Michelle; McConathy, Jonathan

2018-01-01

Clinical PET/MR imaging is currently performed at a number of centers around the world as part of routine standard of care. This article focuses on issues and considerations for a clinical PET/MR imaging program, focusing on routine standard-of-care studies. Although local factors influence how clinical PET/MR imaging is implemented, the approaches and considerations described here intend to apply to most clinical programs. PET/MR imaging provides many more options than PET/computed tomography with diagnostic advantages for certain clinical applications but with added complexity. A recurring theme is matching the PET/MR imaging protocol to the clinical application to balance diagnostic accuracy with efficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Clinical photoacoustic imaging of cancer

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Valluru, Keerthi S.; Willmann, Juergen K. [Dept. of Radiology, Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford (United States)

2016-08-15

Photoacoustic imaging is a hybrid technique that shines laser light on tissue and measures optically induced ultrasound signal. There is growing interest in the clinical community over this new technique and its possible clinical applications. One of the most prominent features of photoacoustic imaging is its ability to characterize tissue, leveraging differences in the optical absorption of underlying tissue components such as hemoglobin, lipids, melanin, collagen and water among many others. In this review, the state-of-the-art photoacoustic imaging techniques and some of the key outcomes pertaining to different cancer applications in the clinic are presented.

Muon tomography imaging improvement using optimized limited angle data

Science.gov (United States)

Bai, Chuanyong; Simon, Sean; Kindem, Joel; Luo, Weidong; Sossong, Michael J.; Steiger, Matthew

2014-05-01

Image resolution of muon tomography is limited by the range of zenith angles of cosmic ray muons and the flux rate at sea level. Low flux rate limits the use of advanced data rebinning and processing techniques to improve image quality. By optimizing the limited angle data, however, image resolution can be improved. To demonstrate the idea, physical data of tungsten blocks were acquired on a muon tomography system. The angular distribution and energy spectrum of muons measured on the system was also used to generate simulation data of tungsten blocks of different arrangement (geometry). The data were grouped into subsets using the zenith angle and volume images were reconstructed from the data subsets using two algorithms. One was a distributed PoCA (point of closest approach) algorithm and the other was an accelerated iterative maximal likelihood/expectation maximization (MLEM) algorithm. Image resolution was compared for different subsets. Results showed that image resolution was better in the vertical direction for subsets with greater zenith angles and better in the horizontal plane for subsets with smaller zenith angles. The overall image resolution appeared to be the compromise of that of different subsets. This work suggests that the acquired data can be grouped into different limited angle data subsets for optimized image resolution in desired directions. Use of multiple images with resolution optimized in different directions can improve overall imaging fidelity and the intended applications.

Clinical dosimetry in molecular radiotherapy: protocol optimization and clinical implementation

International Nuclear Information System (INIS)

Ferrer, Ludovic

2011-01-01

Molecular radiotherapy (mrt) consists in destructing tumour targets by radiolabelled vectors. This nuclear medicine specialty is being considered with increasing interest for example via the success achieved in the treatment of non-Hodgkin lymphomas by radioimmunotherapy. One of the keys of mrt optimization relies on the personalising of absorbed doses delivered to the patient: This is required to ascertain that irradiation is focused on tumour cells while keeping surrounding healthy tissue irradiation at an acceptable - non-toxic - level. Radiation dose evaluation in mrt requires in one hand, the spatial and temporal localization of injected radioactive sources by scintigraphic imaging, and on a second hand, the knowledge of the emitted radiation propagating media, given by CT imaging. Global accuracy relies on the accuracy of each of the steps that contribute to clinical dosimetry. There is no reference, standardized dosimetric protocol to date. Due to heterogeneous implementations, evaluation of the accuracy of the absorbed dose is a difficult task. In this thesis, we developed and evaluated different dosimetric approaches that allow us to find a relationship between the absorbed dose to the bone marrow and haematological toxicity. Besides, we built a scientific project, called DosiTest, which aims at evaluating the impact of the various step that contribute to the realization of a dosimetric study, by means of a virtual multicentric comparison based on Monte-Carlo modelling. (author) [fr

LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials.

Science.gov (United States)

Urban, Trinity; Ziegler, Erik; Lewis, Rob; Hafey, Chris; Sadow, Cheryl; Van den Abbeele, Annick D; Harris, Gordon J

2017-11-01

Oncology clinical trials have become increasingly dependent upon image-based surrogate endpoints for determining patient eligibility and treatment efficacy. As therapeutics have evolved and multiplied in number, the tumor metrics criteria used to characterize therapeutic response have become progressively more varied and complex. The growing intricacies of image-based response evaluation, together with rising expectations for rapid and consistent results reporting, make it difficult for site radiologists to adequately address local and multicenter imaging demands. These challenges demonstrate the need for advanced cancer imaging informatics tools that can help ensure protocol-compliant image evaluation while simultaneously promoting reviewer efficiency. LesionTracker is a quantitative imaging package optimized for oncology clinical trial workflows. The goal of the project is to create an open source zero-footprint viewer for image analysis that is designed to be extensible as well as capable of being integrated into third-party systems for advanced imaging tools and clinical trials informatics platforms. Cancer Res; 77(21); e119-22. ©2017 AACR . ©2017 American Association for Cancer Research.

Effective Clipart Image Vectorization through Direct Optimization of Bezigons.

Science.gov (United States)

Yang, Ming; Chao, Hongyang; Zhang, Chi; Guo, Jun; Yuan, Lu; Sun, Jian

2016-02-01

Bezigons, i.e., closed paths composed of Bézier curves, have been widely employed to describe shapes in image vectorization results. However, most existing vectorization techniques infer the bezigons by simply approximating an intermediate vector representation (such as polygons). Consequently, the resultant bezigons are sometimes imperfect due to accumulated errors, fitting ambiguities, and a lack of curve priors, especially for low-resolution images. In this paper, we describe a novel method for vectorizing clipart images. In contrast to previous methods, we directly optimize the bezigons rather than using other intermediate representations; therefore, the resultant bezigons are not only of higher fidelity compared with the original raster image but also more reasonable because they were traced by a proficient expert. To enable such optimization, we have overcome several challenges and have devised a differentiable data energy as well as several curve-based prior terms. To improve the efficiency of the optimization, we also take advantage of the local control property of bezigons and adopt an overlapped piecewise optimization strategy. The experimental results show that our method outperforms both the current state-of-the-art method and commonly used commercial software in terms of bezigon quality.

The optimal monochromatic spectral computed tomographic imaging plus adaptive statistical iterative reconstruction algorithm can improve the superior mesenteric vessel image quality

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Yin, Xiao-Ping; Zuo, Zi-Wei; Xu, Ying-Jin; Wang, Jia-Ning [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Liu, Huai-Jun, E-mail: hebeiliu@outlook.com [Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000 (China); Liang, Guang-Lu [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Gao, Bu-Lang, E-mail: browngao@163.com [Department of Medical Research, Shijiazhuang First Hospital, Shijiazhuang, Hebei, 050011 (China)

2017-04-15

Objective: To investigate the effect of the optimal monochromatic spectral computed tomography (CT) plus adaptive statistical iterative reconstruction on the improvement of the image quality of the superior mesenteric artery and vein. Materials and methods: The gemstone spectral CT angiographic data of 25 patients were reconstructed in the following three groups: 70 KeV, the optimal monochromatic imaging, and the optimal monochromatic plus 40%iterative reconstruction mode. The CT value, image noises (IN), background CT value and noises, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image scores of the vessels and surrounding tissues were analyzed. Results: In the 70 KeV, the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group, the mean scores of image quality were 3.86, 4.24 and 4.25 for the superior mesenteric artery and 3.46, 3.78 and 3.81 for the superior mesenteric vein, respectively. The image quality scores for the optimal monochromatic and the optimal monochromatic plus 40% iterative reconstruction groups were significantly greater than for the 70 KeV group (P < 0.05). The vascular CT value, image noise, background noise, CNR and SNR were significantly (P < 0.001) greater in the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group than in the 70 KeV group. The optimal monochromatic plus 40% iterative reconstruction group had significantly (P < 0.05) lower image and background noise but higher CNR and SNR than the other two groups. Conclusion: The optimal monochromatic imaging combined with 40% iterative reconstruction using low-contrast agent dosage and low injection rate can significantly improve the image quality of the superior mesenteric artery and vein.

Optimized protocols for cardiac magnetic resonance imaging in patients with thoracic metallic implants.

Science.gov (United States)

Olivieri, Laura J; Cross, Russell R; O'Brien, Kendall E; Ratnayaka, Kanishka; Hansen, Michael S

2015-09-01

Cardiac magnetic resonance (MR) imaging is a valuable tool in congenital heart disease; however patients frequently have metal devices in the chest from the treatment of their disease that complicate imaging. Methods are needed to improve imaging around metal implants near the heart. Basic sequence parameter manipulations have the potential to minimize artifact while limiting effects on image resolution and quality. Our objective was to design cine and static cardiac imaging sequences to minimize metal artifact while maintaining image quality. Using systematic variation of standard imaging parameters on a fluid-filled phantom containing commonly used metal cardiac devices, we developed optimized sequences for steady-state free precession (SSFP), gradient recalled echo (GRE) cine imaging, and turbo spin-echo (TSE) black-blood imaging. We imaged 17 consecutive patients undergoing routine cardiac MR with 25 metal implants of various origins using both standard and optimized imaging protocols for a given slice position. We rated images for quality and metal artifact size by measuring metal artifact in two orthogonal planes within the image. All metal artifacts were reduced with optimized imaging. The average metal artifact reduction for the optimized SSFP cine was 1.5+/-1.8 mm, and for the optimized GRE cine the reduction was 4.6+/-4.5 mm (P metal artifact reduction for the optimized TSE images was 1.6+/-1.7 mm (P metal artifact are easily created by modifying basic sequence parameters, and images are superior to standard imaging sequences in both quality and artifact size. Specifically, for optimized cine imaging a GRE sequence should be used with settings that favor short echo time, i.e. flow compensation off, weak asymmetrical echo and a relatively high receiver bandwidth. For static black-blood imaging, a TSE sequence should be used with fat saturation turned off and high receiver bandwidth.

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

Science.gov (United States)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

Digital radiography: optimization of image quality and dose using multi-frequency software.

Science.gov (United States)

Precht, H; Gerke, O; Rosendahl, K; Tingberg, A; Waaler, D

2012-09-01

New developments in processing of digital radiographs (DR), including multi-frequency processing (MFP), allow optimization of image quality and radiation dose. This is particularly promising in children as they are believed to be more sensitive to ionizing radiation than adults. To examine whether the use of MFP software reduces the radiation dose without compromising quality at DR of the femur in 5-year-old-equivalent anthropomorphic and technical phantoms. A total of 110 images of an anthropomorphic phantom were imaged on a DR system (Canon DR with CXDI-50 C detector and MLT[S] software) and analyzed by three pediatric radiologists using Visual Grading Analysis. In addition, 3,500 images taken of a technical contrast-detail phantom (CDRAD 2.0) provide an objective image-quality assessment. Optimal image-quality was maintained at a dose reduction of 61% with MLT(S) optimized images. Even for images of diagnostic quality, MLT(S) provided a dose reduction of 88% as compared to the reference image. Software impact on image quality was found significant for dose (mAs), dynamic range dark region and frequency band. By optimizing image processing parameters, a significant dose reduction is possible without significant loss of image quality.

Dual-energy compared to single-energy CT in pediatric imaging: a phantom study for DECT clinical guidance

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Zhu, Xiaowei; Servaes, Sabah; Darge, Kassa [The Children' s Hospital of Philadelphia, Department of Radiology, Philadelphia, PA (United States); University of Pennsylvania, The Perelman School of Medicine, Philadelphia, PA (United States); McCullough, William P. [University of Virginia Health System, Department of Radiology and Medical Imaging, Charlottesville, VA (United States); Mecca, Patricia [The Children' s Hospital of Philadelphia, Department of Radiology, Philadelphia, PA (United States)

2016-11-15

Dual-energy CT technology is available on scanners from several vendors and offers significant advantages over classic single-energy CT technology in multiple clinical applications. Many studies have detailed dual-energy CT applications in adults and several have evaluated the relative radiation dose performance of dual-energy CT in adult imaging. However, little has been published on dual-energy CT imaging in the pediatric population, and the relative dose performance of dual-energy CT imaging in the pediatric population is not well described. When evaluating dual-energy CT technology for implementation into a routine clinical pediatric imaging practice, the radiation dose implications must be considered, and when comparing relative CT dose performance, image quality must also be evaluated. Therefore the purpose of this study is to develop dual-energy CT scan protocols based on our optimized single-energy scan protocols and compare the dose. We scanned the head, chest and abdomen regions of pediatric-size anthropomorphic phantoms with contrast inserts, using our optimized single-energy clinical imaging protocols on a Siemens Flash {sup registered} CT scanner. We then scanned the phantoms in dual-energy mode using matching image-quality reference settings. The effective CT dose index volume (CTDI{sub vol}) of the scans was used as a surrogate for relative dose in comparing the single- and dual-energy scans. Additionally, we evaluated image quality using visual assessment and contrast-to-noise ratio. Dual-energy CT scans of the head and abdomen were dose-neutral for all three phantoms. Dual-energy CT scans of the chest showed a relative dose increase over the single-energy scan for 1- and 5-year-old child-based age-equivalent phantoms, ranging 11-20%. Quantitative analysis of image quality showed no statistically significant difference in image quality between the single-energy and dual-energy scans. There was no clinically significant difference in image quality by

Commentary: progress in optimization of patient dose and image quality in x-ray diagnostics

International Nuclear Information System (INIS)

Carlsson, G.A.; Chan, H.-P.

1999-01-01

X-ray diagnostics gives the largest contribution to the population dose from man-made radiation sources. Strategies for reduction of patient doses without loss of diagnostic accuracy are therefore of great interest to society and have been focussed in general terms by the ICRP (ICRP 1996) through the introduction of the concept of diagnostic reference levels. The European Union has stimulated research in the field, and, based on patient dose measurements and radiologists' appreciation of acceptable image quality, good radiographic techniques have been identified and recommended (EUR 1996a, b) for conventional screen-film imaging. These efforts have resulted in notable dose reductions in clinical practices (Hart et al 1996). In spite of 100 years of use of x-rays for diagnostics, the choice of technique parameters still relies to a great extent on experience. Scientific efforts to optimize the choice in terms of finding the parameter settings which yield sufficient image quality at the lowest possible cost in dose are still rare. True optimization requires (1) estimation of the image quality needed to make a correct diagnosis and (2) methods to investigate all possible means of achieving this image quality in order to be able to decide which of them gives the lowest dose. The paper by Tapiovaara, Sandborg and Dance published in this issue of Physics in Medicine and Biology (pages 537-559) addresses the optimization of paediatric fluoroscopy, a timely and important topic. Fluoroscopy procedures, used to guide x-ray examinations or interventional procedures, are little standardized and may result in high dose levels; radiation exposure in childhood is likely to result in a higher lifetime risk than the same exposure later in life. The authors represent an interesting mix of expertise within various scientific fields: the theory of medical imaging and assessment of image quality, the physics of diagnostic radiology and radiation dosimetry. They provide good insights

Generalized PSF modeling for optimized quantitation in PET imaging.

Science.gov (United States)

Ashrafinia, Saeed; Mohy-Ud-Din, Hassan; Karakatsanis, Nicolas A; Jha, Abhinav K; Casey, Michael E; Kadrmas, Dan J; Rahmim, Arman

2017-06-21

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUV mean and SUV max , including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUV mean bias in small tumours. Overall, the results indicate that exactly matched PSF

Edge detection in digital images using Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Marjan Kuchaki Rafsanjani

2015-11-01

Full Text Available Ant Colony Optimization (ACO is an optimization algorithm inspired by the behavior of real ant colonies to approximate the solutions of difficult optimization problems. In this paper, ACO is introduced to tackle the image edge detection problem. The proposed approach is based on the distribution of ants on an image; ants try to find possible edges by using a state transition function. Experimental results show that the proposed method compared to standard edge detectors is less sensitive to Gaussian noise and gives finer details and thinner edges when compared to earlier ant-based approaches.

Medical Image Registration by means of a Bio-Inspired Optimization Strategy

Directory of Open Access Journals (Sweden)

Hariton Costin

2012-07-01

Full Text Available Medical imaging mainly treats and processes missing, ambiguous, complementary, redundant and distorted data. Biomedical image registration is the process of geometric overlaying or alignment of two or more 2D/3D images of the same scene, taken at different time slots, from different angles, and/or by different acquisition systems. In medical practice, it is becoming increasingly important in diagnosis, treatment planning, functional studies, computer-guided therapies, and in biomedical research. Technically, image registration implies a complex optimization of different parameters, performed at local or/and global levels. Local optimization methods frequently fail because functions of the involved metrics with respect to transformation parameters are generally nonconvex and irregular. Therefore, global methods are often required, at least at the beginning of the procedure. In this paper, a new evolutionary and bio-inspired approach -- bacterial foraging optimization -- is adapted for single-slice to 3-D PET and CT multimodal image registration. Preliminary results of optimizing the normalized mutual information similarity metric validated the efficacy of the proposed method by using a freely available medical image database.

On the sensitivity of IMRT dose optimization to the mathematical form of a biological imaging-based prescription function

International Nuclear Information System (INIS)

Bowen, Stephen R; Bentzen, Soeren M; Jeraj, Robert; Flynn, Ryan T

2009-01-01

Voxel-based prescriptions of deliberately non-uniform dose distributions based on molecular imaging, so-called dose painting or theragnostic radiation therapy, require specification of a transformation that maps the image data intensities to prescribed doses. However, the functional form of this transformation is currently unknown. An investigation into the sensitivity of optimized dose distributions resulting from several possible prescription functions was conducted. Transformations between the radiotracer activity concentrations from Cu-ATSM PET images, as a surrogate of tumour hypoxia, and dose prescriptions were implemented to yield weighted distributions of prescribed dose boosts in high uptake regions. Dose escalation was constrained to reflect clinically realistic whole tumour doses and constant normal tissue doses. Optimized heterogeneous dose distributions were found by minimizing a voxel-by-voxel quadratic objective function in which all tumour voxels were given equal weight. Prescriptions based on a polynomial mapping function were found to be least constraining on their optimized plans, while prescriptions based on a sigmoid mapping function were the most demanding to deliver. A prescription formalism that fixed integral dose was less sensitive to errors in the choice of the mapping function than one that boosted integral dose. Integral doses to normal tissue and critical structures were insensitive to the shape of the prescription function. Planned target dose conformity improved with smaller beamlet dimensions until the inherent spatial resolution of the functional image was matched. Clinical implementation of dose painting depends on advances in absolute quantification of functional images and improvements in delivery techniques over smaller spatial scales.

Building Imaging Institutes of Patient Care Outcomes: Imaging as a Nidus for Innovation in Clinical Care, Research, and Education.

Science.gov (United States)

Petrou, Myria; Cronin, Paul; Altaee, Duaa K; Kelly, Aine M; Foerster, Bradley R

2018-05-01

Traditionally, radiologists have been responsible for the protocol of imaging studies, imaging acquisition, supervision of imaging technologists, and interpretation and reporting of imaging findings. In this article, we outline how radiology needs to change and adapt to a role of providing value-based, integrated health-care delivery. We believe that the way to best serve our specialty and our patients is to undertake a fundamental paradigm shift in how we practice. We describe the need for imaging institutes centered on disease entities (eg, lung cancer, multiple sclerosis) to not only optimize clinical care and patient outcomes, but also spur the development of a new educational focus, which will increase opportunities for medical trainees and other health professionals. These institutes will also serve as unique environments for testing and implementing new technologies and for generating new ideas for research and health-care delivery. We propose that the imaging institutes focus on how imaging practices-including new innovations-improve patient care outcomes within a specific disease framework. These institutes will allow our specialty to lead patient care, provide the necessary infrastructure for state-of-the art-education of trainees, and stimulate innovative and clinically relevant research. Copyright © 2018 The Association of University Radiologists. All rights reserved.

Optimization of oncological {sup 18}F-FDG PET/CT imaging based on a multiparameter analysis

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Menezes, Vinicius O., E-mail: vinicius@radtec.com.br [Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital das Clínicas da Universidade Federal de Pernambuco/Ebserh, Recife 50670-901 (Brazil); Machado, Marcos A. D. [Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital das Clínicas da Universidade Federal de Bahia/Ebserh, Salvador 40110-060 (Brazil); Queiroz, Cleiton C. [Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital Universitário Professor Alberto Antunes/Ebserh, Maceió 57072-900 (Brazil); Souza, Susana O. [Department of Physics, Universidade Federal de Sergipe, São Cristóvão 49100-000 (Brazil); D’Errico, Francesco [Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, Connecticut 06520 and School of Engineering, University of Pisa, Pisa 56126 (Italy); Namías, Mauro [Fundación Centro Diagnóstico Nuclear, Buenos Aires C1417CVE (Argentina); Larocca, Ticiana F. [Centro de Biotecnologia e Terapia Celular, São Rafael Hospital, Salvador 41253-190 (Brazil); Soares, Milena B. P. [Centro de Biotecnologia e Terapia Celular, São Rafael Hospital, Salvador 41253-190, Brazil and Fundação Oswaldo Cruz, Centro de Pesq. Gonçalo Moniz, Salvador 40296-710 (Brazil)

2016-02-15

Purpose: This paper describes a method to achieve consistent clinical image quality in {sup 18}F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60–90 kg, >90 kg) allows improved image quality with both point spread function and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations.

Task-based data-acquisition optimization for sparse image reconstruction systems

Science.gov (United States)

Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

2017-03-01

Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

Cloud Optimized Image Format and Compression

Science.gov (United States)

Becker, P.; Plesea, L.; Maurer, T.

2015-04-01

Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

Optimal energy window setting depending on the energy resolution for radionuclides used in gamma camera imaging. Planar imaging evaluation

International Nuclear Information System (INIS)

Kojima, Akihiro; Watanabe, Hiroyuki; Arao, Yuichi; Kawasaki, Masaaki; Takaki, Akihiro; Matsumoto, Masanori

2007-01-01

In this study, we examined whether the optimal energy window (EW) setting depending on an energy resolution of a gamma camera, which we previously proposed, is valid on planar scintigraphic imaging using Tl-201, Ga-67, Tc-99m, and I-123. Image acquisitions for line sources and paper sheet phantoms containing each radionuclide were performed in air and with scattering materials. For the six photopeaks excluding the Hg-201 characteristic x-rays' one, the conventional 20%-width energy window (EW20%) setting and the optimal energy window (optimal EW) setting (15%-width below 100 keV and 13%-width above 100 keV) were compared. For the Hg-201 characteristic x-rays' photopeak, the conventional on-peak EW20% setting was compared with the off-peak EW setting (73 keV-25%) and the wider off-peak EW setting (77 keV-29%). Image-count ratio (defined as the ratio of the image counts obtained with an EW and the total image counts obtained with the EW covered the whole photopeak for a line source in air), image quality, spatial resolutions (full width half maximum (FWHM) and full width tenth maximum (FWTM) values), count-profile curves, and defect-contrast values were compared between the conventional EW setting and the optimal EW setting. Except for the Hg-201 characteristic x-rays, the image-count ratios were 94-99% for the EW20% setting, but 78-89% for the optimal EW setting. However, the optimal EW setting reduced scatter fraction (defined as the scattered-to-primary counts ratio) effectively, as compared with the EW20% setting. Consequently, all the images with the optimal EW setting gave better image quality than ones with the EW20% setting. For the Hg-201 characteristic x-rays, the off-peak EW setting showed great improvement in image quality in comparison with the EW20% setting and the wider off-peak EW setting gave the best results. In conclusion, from our planar imaging study it was shown that although the optimal EW setting proposed by us gives less image-count ratio by

Practical evaluation of clinical image quality (4). Determination of image quality in digital radiography system

International Nuclear Information System (INIS)

Katayama, Reiji

2016-01-01

Recently, for medical imaging, digital radiography systems are widely used in clinical practices. However, a study in the past reported that a patient radiation exposure level by digital radiography is in fact not lower than that by analog radiography system. High level of attention needs to be paid for over-exposure when using the conventional analog radiography with a screen and a film, as it results in high density of the film. However, for digital radiography systems, since the automatic adjusting function of image density is equipped with them, no attention for radiation dose need to be paid. Thus technologists tend to be careless and results in higher chance for over-exposure. Current digital radiography systems are high-performance in the image properties and capable of patient dose reduction. Especially, the image quality of the flat panel detector system is recognized, higher than that of the computed radiography system by imaging plates, in both objective and subjective evaluations. Therefore, we technologists are responsible for optimizing the balance between the image quality of the digital radiogram and the radiation dose required for each case. Moreover, it is also required for us as medical technologists to make effective use of such evaluation result of medical images for patients. (author)

Ultrafuzziness Optimization Based on Type II Fuzzy Sets for Image Thresholding

Directory of Open Access Journals (Sweden)

Hudan Studiawan

2010-11-01

Full Text Available Image thresholding is one of the processing techniques to provide high quality preprocessed image. Image vagueness and bad illumination are common obstacles yielding in a poor image thresholding output. By assuming image as fuzzy sets, several different fuzzy thresholding techniques have been proposed to remove these obstacles during threshold selection. In this paper, we proposed an algorithm for thresholding image using ultrafuzziness optimization to decrease uncertainty in fuzzy system by common fuzzy sets like type II fuzzy sets. Optimization was conducted by involving ultrafuzziness measurement for background and object fuzzy sets separately. Experimental results demonstrated that the proposed image thresholding method had good performances for images with high vagueness, low level contrast, and grayscale ambiguity.

Automatic selection of optimal cardiac-phase in coronary CT angiography. Its clinical usefulness for patients with atrial fibrillation

International Nuclear Information System (INIS)

Matsumoto, Ryota; Narita, Hiroshi; Anno, Hirofumi; Ida, Yoshihiro; Sanda, Yoshihiro; Katada, Kazuhiro; Motoyama, Sadako; Sarai, Masayoshi; Tsuyuki, Masaharu

2008-01-01

The optimal cardiac phases for coronary CT angiography (CTA) are end-systole and mid-diastole, in which cardiac movement is slow. In conventional methods, these cardiac phases are determined by visual selection. We have compared the images in the optimal cardiac phases that were selected by the conventional method and cardiac-phase search software (Phase Navi), and examined the clinical usefulness of Phase Navi in patients with atrial fibrillation. The subjects were 38 patients (regular rhythm: 20, atrial fibrillation: 18). The continuity scores of patients with regular rhythm (Phase Navi, conventional methods) were 2.4±0.3-2.5±0.3 in end-systole and 2.4±0.5-2.4±0.4 in mid-diastole. The scores of patients with atrial fibrillation (Phase Navi, conventional methods) were 2.3±0.4-2.3±0.4 in end-systole, and 2.2±0.5-2.1±0.6 in mid-diastole. Because the continuity scores of the optimal images from Phase Navi were similar to those from the conventional method, Phase Navi had clinical usefulness in patients with atrial fibrillation. (author)

Selecting optimal monochromatic level with spectral CT imaging for improving imaging quality in hepatic venography

International Nuclear Information System (INIS)

Sun Jun; Luo Xianfu; Wang Shou'an; Wang Jun; Sun Jiquan; Wang Zhijun; Wu Jingtao

2013-01-01

Objective: To investigate the effect of spectral CT monochromatic images for improving imaging quality in hepatic venography. Methods: Thirty patients underwent spectral CT examination on a GE Discovery CT 750 HD scanner. During portal phase, 1.25 mm slice thickness polychromatic images and optimal monochromatic images were obtained, and volume rendering and maximum intensity projection were created to show the hepatic veins respectively. The overall imaging quality was evaluated on a five-point scale by two radiologists. Inter-observer agreement in subjective image quality grading was assessed by Kappa statistics. Paired-sample t test were used to compare hepatic vein attenuation, hepatic parenchyma attenuation, CT value difference between the hepatic vein and the liver parenchyma, image noise, vein-to-liver contrast-to-noise ratio (CNR), the image quality score of hepatic venography between the two image data sets. Results: The monochromatic images at 50 keV were found to demonstrate the best CNR for hepatic vein.The hepatic vein attenuation [(329 ± 47) HU], hepatic parenchyma attenuation [(178 ± 33) HU], CT value difference between the hepatic vein and the liver parenchyma [(151 ± 33) HU], image noise (17.33 ± 4.18), CNR (9.13 ± 2.65), the image quality score (4.2 ± 0.6) of optimal monochromatic images were significantly higher than those of polychromatic images [(149 ± 18) HU], [(107 ± 14) HU], [(43 ±11) HU], 12.55 ± 3.02, 3.53 ± 1.03, 3.1 ± 0.8 (t values were 24.79, 13.95, 18.85, 9.07, 13.25 and 12.04, respectively, P < 0.01). In the comparison of image quality, Kappa value was 0.81 with optimal monochromatic images and 0.69 with polychromatic images. Conclusion: Monochromatic images of spectral CT could improve CNR for displaying hepatic vein and improve the image quality compared to the conventional polychromatic images. (authors)

An MR Brain Images Classifier System via Particle Swarm Optimization and Kernel Support Vector Machine

Directory of Open Access Journals (Sweden)

Yudong Zhang

2013-01-01

Full Text Available Automated abnormal brain detection is extremely of importance for clinical diagnosis. Over last decades numerous methods had been presented. In this paper, we proposed a novel hybrid system to classify a given MR brain image as either normal or abnormal. The proposed method first employed digital wavelet transform to extract features then used principal component analysis (PCA to reduce the feature space. Afterwards, we constructed a kernel support vector machine (KSVM with RBF kernel, using particle swarm optimization (PSO to optimize the parameters C and σ. Fivefold cross-validation was utilized to avoid overfitting. In the experimental procedure, we created a 90 images dataset brain downloaded from Harvard Medical School website. The abnormal brain MR images consist of the following diseases: glioma, metastatic adenocarcinoma, metastatic bronchogenic carcinoma, meningioma, sarcoma, Alzheimer, Huntington, motor neuron disease, cerebral calcinosis, Pick’s disease, Alzheimer plus visual agnosia, multiple sclerosis, AIDS dementia, Lyme encephalopathy, herpes encephalitis, Creutzfeld-Jakob disease, and cerebral toxoplasmosis. The 5-folded cross-validation classification results showed that our method achieved 97.78% classification accuracy, higher than 86.22% by BP-NN and 91.33% by RBF-NN. For the parameter selection, we compared PSO with those of random selection method. The results showed that the PSO is more effective to build optimal KSVM.

Optimized Quasi-Interpolators for Image Reconstruction.

Science.gov (United States)

Sacht, Leonardo; Nehab, Diego

2015-12-01

We propose new quasi-interpolators for the continuous reconstruction of sampled images, combining a narrowly supported piecewise-polynomial kernel and an efficient digital filter. In other words, our quasi-interpolators fit within the generalized sampling framework and are straightforward to use. We go against standard practice and optimize for approximation quality over the entire Nyquist range, rather than focusing exclusively on the asymptotic behavior as the sample spacing goes to zero. In contrast to previous work, we jointly optimize with respect to all degrees of freedom available in both the kernel and the digital filter. We consider linear, quadratic, and cubic schemes, offering different tradeoffs between quality and computational cost. Experiments with compounded rotations and translations over a range of input images confirm that, due to the additional degrees of freedom and the more realistic objective function, our new quasi-interpolators perform better than the state of the art, at a similar computational cost.

Optimal Image Data Compression For Whole Slide Images

Directory of Open Access Journals (Sweden)

J. Isola

2016-06-01

Differences in WSI file sizes of scanned images deemed “visually lossless” were significant. If we set Hamamatsu Nanozoomer .NDPI file size (using its default “jpeg80 quality” as 100%, the size of a “visually lossless” JPEG2000 file was only 15-20% of that. Comparisons to Aperio and 3D-Histech files (.svs and .mrxs at their default settings yielded similar results. A further optimization of JPEG2000 was done by treating empty slide area as uniform white-grey surface, which could be maximally compressed. Using this algorithm, JPEG2000 file sizes were only half, or even smaller, of original JPEG2000. Variation was due to the proportion of empty slide area on the scan. We anticipate that wavelet-based image compression methods, such as JPEG2000, have a significant advantage in saving storage costs of scanned whole slide image. In routine pathology laboratories applying WSI technology widely to their histology material, absolute cost savings can be substantial.  

An Image Morphing Technique Based on Optimal Mass Preserving Mapping

Science.gov (United States)

Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen

2013-01-01

Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods. PMID:17547128

Dual-energy compared to single-energy CT in pediatric imaging: a phantom study for DECT clinical guidance

International Nuclear Information System (INIS)

Zhu, Xiaowei; Servaes, Sabah; Darge, Kassa; McCullough, William P.; Mecca, Patricia

2016-01-01

Dual-energy CT technology is available on scanners from several vendors and offers significant advantages over classic single-energy CT technology in multiple clinical applications. Many studies have detailed dual-energy CT applications in adults and several have evaluated the relative radiation dose performance of dual-energy CT in adult imaging. However, little has been published on dual-energy CT imaging in the pediatric population, and the relative dose performance of dual-energy CT imaging in the pediatric population is not well described. When evaluating dual-energy CT technology for implementation into a routine clinical pediatric imaging practice, the radiation dose implications must be considered, and when comparing relative CT dose performance, image quality must also be evaluated. Therefore the purpose of this study is to develop dual-energy CT scan protocols based on our optimized single-energy scan protocols and compare the dose. We scanned the head, chest and abdomen regions of pediatric-size anthropomorphic phantoms with contrast inserts, using our optimized single-energy clinical imaging protocols on a Siemens Flash "r"e"g"i"s"t"e"r"e"d CT scanner. We then scanned the phantoms in dual-energy mode using matching image-quality reference settings. The effective CT dose index volume (CTDI_v_o_l) of the scans was used as a surrogate for relative dose in comparing the single- and dual-energy scans. Additionally, we evaluated image quality using visual assessment and contrast-to-noise ratio. Dual-energy CT scans of the head and abdomen were dose-neutral for all three phantoms. Dual-energy CT scans of the chest showed a relative dose increase over the single-energy scan for 1- and 5-year-old child-based age-equivalent phantoms, ranging 11-20%. Quantitative analysis of image quality showed no statistically significant difference in image quality between the single-energy and dual-energy scans. There was no clinically significant difference in image quality

A data grid for imaging-based clinical trials

Science.gov (United States)

Zhou, Zheng; Chao, Sander S.; Lee, Jasper; Liu, Brent; Documet, Jorge; Huang, H. K.

2007-03-01

Clinical trials play a crucial role in testing new drugs or devices in modern medicine. Medical imaging has also become an important tool in clinical trials because images provide a unique and fast diagnosis with visual observation and quantitative assessment. A typical imaging-based clinical trial consists of: 1) A well-defined rigorous clinical trial protocol, 2) a radiology core that has a quality control mechanism, a biostatistics component, and a server for storing and distributing data and analysis results; and 3) many field sites that generate and send image studies to the radiology core. As the number of clinical trials increases, it becomes a challenge for a radiology core servicing multiple trials to have a server robust enough to administrate and quickly distribute information to participating radiologists/clinicians worldwide. The Data Grid can satisfy the aforementioned requirements of imaging based clinical trials. In this paper, we present a Data Grid architecture for imaging-based clinical trials. A Data Grid prototype has been implemented in the Image Processing and Informatics (IPI) Laboratory at the University of Southern California to test and evaluate performance in storing trial images and analysis results for a clinical trial. The implementation methodology and evaluation protocol of the Data Grid are presented.

SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

International Nuclear Information System (INIS)

Weir, V; Zhang, J

2015-01-01

Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols

SU-E-I-23: A General KV Constrained Optimization of CNR for CT Abdominal Imaging

Energy Technology Data Exchange (ETDEWEB)

Weir, V; Zhang, J [University of Kentucky, Lexington, KY (United States)

2015-06-15

Purpose: While Tube current modulation has been well accepted for CT dose reduction, kV adjusting in clinical settings is still at its early stage. This is mainly due to the limited kV options of most current CT scanners. kV adjusting can potentially reduce radiation dose and optimize image quality. This study is to optimize CT abdomen imaging acquisition based on the assumption of a continuous kV, with the goal to provide the best contrast to noise ratio (CNR). Methods: For a given dose (CTDIvol) level, the CNRs at different kV and pitches were measured with an ACR GAMMEX phantom. The phantom was scanned in a Siemens Sensation 64 scanner and a GE VCT 64 scanner. A constrained mathematical optimization was used to find the kV which led to the highest CNR for the anatomy and pitch setting. Parametric equations were obtained from polynomial fitting of plots of kVs vs CNRs. A suitable constraint region for optimization was chosen. Subsequent optimization yielded a peak CNR at a particular kV for different collimations and pitch setting. Results: The constrained mathematical optimization approach yields kV of 114.83 and 113.46, with CNRs of 1.27 and 1.11 at the pitch of 1.2 and 1.4, respectively, for the Siemens Sensation 64 scanner with the collimation of 32 x 0.625mm. An optimized kV of 134.25 and 1.51 CNR is obtained for a GE VCT 64 slice scanner with a collimation of 32 x 0.625mm and a pitch of 0.969. At 0.516 pitch and 32 x 0.625 mm an optimized kV of 133.75 and a CNR of 1.14 was found for the GE VCT 64 slice scanner. Conclusion: CNR in CT image acquisition can be further optimized with a continuous kV option instead of current discrete or fixed kV settings. A continuous kV option is a key for individualized CT protocols.

Differential evolution optimization combined with chaotic sequences for image contrast enhancement

Energy Technology Data Exchange (ETDEWEB)

Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Sauer, Joao Guilherme [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: joao.sauer@gmail.com; Rudek, Marcelo [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: marcelo.rudek@pucpr.br

2009-10-15

Evolutionary Algorithms (EAs) are stochastic and robust meta-heuristics of evolutionary computation field useful to solve optimization problems in image processing applications. Recently, as special mechanism to avoid being trapped in local minimum, the ergodicity property of chaotic sequences has been used in various designs of EAs. Three differential evolution approaches based on chaotic sequences using logistic equation for image enhancement process are proposed in this paper. Differential evolution is a simple yet powerful evolutionary optimization algorithm that has been successfully used in solving continuous problems. The proposed chaotic differential evolution schemes have fast convergence rate but also maintain the diversity of the population so as to escape from local optima. In this paper, the image contrast enhancement is approached as a constrained nonlinear optimization problem. The objective of the proposed chaotic differential evolution schemes is to maximize the fitness criterion in order to enhance the contrast and detail in the image by adapting the parameters using a contrast enhancement technique. The proposed chaotic differential evolution schemes are compared with classical differential evolution to two testing images. Simulation results on three images show that the application of chaotic sequences instead of random sequences is a possible strategy to improve the performance of classical differential evolution optimization algorithm.

Image-optimized Coronal Magnetic Field Models

Energy Technology Data Exchange (ETDEWEB)

Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M., E-mail: shaela.i.jones-mecholsky@nasa.gov, E-mail: shaela.i.jonesmecholsky@nasa.gov [NASA Goddard Space Flight Center, Code 670, Greenbelt, MD 20771 (United States)

2017-08-01

We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work, we presented early tests of the method, which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper, we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane and the effect on the outcome of the optimization of errors in the localization of constraints. We find that substantial improvement in the model field can be achieved with these types of constraints, even when magnetic features in the images are located outside of the image plane.

Image-Optimized Coronal Magnetic Field Models

Science.gov (United States)

Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M.

2017-01-01

We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work we presented early tests of the method which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane, and the effect on the outcome of the optimization of errors in localization of constraints. We find that substantial improvement in the model field can be achieved with this type of constraints, even when magnetic features in the images are located outside of the image plane.

Highly accelerated cardiovascular MR imaging using many channel technology: concepts and clinical applications

International Nuclear Information System (INIS)

Niendorf, Thoralf; Sodickson, Daniel K.

2008-01-01

Cardiovascular magnetic resonance imaging (CVMRI) is of proven clinical value in the non-invasive imaging of cardiovascular diseases. CVMRI requires rapid image acquisition, but acquisition speed is fundamentally limited in conventional MRI. Parallel imaging provides a means for increasing acquisition speed and efficiency. However, signal-to-noise (SNR) limitations and the limited number of receiver channels available on most MR systems have in the past imposed practical constraints, which dictated the use of moderate accelerations in CVMRI. High levels of acceleration, which were unattainable previously, have become possible with many-receiver MR systems and many-element, cardiac-optimized RF-coil arrays. The resulting imaging speed improvements can be exploited in a number of ways, ranging from enhancement of spatial and temporal resolution to efficient whole heart coverage to streamlining of CVMRI work flow. In this review, examples of these strategies are provided, following an outline of the fundamentals of the highly accelerated imaging approaches employed in CVMRI. Topics discussed include basic principles of parallel imaging; key requirements for MR systems and RF-coil design; practical considerations of SNR management, supported by multi-dimensional accelerations, 3D noise averaging and high field imaging; highly accelerated clinical state-of-the art cardiovascular imaging applications spanning the range from SNR-rich to SNR-limited; and current trends and future directions. (orig.)

Optimized T1- and T2-weighted volumetric brain imaging as a diagnostic tool in very preterm neonates

International Nuclear Information System (INIS)

Nossin-Manor, Revital; Chung, Andrew D.; Morris, Drew; Thomas, Bejoy; Shroff, Manohar M.; Soares-Fernandes, Joao P.; Cheng, Hai-Ling M.; Whyte, Hilary E.A.; Taylor, Margot J.; Sled, John G.

2011-01-01

T1- and T2-W MR sequences used for obtaining diagnostic information and morphometric measurements in the neonatal brain are frequently acquired using different imaging protocols. Optimizing one protocol for obtaining both kinds of information is valuable. To determine whether high-resolution T1- and T2-W volumetric sequences optimized for preterm brain imaging could provide both diagnostic and morphometric value. Thirty preterm neonates born between 24 and 32 weeks' gestational age were scanned during the first 2 weeks after birth. T1- and T2-W high-resolution sequences were optimized in terms of signal-to-noise ratio, contrast-to-noise ratio and scan time and compared to conventional spin-echo-based sequences. No differences were found between conventional and high-resolution T1-W sequences for diagnostic confidence, image quality and motion artifacts. A preference for conventional over high-resolution T2-W sequences for image quality was observed. High-resolution T1 images provided better delineation of thalamic myelination and the superior temporal sulcus. No differences were found for detection of myelination and sulcation using conventional and high-resolution T2-W images. High-resolution T1- and T2-W volumetric sequences can be used in clinical MRI in the very preterm brain to provide both diagnostic and morphometric information. (orig.)

MR Imaging of the Triangular Fibrocartilage Complex.

Science.gov (United States)

Cody, Michael E; Nakamura, David T; Small, Kirstin M; Yoshioka, Hiroshi

2015-08-01

MR imaging has emerged as the mainstay in imaging internal derangement of the soft tissues of the musculoskeletal system largely because of superior contrast resolution. The complex geometry and diminutive size of the triangular fibrocartilage complex (TFCC) and its constituent structures can make optimal imaging of the TFCC challenging; therefore, production of clinically useful images requires careful optimization of image acquisition parameters. This article provides a foundation for advanced TFCC imaging including factors to optimize magnetic resonance images, arthrography, detailed anatomy, and classification of injury. In addition, clinical presentations and treatments for TFCC injury are briefly considered. Copyright © 2015 Elsevier Inc. All rights reserved.

An imaging informatics-based ePR (electronic patient record) system for providing decision support in evaluating dose optimization in stroke rehabilitation

Science.gov (United States)

Liu, Brent J.; Winstein, Carolee; Wang, Ximing; Konersman, Matt; Martinez, Clarisa; Schweighofer, Nicolas

2012-02-01

Stroke is one of the major causes of death and disability in America. After stroke, about 65% of survivors still suffer from severe paresis, while rehabilitation treatment strategy after stroke plays an essential role in recovery. Currently, there is a clinical trial (NIH award #HD065438) to determine the optimal dose of rehabilitation for persistent recovery of arm and hand paresis. For DOSE (Dose Optimization Stroke Evaluation), laboratory-based measurements, such as the Wolf Motor Function test, behavioral questionnaires (e.g. Motor Activity Log-MAL), and MR, DTI, and Transcranial Magnetic Stimulation (TMS) imaging studies are planned. Current data collection processes are tedious and reside in various standalone systems including hardcopy forms. In order to improve the efficiency of this clinical trial and facilitate decision support, a web-based imaging informatics system has been implemented together with utilizing mobile devices (eg, iPAD, tablet PC's, laptops) for collecting input data and integrating all multi-media data into a single system. The system aims to provide clinical imaging informatics management and a platform to develop tools to predict the treatment effect based on the imaging studies and the treatment dosage with mathematical models. Since there is a large amount of information to be recorded within the DOSE project, the system provides clinical data entry through mobile device applications thus allowing users to collect data at the point of patient interaction without typing into a desktop computer, which is inconvenient. Imaging analysis tools will also be developed for structural MRI, DTI, and TMS imaging studies that will be integrated within the system and correlated with the clinical and behavioral data. This system provides a research platform for future development of mathematical models to evaluate the differences between prediction and reality and thus improve and refine the models rapidly and efficiently.

The PWR loading pattern optimization in X-IMAGE

International Nuclear Information System (INIS)

Stevens, J.G.; Smith, K.S.; Rempe, K.R.; Downar, T.J.

1993-01-01

The design of reactor core loading patterns is difficult due to the staggering number of patterns. The integer nature and nonlinear neutronic response of core design preclude simple prescriptions for generation of the feasible patterns, much less optimization among feasible candidates. Fortunately, recent developments in optimization, graphical user interfaces (GUIs), and the speed and low cost of engineering workstations combine to make loading pattern automation possible. The optimization module SIMAN has been added to X-IMAGE to automatically generate high-quality core loadings

Information theoretic methods for image processing algorithm optimization

Science.gov (United States)

Prokushkin, Sergey F.; Galil, Erez

2015-01-01

Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning

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Li Jun-Bao

2017-06-01

Full Text Available Magnetic Resonance Super-resolution Imaging Measurement (MRIM is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.

Clinical blood pool MR Imaging

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Leiner, Tim [Maastrich University Medical Center (Netherlands). Dept. of Radiology; Goyen, Martin [University Medical Center Hamburg-Eppendorf (Germany); Rohrer, Mathias [Bayer Schering Pharma AG, Berlin (Germany). European Business Unit Diagnostic Imaging; Schoenberg, Stefan O. (eds.) [University Hospital Mannheim Medical Faculty Mannheim - Heidelberg Univ. (Germany). Dept. of Clinical Radiology and Nuclear Medicine

2008-07-01

Clinical Blood Pool MR Imaging - This excellent treatise on Vasovist {sup registered} created by a team of exceptional faculty who are pioneers in MR Angiography covers the basic techniques, safety, efficacy, image processing and pharmaco-economic details to successfully implement a new level of MRA image quality with this new contrast agent. Martin Prince, Cornell University, New York The editors and authors have made groundbreaking contributions towards establishing MR angiography in various investigative settings, rendering it more precise and applying it for diverse indications. The work presented here is founded upon the extensive experience of the editors, as well as the broad range of experience from other scientific working groups. Maximilian Reiser, Ludwig Maximilian University, Munich Vasovist {sup registered} (Gadofosveset), worldwide the first blood pool agent, has only recently become available for clinical use, but has already gained wide acceptance as a tool to improve magnetic resonance angiography. This book presents the first in-depth introduction to the basic physicochemical aspects of the agent, the application of Vasovist {sup registered} in clinical MRA, as well as potential clinical applications beyond MRA and patient management-related aspects. The first part of the book explains basic and technical properties of the agent and the differences of Vasovist {sup registered} compared to currently available extracellular agents. The second part contains detailed chapters on safety and efficacy. In the third part the focus is on MR angiographic applications, and in the fourth part of the book potential clinical fields beyond MRA are explored. All clinical chapters feature ready-to-use clinical protocols and a series of take home messages that concisely summarize the current role of blood pool imaging for each specific indication. (orig.)

An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Kai Hu

2015-01-01

Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.

Optimal image resolution for digital storage of radiotherapy-planning images

International Nuclear Information System (INIS)

Baba, Yuji; Furusawa, Mitsuhiro; Murakami, Ryuji; Baba, Takashi; Yokoyama, Toshimi; Nishimura, Ryuichi; Takahashi, Mutsumasa

1998-01-01

Purpose: To evaluate the quality of digitized radiation-planning images at different resolution and to determine the optimal resolution for digital storage. Methods and Materials: Twenty-five planning films were scanned and digitized using a film scanner at a resolution of 72 dots per inch (dpi) with 8-bit depth. The resolution of scanned images was reduced to 48, 36, 24, and 18 dpi using computer software. Image qualities of these five images (72, 48, 36, 24, and 18 dpi) were evaluated and given scores (4 = excellent; 3 = good; 2 = fair; and 1 = poor) by three radiation oncologists. An image data compression algorithm by the Joint Photographic Experts Group (JPEG) (not reversible and some information will be lost) was also evaluated. Results: The scores of digitized images with 72, 48, 36, 24, and 17 dpi resolution were 3.8 ± 0.3, 3.5 ± 0.3, 3.3 ± 0.5, 2.7 ± 0.5, and 1.6 ± 0.3, respectively. The quality of 36-dpi images were definitely worse compared to 72-dpi images, but were good enough as planning films. Digitized planning images with 72- and 36-dpi resolution requires about 800 and 200 KBytes, respectively. The JPEG compression algorithm produces little degradation in 36-dpi images at compression ratios of 5:1. Conclusion: The quality of digitized images with 36-dpi resolution was good enough as radiation-planning images and required 200 KBytes/image

Lymphoma: current status of clinical and preclinical imaging with radiolabeled antibodies

Energy Technology Data Exchange (ETDEWEB)

England, Christopher G. [University of Wisconsin School of Medicine and Public Health, Department of Medical Physics, Madison, WI (United States); Rui, Lixin [University of Wisconsin School of Medicine and Public Health, Department of Medicine, Madison, WI (United States); University of Wisconsin School of Medicine and Public Health, Carbone Cancer Center, Madison, WI (United States); Cai, Weibo [University of Wisconsin School of Medicine and Public Health, Department of Medical Physics, Madison, WI (United States); University of Wisconsin School of Medicine and Public Health, Carbone Cancer Center, Madison, WI (United States); University of Wisconsin School of Medicine and Public Health, Department of Radiology, Madison, WI (United States)

2017-03-15

Lymphoma is a complex disease that arises from cells of the immune system with an intricate pathology. While lymphoma may be classified as Hodgkin or non-Hodgkin, each type of tumor is genetically and phenotypically different and highly invasive tissue biopsies are the only method to investigate these differences. Noninvasive imaging strategies, such as immunoPET, can provide a vital insight into disease staging, monitoring treatment response in patients, and dose planning in radioimmunotherapy. ImmunoPET imaging with radiolabeled antibody-based tracers may also assist physicians in optimizing treatment strategies and enhancing patient stratification. Currently, there are two common biomarkers for molecular imaging of lymphoma, CD20 and CD30, both of which have been considered for investigation in preclinical imaging studies. In this review, we examine the current status of both preclinical and clinical imaging of lymphoma using radiolabeled antibodies. Additionally, we briefly investigate the role of radiolabeled antibodies in lymphoma therapy. As radiolabeled antibodies play critical roles in both imaging and therapy of lymphoma, the development of novel antibodies and the discovery of new biomarkers may greatly affect lymphoma imaging and therapy in the future. (orig.)

Lymphoma: current status of clinical and preclinical imaging with radiolabeled antibodies

International Nuclear Information System (INIS)

England, Christopher G.; Rui, Lixin; Cai, Weibo

2017-01-01

Lymphoma is a complex disease that arises from cells of the immune system with an intricate pathology. While lymphoma may be classified as Hodgkin or non-Hodgkin, each type of tumor is genetically and phenotypically different and highly invasive tissue biopsies are the only method to investigate these differences. Noninvasive imaging strategies, such as immunoPET, can provide a vital insight into disease staging, monitoring treatment response in patients, and dose planning in radioimmunotherapy. ImmunoPET imaging with radiolabeled antibody-based tracers may also assist physicians in optimizing treatment strategies and enhancing patient stratification. Currently, there are two common biomarkers for molecular imaging of lymphoma, CD20 and CD30, both of which have been considered for investigation in preclinical imaging studies. In this review, we examine the current status of both preclinical and clinical imaging of lymphoma using radiolabeled antibodies. Additionally, we briefly investigate the role of radiolabeled antibodies in lymphoma therapy. As radiolabeled antibodies play critical roles in both imaging and therapy of lymphoma, the development of novel antibodies and the discovery of new biomarkers may greatly affect lymphoma imaging and therapy in the future. (orig.)

Simultaneous topography and recognition imaging: physical aspects and optimal imaging conditions

International Nuclear Information System (INIS)

Preiner, Johannes; Ebner, Andreas; Zhu Rong; Hinterdorfer, Peter; Chtcheglova, Lilia

2009-01-01

Simultaneous topography and recognition imaging (TREC) allows for the investigation of receptor distributions on natural biological surfaces under physiological conditions. Based on atomic force microscopy (AFM) in combination with a cantilever tip carrying a ligand molecule, it enables us to sense topography and recognition of receptor molecules simultaneously with nanometre accuracy. In this study we introduce optimized handling conditions and investigate the physical properties of the cantilever-tip-sample ensemble, which is essential for the interpretation of the experimental data gained from this technique. In contrast to conventional AFM methods, TREC is based on a more sophisticated feedback loop, which enables us to discriminate topographical contributions from recognition events in the AFM cantilever motion. The features of this feedback loop were investigated through a detailed analysis of the topography and recognition data obtained on a model protein system. Single avidin molecules immobilized on a mica substrate were imaged with an AFM tip functionalized with a biotinylated IgG. A simple procedure for adjusting the optimal amplitude for TREC imaging is described by exploiting the sharp localization of the TREC signal within a small range of oscillation amplitudes. This procedure can also be used for proving the specificity of the detected receptor-ligand interactions. For understanding and eliminating topographical crosstalk in the recognition images we developed a simple theoretical model, which nicely explains its origin and its dependence on the excitation frequency.

Medical imaging using ionizing radiation: Optimization of dose and image quality in fluoroscopy

International Nuclear Information System (INIS)

Jones, A. Kyle; Balter, Stephen; Rauch, Phillip; Wagner, Louis K.

2014-01-01

The 2012 Summer School of the American Association of Physicists in Medicine (AAPM) focused on optimization of the use of ionizing radiation in medical imaging. Day 2 of the Summer School was devoted to fluoroscopy and interventional radiology and featured seven lectures. These lectures have been distilled into a single review paper covering equipment specification and siting, equipment acceptance testing and quality control, fluoroscope configuration, radiation effects, dose estimation and measurement, and principles of flat panel computed tomography. This review focuses on modern fluoroscopic equipment and is comprised in large part of information not found in textbooks on the subject. While this review does discuss technical aspects of modern fluoroscopic equipment, it focuses mainly on the clinical use and support of such equipment, from initial installation through estimation of patient dose and management of radiation effects. This review will be of interest to those learning about fluoroscopy, to those wishing to update their knowledge of modern fluoroscopic equipment, to those wishing to deepen their knowledge of particular topics, such as flat panel computed tomography, and to those who support fluoroscopic equipment in the clinic

Optimizer convergence and local minima errors and their clinical importance

International Nuclear Information System (INIS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-01-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization

Natural Image Enhancement Using a Biogeography Based Optimization Enhanced with Blended Migration Operator

Directory of Open Access Journals (Sweden)

J. Jasper

2014-01-01

Full Text Available This paper addresses a novel and efficient algorithm for solving optimization problem in image processing applications. Image enhancement (IE is one of the complex optimization problems in image processing. The main goal of this paper is to enhance color images such that the eminence of the image is more suitable than the original image from the perceptual viewpoint of human. Traditional methods require prior knowledge of the image to be enhanced, whereas the aim of the proposed biogeography based optimization (BBO enhanced with blended migration operator (BMO algorithm is to maximize the objective function in order to enhance the image contrast by maximizing the parameters like edge intensity, edge information, and entropy. Experimental results are compared with the current state-of-the-art approaches and indicate the superiority of the proposed technique in terms of subjective and objective evaluation.

3-D brain image registration using optimal morphological processing

International Nuclear Information System (INIS)

Loncaric, S.; Dhawan, A.P.

1994-01-01

The three-dimensional (3-D) registration of Magnetic Resonance (MR) and Positron Emission Tomographic (PET) images of the brain is important for analysis of the human brain and its diseases. A procedure for optimization of (3-D) morphological structuring elements, based on a genetic algorithm, is presented in the paper. The registration of the MR and PET images is done by means of a registration procedure in two major phases. In the first phase, the Iterative Principal Axis Transform (IPAR) is used for initial registration. In the second phase, the optimal shape description method based on the Morphological Signature Transform (MST) is used for final registration. The morphological processing is used to improve the accuracy of the basic IPAR method. The brain ventricle is used as a landmark for MST registration. A near-optimal structuring element obtained by means of a genetic algorithm is used in MST to describe the shape of the ventricle. The method has been tested on the set of brain images demonstrating the feasibility of approach. (author). 11 refs., 3 figs

GPU based Monte Carlo for PET image reconstruction: parameter optimization

International Nuclear Information System (INIS)

Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.

2011-01-01

This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)

Image Registration for PET/CT and CT Images with Particle Swarm Optimization

International Nuclear Information System (INIS)

Lee, Hak Jae; Kim, Yong Kwon; Lee, Ki Sung; Choi, Jong Hak; Kim, Chang Kyun; Moon, Guk Hyun; Joo, Sung Kwan; Kim, Kyeong Min; Cheon, Gi Jeong

2009-01-01

Image registration is a fundamental task in image processing used to match two or more images. It gives new information to the radiologists by matching images from different modalities. The objective of this study is to develop 2D image registration algorithm for PET/CT and CT images acquired by different systems at different times. We matched two CT images first (one from standalone CT and the other from PET/CT) that contain affluent anatomical information. Then, we geometrically transformed PET image according to the results of transformation parameters calculated by the previous step. We have used Affine transform to match the target and reference images. For the similarity measure, mutual information was explored. Use of particle swarm algorithm optimized the performance by finding the best matched parameter set within a reasonable amount of time. The results show good agreements of the images between PET/CT and CT. We expect the proposed algorithm can be used not only for PET/CT and CT image registration but also for different multi-modality imaging systems such as SPECT/CT, MRI/PET and so on.

Physical performance and image optimization of megavoltage cone-beam CT

Energy Technology Data Exchange (ETDEWEB)

Morin, Olivier; Aubry, Jean-Francois; Aubin, Michele; Chen, Josephine; Descovich, Martina; Hashemi, Ali-Bani; Pouliot, Jean [Department of Radiation Oncology, Helen Diller Comprehensive Cancer Center, University of California San Francisco, San Francisco, California 94143 and UCSF/UC Berkeley Joint Graduate Group in Bioengineering, San Francisco, California 94158 (United States); Department of Radiation Oncology, Helen Diller Comprehensive Cancer Center, University of California San Francisco, San Francisco, California 94143 (United States); Siemens Oncology Care Systems, Concord, California 94520 (United States); Department of Radiation Oncology, Helen Diller Comprehensive Cancer Center, University of California San Francisco, San Francisco, California 94143 and UCSF/UC Berkeley Joint Graduate Group in Bioengineering, San Francisco, California 94158 (United States)

2009-04-15

Megavoltage cone-beam CT (MVCBCT) is the most recent addition to the in-room CT systems developed for image-guided radiation therapy. The first generation MVCBCT system consists of a 6 MV treatment x-ray beam produced by a conventional linear accelerator equipped with a flat panel amorphous silicon detector. The objective of this study was to evaluate the physical performance of MVCBCT in order to optimize the system acquisition and reconstruction parameters for image quality. MVCBCT acquisitions were performed with the clinical system but images were reconstructed and analyzed with a separate research workstation. The geometrical stability and the positioning accuracy of the system were evaluated by comparing geometrical calibrations routinely performed over a period of 12 months. The beam output and detector intensity stability during MVCBCT acquisition were also evaluated by analyzing in-air acquisitions acquired at different exposure levels. Several system parameters were varied to quantify their impact on image quality including the exposure (2.7, 4.5, 9.0, 18.0, and 54.0 MU), the craniocaudal imaging length (2, 5, 15, and 27.4 cm), the voxel size (0.5, 1, and 2 mm), the slice thickness (1, 3, and 5 mm), and the phantom size. For the reconstruction algorithm, the study investigated the effect of binning, averaging and diffusion filtering of raw projections as well as three different projection filters. A head-sized water cylinder was used to measure and improve the uniformity of MVCBCT images. Inserts of different electron densities were placed in a water cylinder to measure the contrast-to-noise ratio (CNR). The spatial resolution was obtained by measuring the point-spread function of the system using an iterative edge blurring technique. Our results showed that the geometric stability and accuracy of MVCBCT were better than 1 mm over a period of 12 months. Beam intensity variations per projection of up to 35.4% were observed for a 2.7 MU MVCBCT acquisition

Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

Science.gov (United States)

McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

2006-03-01

To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the

Diagnosis of scaphoid fracture: optimal imaging techniques

Directory of Open Access Journals (Sweden)

Geijer M

2013-07-01

Full Text Available Mats Geijer Center for Medical Imaging and Physiology, Skåne University Hospital and Lund University, Lund, Sweden Abstract: This review aims to provide an overview of modern imaging techniques for evaluation of scaphoid fracture, with emphasis on occult fractures and an outlook on the possible evolution of imaging; it also gives an overview of the pathologic and anatomic basis for selection of techniques. Displaced scaphoid fractures detected by wrist radiography, with or without special scaphoid views, pose no diagnostic problems. After wrist trauma with clinically suspected scaphoid fracture and normal scaphoid radiography, most patients will have no clinically important fracture. Between 5% and 19% of patients (on average 16% in meta-analyses will, however, have an occult scaphoid fracture which, untreated, may lead to later, potentially devastating, complications. Follow-up imaging may be done with repeat radiography, tomosynthesis, computed tomography, magnetic resonance imaging (MRI, or bone scintigraphy. However, no method is perfect, and choice of imaging may be based on availability, cost, perceived accuracy, or personal preference. Generally, MRI and bone scintigraphy are regarded as the most sensitive modalities, but both are flawed by false positive results at various rates. Keywords: occult fracture, wrist, radiography, computed tomography, magnetic resonance imaging, radionuclide imaging

Optimization of imaging parameters for SPECT scans of [99mTc]TRODAT-1 using Taguchi analysis.

Directory of Open Access Journals (Sweden)

Cheng-Kai Huang

Full Text Available Parkinson's disease (PD is a neurodegenerative disease characterized by progressive loss of dopaminergic neurons in the basal ganglia. Single photon emission computed tomography (SPECT scans using [99mTc]TRODAT-1 can image dopamine transporters and provide valuable diagnostic information of PD. In this study, we optimized the scanning parameters for [99mTc]TRODAT-1/SPECT using the Taguchi analysis to improve image quality. SPECT scans were performed on forty-five healthy volunteers according to an L9 orthogonal array. Three parameters were considered, including the injection activity, uptake duration, and acquisition time per projection. The signal-to-noise ratio (SNR was calculated from the striatum/occipital activity ratio as an image quality index. Ten healthy subjects and fifteen PD patients were used to verify the optimal parameters. The estimated optimal parameters were 962 MBq for [99mTc]TRODAT-1 injection, 260 min for uptake duration, and 60 s/projection for data acquisition. The uptake duration and time per projection were the two dominant factors which had an F-value of 18.638 (38% and 25.933 (53%, respectively. Strong cross interactions existed between the injection activity/uptake duration and injection activity/time per projection. Therefore, under the consideration of as low as reasonably achievable (ALARA for radiation protection, we can decrease the injection activity to 740 MBq. The image quality remains almost the same for clinical applications.

Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approach

Science.gov (United States)

Wang, Chuang; Udupa, Jayaram K.; Tong, Yubing; Chen, Jerry; Venigalla, Sriram; Odhner, Dewey; Guzzo, Thomas J.; Christodouleas, John; Torigian, Drew A.

2018-02-01

Magnetic resonance imaging (MRI) is often used in clinical practice to stage patients with bladder cancer to help plan treatment. However, qualitative assessment of MR images is prone to inaccuracies, adversely affecting patient outcomes. In this paper, T2-weighted MR image-based quantitative features were extracted from the bladder wall in 65 patients with bladder cancer to classify them into two primary tumor (T) stage groups: group 1 - T stage T2, with primary tumor locally confined to the bladder, and group 2 - T stage T2, with primary tumor locally extending beyond the bladder. The bladder was divided into 8 sectors in the axial plane, where each sector has a corresponding reference standard T stage that is based on expert radiology qualitative MR image review and histopathologic results. The performance of the classification for correct assignment of T stage grouping was then evaluated at both the patient level and the sector level. Each bladder sector was divided into 3 shells (inner, middle, and outer), and 15,834 features including intensity features and texture features from local binary pattern and gray-level co-occurrence matrix were extracted from the 3 shells of each sector. An optimal feature set was selected from all features using an optimal biomarker approach. Nine optimal biomarker features were derived based on texture properties from the middle shell, with an area under the ROC curve of AUC value at the sector and patient level of 0.813 and 0.806, respectively.

Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

Rosenberger C

2008-01-01

Full Text Available Abstract Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

Optimization-Based Image Segmentation by Genetic Algorithms

Directory of Open Access Journals (Sweden)

H. Laurent

2008-05-01

Full Text Available Many works in the literature focus on the definition of evaluation metrics and criteria that enable to quantify the performance of an image processing algorithm. These evaluation criteria can be used to define new image processing algorithms by optimizing them. In this paper, we propose a general scheme to segment images by a genetic algorithm. The developed method uses an evaluation criterion which quantifies the quality of an image segmentation result. The proposed segmentation method can integrate a local ground truth when it is available in order to set the desired level of precision of the final result. A genetic algorithm is then used in order to determine the best combination of information extracted by the selected criterion. Then, we show that this approach can either be applied for gray-levels or multicomponents images in a supervised context or in an unsupervised one. Last, we show the efficiency of the proposed method through some experimental results on several gray-levels and multicomponents images.

Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition

Science.gov (United States)

Guo, Chengwen; Wang, Jing; Qin, Yu; Zhan, Hongchen; Yuan, Jie; Cheng, Qian; Wang, Xueding

2018-02-01

Photoacoustic (PA) signal of an ideal optical absorb particle is a single N-shape wave. PA signals of a complicated biological tissue can be considered as the combination of individual N-shape waves. However, the N-shape wave basis not only complicates the subsequent work, but also results in aliasing between adjacent micro-structures, which deteriorates the quality of the final PA images. In this paper, we propose a method to improve PA image quality through signal processing method directly working on raw signals, which including deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent point spread function (PSF) which is measured in advance. Then, EMD is adopted to adaptively re-shape the PA signals with two constraints, positive polarity and spectrum consistence. With our proposed method, the built PA images can yield more detail structural information. Micro-structures are clearly separated and revealed. To validate the effectiveness of this method, we present numerical simulations and phantom studies consist of a densely distributed point sources model and a blood vessel model. In the future, our study might hold the potential for clinical PA imaging as it can help to distinguish micro-structures from the optimized images and even measure the size of objects from deconvolved signals.

Physics-based optimization of image quality in 3D X-ray flat-panel cone-beam imaging

NARCIS (Netherlands)

Snoeren, R.M.

2012-01-01

This thesis describes the techniques for modeling and control of 3D X-ray cardiovascular systems in terms of Image Quality and patient dose, aiming at optimizing the diagnostic quality. When aiming at maximum Image Quality (IQ), a cascaded system constituted from inter-dependent imaging components,

Optimal context quantization in lossless compression of image data sequences

DEFF Research Database (Denmark)

Forchhammer, Søren; Wu, X.; Andersen, Jakob Dahl

2004-01-01

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due...... to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context C/sub t/=(X/sub t-t1/,X/sub t-t2/,...,X/sub t-tK/) of a source symbol X/sub t/ into one of a set of conditioning states. The optimality of context...... quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet...

Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

Science.gov (United States)

Bomarito, G. F.; Hochhalter, J. D.; Cannon, A. H.

2016-01-01

The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under

Obtaining and Using Images in the Clinical Setting

International Nuclear Information System (INIS)

Cendales, Ricardo

2009-01-01

Currently small electronic devices capable of producing high quality images are available. The massive use of these devices has become common in the clinical setting as medical images represent a useful tool to document relevant clinical conditions for patient diagnosis, treatment and follow-up. Besides, clinical images are beneficial for legal, scientific and academic purposes. The extended practice without proper ethical guidelines might represent a significant risk for the protection of patient rights and clinical practice. This document discusses risks and duties when obtaining medical images, and presents some arguments on institutional and professional responsibilities around the definition of policies regarding the protection of privacy and dignity of the patient.

A review of molecular imaging studies reaching the clinical stage

International Nuclear Information System (INIS)

Wong, Franklin C.; Kim, E. Edmund

2009-01-01

The practice of molecular imaging in the clinics is examined across various imaging modalities to assess the current status of clinical molecular imaging. The various physiologic and scientific bases of clinical molecular imaging are surveyed to assess the possibilities and opportunities for the deployment of the different imaging modalities in the near future. The requisites for successful candidate(s) of clinical molecular imaging are reviewed for future development.

Order of magnitude sensitivity increase in X-ray Fluorescence Computed Tomography (XFCT) imaging with an optimized spectro-spatial detector configuration: theory and simulation.

Science.gov (United States)

Ahmad, Moiz; Bazalova, Magdalena; Xiang, Liangzhong; Xing, Lei

2014-05-01

The purpose of this study was to increase the sensitivity of XFCT imaging by optimizing the data acquisition geometry for reduced scatter X-rays. The placement of detectors and detector energy window were chosen to minimize scatter X-rays. We performed both theoretical calculations and Monte Carlo simulations of this optimized detector configuration on a mouse-sized phantom containing various gold concentrations. The sensitivity limits were determined for three different X-ray spectra: a monoenergetic source, a Gaussian source, and a conventional X-ray tube source. Scatter X-rays were minimized using a backscatter detector orientation (scatter direction > 110(°) to the primary X-ray beam). The optimized configuration simultaneously reduced the number of detectors and improved the image signal-to-noise ratio. The sensitivity of the optimized configuration was 10 μg/mL (10 pM) at 2 mGy dose with the mono-energetic source, which is an order of magnitude improvement over the unoptimized configuration (102 pM without the optimization). Similar improvements were seen with the Gaussian spectrum source and conventional X-ray tube source. The optimization improvements were predicted in the theoretical model and also demonstrated in simulations. The sensitivity of XFCT imaging can be enhanced by an order of magnitude with the data acquisition optimization, greatly enhancing the potential of this modality for future use in clinical molecular imaging.

Clinical feasibility of {sup 90}Y digital PET/CT for imaging microsphere biodistribution following radioembolization

Energy Technology Data Exchange (ETDEWEB)

Wright, Chadwick L.; Binzel, Katherine; Zhang, Jun; Knopp, Michael V. [The Ohio State University Wexner Medical Center, Wright Center of Innovation in Biomedical Imaging, Department of Radiology, Columbus, OH (United States); Wuthrick, Evan J. [The Ohio State University Wexner Medical Center, Department of Radiation Oncology, Columbus, OH (United States)

2017-07-15

The purpose of this study was to evaluate the clinical feasibility of next generation solid-state digital photon counting PET/CT (dPET/CT) technology and imaging findings in patients following {sup 90}Y microsphere radioembolization in comparison with standard of care (SOC) bremsstrahlung SPECT/CT (bSPECT/CT). Five patients underwent SOC {sup 90}Y bremsstrahlung imaging immediately following routine radioembolization with 3.5 ± 1.7 GBq of {sup 90}Y-labeled glass microspheres. All patients also underwent dPET/CT imaging at 29 ± 11 h following radioembolization. Matched pairs comparison was used to compare image quality, image contrast and {sup 90}Y biodistribution between dPET/CT and bSPECT/CT images. Volumetric assessments of {sup 90}Y activity using different isocontour thresholds on dPET/CT and bSPECT/CT images were also compared. Digital PET/CT consistently provided better visual image quality and {sup 90}Y-to-background image contrast while depicting {sup 90}Y biodistribution than bSPECT/CT. Isocontour volumetric assessment using a 1% threshold precisely outlined {sup 90}Y activity and the treatment volume on dPET/CT images, whereas a more restrictive 20% threshold on bSPECT/CT images was needed to obtain comparable treatment volumes. The use of a less restrictive 10% threshold isocontour on bSPECT/CT images grossly overestimated the treatment volume when compared with the 1% threshold on dPET/CT images. Digital PET/CT is clinically feasible for the assessment of {sup 90}Y microsphere biodistribution following radioembolization, and provides better visual image quality and image contrast than routine bSPECT/CT with comparable acquisition times. With further optimization and clinical validation, dPET technology may allow faster and more accurate imaging-based assessment of {sup 90}Y microsphere biodistribution. (orig.)

Clinical application of 'Justification' and 'Optimization' principle of ALARA in pediatric CT imaging: "How many children can be protected from unnecessary radiation?".

Science.gov (United States)

Sodhi, Kushaljit S; Krishna, Satheesh; Saxena, Akshay K; Sinha, Anindita; Khandelwal, Niranjan; Lee, Edward Y

2015-09-01

Practice of ALARA (as low as reasonably achievable) principle in the developed world is currently well established. However, there is striking lack of published data regarding such experience in the developing countries. Therefore, the goal of this study is to prospectively evaluate CT request forms to assess how many children could be protected from harmful radiation exposure if 'Justification' and 'Optimization' principles of ALARA are applied before obtaining CT imaging in a developing country. This can save children from potential radiation risks including development of brain cancer and leukemia. Consecutive CT request forms over a six month study period (May 16, 2013 to November 15, 2013) in a tertiary pediatric children's hospital in India were prospectively reviewed by two pediatric radiologists before obtaining CT imaging. First, 'Justification' of CT was evaluated and then 'Optimization' was applied for evaluation of appropriateness of the requested CT studies. The number (and percentage) of CT studies avoided by applying 'Justification' and 'Optimization' principle of ALARA were calculated. The difference in number of declined and optimized CT requests between CT requests from inpatient and outpatient departments was compared using Chi-Square test. A total of 1302 consecutive CT request forms were received during the study period. Some of the request forms (n=86; 6.61%) had requests for more than one (multiple) anatomical regions, hence, a total of 1392 different anatomical CT requests were received. Based on evaluation of the CT request forms for 'Justification' and 'Optimization' principle of ALARA by pediatric radiology reviewers, 111 individual anatomic part CT requests from 105 pediatric patients were avoided. Therefore, 8.06% (105 out of 1302 pediatric patients) were protected from unnecessary or additional radiation exposure.The rates of declined or optimized CT requests from inpatient department was significantly higher than that from outpatient

Comparative evaluation of two dose optimization methods for image-guided, highly-conformal, tandem and ovoids cervix brachytherapy planning

Science.gov (United States)

Ren, Jiyun; Menon, Geetha; Sloboda, Ron

2013-04-01

Although the Manchester system is still extensively used to prescribe dose in brachytherapy (BT) for locally advanced cervix cancer, many radiation oncology centers are transitioning to 3D image-guided BT, owing to the excellent anatomy definition offered by modern imaging modalities. As automatic dose optimization is highly desirable for 3D image-based BT, this study comparatively evaluates the performance of two optimization methods used in BT treatment planning—Nelder-Mead simplex (NMS) and simulated annealing (SA)—for a cervix BT computer simulation model incorporating a Manchester-style applicator. Eight model cases were constructed based on anatomical structure data (for high risk-clinical target volume (HR-CTV), bladder, rectum and sigmoid) obtained from measurements on fused MR-CT images for BT patients. D90 and V100 for HR-CTV, D2cc for organs at risk (OARs), dose to point A, conformation index and the sum of dwell times within the tandem and ovoids were calculated for optimized treatment plans designed to treat the HR-CTV in a highly conformal manner. Compared to the NMS algorithm, SA was found to be superior as it could perform optimization starting from a range of initial dwell times, while the performance of NMS was strongly dependent on their initial choice. SA-optimized plans also exhibited lower D2cc to OARs, especially the bladder and sigmoid, and reduced tandem dwell times. For cases with smaller HR-CTV having good separation from adjoining OARs, multiple SA-optimized solutions were found which differed markedly from each other and were associated with different choices for initial dwell times. Finally and importantly, the SA method yielded plans with lower dwell time variability compared with the NMS method.

Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

Science.gov (United States)

Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

2017-04-01

Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

WE-AB-BRA-09: Sensitivity of Plan Re-Optimization to Errors in Deformable Image Registration in Online Adaptive Image-Guided Radiation Therapy

International Nuclear Information System (INIS)

McClain, B; Olsen, J; Green, O; Yang, D; Santanam, L; Olsen, L; Zhao, T; Rodriguez, V; Wooten, H; Mutic, S; Kashani, R; Victoria, J; Dempsey, J

2015-01-01

Purpose: Online adaptive therapy (ART) relies on auto-contouring using deformable image registration (DIR). DIR’s inherent uncertainties require user intervention and manual edits while the patient is on the table. We investigated the dosimetric impact of DIR errors on the quality of re-optimized plans, and used the findings to establish regions for focusing manual edits to where DIR errors can Result in clinically relevant dose differences. Methods: Our clinical implementation of online adaptive MR-IGRT involves using DIR to transfer contours from CT to daily MR, followed by a physicians’ edits. The plan is then re-optimized to meet the organs at risk (OARs) constraints. Re-optimized abdomen and pelvis plans generated based on physician edited OARs were selected as the baseline for evaluation. Plans were then re-optimized on auto-deformed contours with manual edits limited to pre-defined uniform rings (0 to 5cm) around the PTV. A 0cm ring indicates that the auto-deformed OARs were used without editing. The magnitude of the variations caused by the non-deterministic optimizer was quantified by repeat re-optimizations on the same geometry to determine the mean and standard deviation (STD). For each re-optimized plan, various volumetric parameters for the PTV, the OARs were extracted along with DVH and isodose evaluation. A plan was deemed acceptable if the variation from the baseline plan was within one STD. Results: Initial results show that for abdomen and pancreas cases, a minimum of 5cm margin around the PTV is required for contour corrections, while for pelvic and liver cases a 2–3 cm margin is sufficient. Conclusion: Focusing manual contour edits to regions of dosimetric relevance can reduce contouring time in the online ART process while maintaining a clinically comparable plan. Future work will further refine the contouring region by evaluating the path along the beams, dose gradients near the target and OAR dose metrics

Co-clinical quantitative tumor volume imaging in ALK-rearranged NSCLC treated with crizotinib

Energy Technology Data Exchange (ETDEWEB)

Nishino, Mizuki, E-mail: Mizuki_Nishino@DFCI.HARVARD.EDU [Department of Radiology, Brigham and Women’s Hospital, 450 Brookline Ave., Boston MA, 02215 (United States); Department of Imaging, Dana-Farber Cancer Institute, 450 Brookline Ave., Boston MA, 02215 (United States); Sacher, Adrian G.; Gandhi, Leena; Chen, Zhao; Akbay, Esra [Department of Medical Oncology and Department of Medicine Dana-Farber Cancer Institute and Brigham and Women’s Hospital 450 Brookline Ave., Boston MA, 02215 (United States); Fedorov, Andriy; Westin, Carl F.; Hatabu, Hiroto [Department of Radiology, Brigham and Women’s Hospital, 450 Brookline Ave., Boston MA, 02215 (United States); Johnson, Bruce E.; Hammerman, Peter; Wong, Kwok-kin [Department of Medical Oncology and Department of Medicine Dana-Farber Cancer Institute and Brigham and Women’s Hospital 450 Brookline Ave., Boston MA, 02215 (United States)

2017-03-15

Highlights: • Role of co-clinical studies in precision cancer medicine is increasingly recognized. • This study compared tumor volume in co-clinical trials of ALK-rearranged NSCLC. • Similarities and differences of tumor volume changes in mice and humans were noted. • The study provides insights to optimize murine co-clinical trial designs. - Abstract: Purpose: To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC). Methods: Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans. Results: The median tumor volume decrease (%) at the maximal response was −40.4% (range: −79.5%–+11.7%) in mice, and −72.9% (range: −100%–+72%) in humans (Wilcoxon p = 0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months. Conclusion: The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.

Co-clinical quantitative tumor volume imaging in ALK-rearranged NSCLC treated with crizotinib

International Nuclear Information System (INIS)

Nishino, Mizuki; Sacher, Adrian G.; Gandhi, Leena; Chen, Zhao; Akbay, Esra; Fedorov, Andriy; Westin, Carl F.; Hatabu, Hiroto; Johnson, Bruce E.; Hammerman, Peter; Wong, Kwok-kin

2017-01-01

Highlights: • Role of co-clinical studies in precision cancer medicine is increasingly recognized. • This study compared tumor volume in co-clinical trials of ALK-rearranged NSCLC. • Similarities and differences of tumor volume changes in mice and humans were noted. • The study provides insights to optimize murine co-clinical trial designs. - Abstract: Purpose: To evaluate and compare the volumetric tumor burden changes during crizotinib therapy in mice and human cohorts with ALK-rearranged non-small-cell lung cancer (NSCLC). Methods: Volumetric tumor burden was quantified on serial imaging studies in 8 bitransgenic mice with ALK-rearranged adenocarcinoma treated with crizotinib, and in 33 human subjects with ALK-rearranged NSCLC treated with crizotinib. The volumetric tumor burden changes and the time to maximal response were compared between mice and humans. Results: The median tumor volume decrease (%) at the maximal response was −40.4% (range: −79.5%–+11.7%) in mice, and −72.9% (range: −100%–+72%) in humans (Wilcoxon p = 0.03). The median time from the initiation of therapy to maximal response was 6 weeks in mice, and 15.7 weeks in humans. Overall volumetric response rate was 50% in mice and 97% in humans. Spider plots of tumor volume changes during therapy demonstrated durable responses in the human cohort, with a median time on therapy of 13.1 months. Conclusion: The present study described an initial attempt to evaluate quantitative tumor burden changes in co-clinical imaging studies of genomically-matched mice and human cohorts with ALK-rearranged NSCLC treated with crizotinib. Differences are noted in the degree of maximal volume response between the two cohorts in this well-established paradigm of targeted therapy, indicating a need for further studies to optimize co-clinical trial design and interpretation.

Ultrasound Image Quality Assessment: A framework for evaluation of clinical image quality

DEFF Research Database (Denmark)

Hemmsen, Martin Christian; Pedersen, Mads Møller; Nikolov, Svetoslav Ivanov

2010-01-01

Improvement of ultrasound images should be guided by their diagnostic value. Evaluation of clinical image quality is generally performed subjectively, because objective criteria have not yet been fully developed and accepted for the evaluation of clinical image quality. Based on recommendation 50...... information, which is fast enough to get sufficient number of scans under realistic operating conditions, so that statistical evaluation is valid and reliable....

MR imaging of the ankle at 3 Tesla and 1.5 Tesla: protocol optimization and application to cartilage, ligament and tendon pathology in cadaver specimens

International Nuclear Information System (INIS)

Barr, Cameron; Malfair, David; Henning, Tobias D.; Steinbach, Lynne; Link, Thomas M.; Bauer, Jan S.; Ma, Benjamin

2007-01-01

The objective of this study was to optimize ankle joint MR imaging in volunteers at 1.5 Tesla (T) and 3.0 T, and to compare these optimized sequences concerning image quality and performance in assessing cartilage, ligament and tendon pathology in fresh human cadaver specimens. Initially our clinical ankle protocol consisting of T1-weighted (-w), fat-saturated (fs) T2-w, and short τ inversion-recovery fast spinecho (FSE) sequences was optimized at 1.5 T and 3.0 T by two radiologists. For dedicated cartilage imaging, fs-intermediate (IM)-w FSE, fs spoiled gradient echo, and balanced free-precession steady-state sequences were optimized. Using the optimized sequences, thirteen cadaver ankle joints were imaged. Four radiologists independently assessed these images concerning image quality and pathology. All radiologists consistently rated image quality higher at 3.0 T (all sequences p<0.05). For detecting cartilage pathology, diagnostic performance was significantly higher at 3.0 T (ROC-values up to 0.93 vs. 0.77; p<0.05); the fs-IM FSE sequence showed highest values among the different sequences. Average sensitivity for detecting tendon pathology was 63% at 3.0 T vs. 41% at 1.5 T and was significantly higher at 3.0 T for 2 out of 4 radiologists (p<0.05). Compared to 1.5 T, imaging of the ankle joint at 3.0 T significantly improved image quality and diagnostic performance in assessing cartilage pathology. (orig.)

[Optimization of digital chest radiography image post-processing in diagnosis of pneumoconiosis].

Science.gov (United States)

Sheng, Bing-yong; Mao, Ling; Zhou, Shao-wei; Shi, Jin

2013-11-01

To establish the optimal image post-processing parameters for digital chest radiography as preliminary research for introducing digital radiography (DR) to pneumoconiosis diagnosis in China. A total of 204 pneumoconiosis patients and 31 dust-exposed workers were enrolled as the subjects in this research. Film-screen radiography (FSR) and DR images were taken for all subjects. DR films were printed after raw images were processed and parameters were altered using DR workstation (GE Healthcare, U.S.A.). Image gradations, lung textures, and the imaging of thoracic vertebra were evaluated by pneumoconiosis experts, and the optimal post-processing parameters were selected. Optical density was measured for both DR films and FSR films. For the DR machine used in this research, the contrast adjustment (CA) and brightness adjustment (BA) were the main parameters that determine the brightness and gray levels of images. The optimal ranges for CA and BA were 115%∼120% and 160%∼165%, respectively. The quality of DR chest films would be optimized when tissue contrast was adjusted to a maximum of 0.15, edge to a minimum of 1, and both noise reduction and tissue equalization to0.The failure rate of chest DR (0.4%) was significantly lower than that of chest FSR (17%) (P image post-processing on DR machine purchased from GE Healthcare, the DR chest films can meet all requirements for the quality of chest X-ray films in the Chinese diagnostic criteria for pneumoconiosis.

Improved total variation-based CT image reconstruction applied to clinical data

Energy Technology Data Exchange (ETDEWEB)

Ritschl, Ludwig; Bergner, Frank; Kachelriess, Marc [Institute of Medical Physics (IMP), University of Erlangen-Nuernberg, Henkestr. 91, 91052 Erlangen (Germany); Fleischmann, Christof, E-mail: ludwig.ritschl@imp.uni-erlangen.de [Ziehm Imaging GmbH, Donaustrasse 31, 90451 Nuernberg (Germany)

2011-03-21

In computed tomography there are different situations where reconstruction has to be performed with limited raw data. In the past few years it has been shown that algorithms which are based on compressed sensing theory are able to handle incomplete datasets quite well. As a cost function these algorithms use the l{sub 1}-norm of the image after it has been transformed by a sparsifying transformation. This yields to an inequality-constrained convex optimization problem. Due to the large size of the optimization problem some heuristic optimization algorithms have been proposed in the past few years. The most popular way is optimizing the raw data and sparsity cost functions separately in an alternating manner. In this paper we will follow this strategy and present a new method to adapt these optimization steps. Compared to existing methods which perform similarly, the proposed method needs no a priori knowledge about the raw data consistency. It is ensured that the algorithm converges to the lowest possible value of the raw data cost function, while holding the sparsity constraint at a low value. This is achieved by transferring the step-size determination of both optimization procedures into the raw data domain, where they are adapted to each other. To evaluate the algorithm, we process measured clinical datasets. To cover a wide field of possible applications, we focus on the problems of angular undersampling, data lost due to metal implants, limited view angle tomography and interior tomography. In all cases the presented method reaches convergence within less than 25 iteration steps, while using a constant set of algorithm control parameters. The image artifacts caused by incomplete raw data are mostly removed without introducing new effects like staircasing. All scenarios are compared to an existing implementation of the ASD-POCS algorithm, which realizes the step-size adaption in a different way. Additional prior information as proposed by the PICCS algorithm

SU-G-BRA-03: PCA Based Imaging Angle Optimization for 2D Cine MRI Based Radiotherapy Guidance

Energy Technology Data Exchange (ETDEWEB)

Chen, T; Yue, N; Jabbour, S; Zhang, M [Rutgers University, New Brunswick, NJ (United States)

2016-06-15

Purpose: To develop an imaging angle optimization methodology for orthogonal 2D cine MRI based radiotherapy guidance using Principal Component Analysis (PCA) of target motion retrieved from 4DCT. Methods: We retrospectively analyzed 4DCT of 6 patients with lung tumor. A radiation oncologist manually contoured the target volume at the maximal inhalation phase of the respiratory cycle. An object constrained deformable image registration (DIR) method has been developed to track the target motion along the respiration at ten phases. The motion of the center of the target mass has been analyzed using the PCA to find out the principal motion components that were uncorrelated with each other. Two orthogonal image planes for cineMRI have been determined using this method to minimize the through plane motion during MRI based radiotherapy guidance. Results: 3D target respiratory motion for all 6 patients has been efficiently retrieved from 4DCT. In this process, the object constrained DIR demonstrated satisfactory accuracy and efficiency to enable the automatic motion tracking for clinical application. The average motion amplitude in the AP, lateral, and longitudinal directions were 3.6mm (min: 1.6mm, max: 5.6mm), 1.7mm (min: 0.6mm, max: 2.7mm), and 5.6mm (min: 1.8mm, max: 16.1mm), respectively. Based on PCA, the optimal orthogonal imaging planes were determined for cineMRI. The average angular difference between the PCA determined imaging planes and the traditional AP and lateral imaging planes were 47 and 31 degrees, respectively. After optimization, the average amplitude of through plane motion reduced from 3.6mm in AP images to 2.5mm (min:1.3mm, max:3.9mm); and from 1.7mm in lateral images to 0.6mm (min: 0.2mm, max:1.5mm), while the principal in plane motion amplitude increased from 5.6mm to 6.5mm (min: 2.8mm, max: 17mm). Conclusion: DIR and PCA can be used to optimize the orthogonal image planes of cineMRI to minimize the through plane motion during radiotherapy

SU-G-BRA-03: PCA Based Imaging Angle Optimization for 2D Cine MRI Based Radiotherapy Guidance

International Nuclear Information System (INIS)

Chen, T; Yue, N; Jabbour, S; Zhang, M

2016-01-01

Purpose: To develop an imaging angle optimization methodology for orthogonal 2D cine MRI based radiotherapy guidance using Principal Component Analysis (PCA) of target motion retrieved from 4DCT. Methods: We retrospectively analyzed 4DCT of 6 patients with lung tumor. A radiation oncologist manually contoured the target volume at the maximal inhalation phase of the respiratory cycle. An object constrained deformable image registration (DIR) method has been developed to track the target motion along the respiration at ten phases. The motion of the center of the target mass has been analyzed using the PCA to find out the principal motion components that were uncorrelated with each other. Two orthogonal image planes for cineMRI have been determined using this method to minimize the through plane motion during MRI based radiotherapy guidance. Results: 3D target respiratory motion for all 6 patients has been efficiently retrieved from 4DCT. In this process, the object constrained DIR demonstrated satisfactory accuracy and efficiency to enable the automatic motion tracking for clinical application. The average motion amplitude in the AP, lateral, and longitudinal directions were 3.6mm (min: 1.6mm, max: 5.6mm), 1.7mm (min: 0.6mm, max: 2.7mm), and 5.6mm (min: 1.8mm, max: 16.1mm), respectively. Based on PCA, the optimal orthogonal imaging planes were determined for cineMRI. The average angular difference between the PCA determined imaging planes and the traditional AP and lateral imaging planes were 47 and 31 degrees, respectively. After optimization, the average amplitude of through plane motion reduced from 3.6mm in AP images to 2.5mm (min:1.3mm, max:3.9mm); and from 1.7mm in lateral images to 0.6mm (min: 0.2mm, max:1.5mm), while the principal in plane motion amplitude increased from 5.6mm to 6.5mm (min: 2.8mm, max: 17mm). Conclusion: DIR and PCA can be used to optimize the orthogonal image planes of cineMRI to minimize the through plane motion during radiotherapy

Fast ℓ1-SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime

Science.gov (United States)

Murphy, Mark; Alley, Marcus; Demmel, James; Keutzer, Kurt; Vasanawala, Shreyas; Lustig, Michael

2012-01-01

We present ℓ1-SPIRiT, a simple algorithm for auto calibrating parallel imaging (acPI) and compressed sensing (CS) that permits an efficient implementation with clinically-feasible runtimes. We propose a CS objective function that minimizes cross-channel joint sparsity in the Wavelet domain. Our reconstruction minimizes this objective via iterative soft-thresholding, and integrates naturally with iterative Self-Consistent Parallel Imaging (SPIRiT). Like many iterative MRI reconstructions, ℓ1-SPIRiT’s image quality comes at a high computational cost. Excessively long runtimes are a barrier to the clinical use of any reconstruction approach, and thus we discuss our approach to efficiently parallelizing ℓ1-SPIRiT and to achieving clinically-feasible runtimes. We present parallelizations of ℓ1-SPIRiT for both multi-GPU systems and multi-core CPUs, and discuss the software optimization and parallelization decisions made in our implementation. The performance of these alternatives depends on the processor architecture, the size of the image matrix, and the number of parallel imaging channels. Fundamentally, achieving fast runtime requires the correct trade-off between cache usage and parallelization overheads. We demonstrate image quality via a case from our clinical experimentation, using a custom 3DFT Spoiled Gradient Echo (SPGR) sequence with up to 8× acceleration via poisson-disc undersampling in the two phase-encoded directions. PMID:22345529

Optimal steel thickness combined with computed radiography for portal imaging of nasopharyngeal cancer patients

International Nuclear Information System (INIS)

Wu Shixiu; Jin Xiance; Xie Congying; Cao Guoquan

2005-01-01

The poor image quality of conventional metal screen-film portal imaging system has long been of concern, and various methods have been investigated in an attempt to enhance the quality of portal images. Computed radiography (CR) used in combination with a steel plate displays image enhancement. The optimal thickness of the steel plate had been studied by measuring the modulation transfer function (MTF) characteristics. Portal images of nasopharyngeal carcinoma patients were taken by both a conventional metal screen-film system and this optimal steel and CR plate combination system. Compared with a conventional metal screen-film system, the CR-metal screen system achieves a much higher image contrast. The measured modulation transfer function (MTF) of the CR combination is greater than conventional film-screen portal imaging systems and also results in superior image performance, as demonstrated by receiver operator characteristic (ROC) analysis. This optimal combination steel CR plate portal imaging system is capable of producing high contrast portal images conveniently

Cardiac tumors: optimal cardiac MR sequences and spectrum of imaging appearances.

LENUS (Irish Health Repository)

O'Donnell, David H

2012-02-01

OBJECTIVE: This article reviews the optimal cardiac MRI sequences for and the spectrum of imaging appearances of cardiac tumors. CONCLUSION: Recent technologic advances in cardiac MRI have resulted in the rapid acquisition of images of the heart with high spatial and temporal resolution and excellent myocardial tissue characterization. Cardiac MRI provides optimal assessment of the location, functional characteristics, and soft-tissue features of cardiac tumors, allowing accurate differentiation of benign and malignant lesions.

Optimization of image quality and patient dose in mammography

International Nuclear Information System (INIS)

Shafqat Faaruq; Jaferi, R.A.; Nafeesa Nazlee

2007-01-01

Complete test of publication follows. Optimization of patient dose and image quality can be defined as to get the best image quality with minimum possible radiation dose to the patient by setting various parameters and modes of operation available in mammography machines. The optimization procedures were performed on two mammography units from M/S GE and Metaltronica, available at NORI, using standard mammographic accreditation phantom (Model: BR-156) and acrylic sheets of variable thicknesses. Quality assurance and quality control (QC) tests being the essential part of optimization. The QC tests as recommended by American College of Radiology, were first performed on both machines as well as X-ray film processor. In the second step, different affecting the image quality and radiation dose to patient, like film screen combination (FSC), phantom optical density (PD), kVp, mAs etc, were adjusted for various phantom thicknesses ranging from 3 cm to 6.5 cm in various modes of operation in the machines (semi-auto- and manual in GE, Auto-, semi-auto- and manual mode in Metaltronica). The image quality was studied for these optimized parameters on the basis of the number of test objects of the phantom visible in these images. Finally the linear relationship between mAs and skin entrance dose (mGy) was verified using ionization chamber with the phantom and the actual patients. Despite some practical limitations, the results of the quality assurance tests were within acceptable limits defined by ACR. The dose factor for GE was 68.0 y/mAs, while 76.0 mGy/mAs for Metaltronica at 25 kVp. Before the start of this study the only one mammography unit GE, was routinely used at NORI and normal mode of operation of this unit was semi-auto mode with fixed kVp independent of compressed breast thickness, but in this study it was concluded that selecting kVp according to beast thickness result in an appreciable dose reduction (4-5 times less) without any compromise in image quality. The

Fruit fly optimization based least square support vector regression for blind image restoration

Science.gov (United States)

Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

2014-11-01

The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and

Adaptive polarimetric image representation for contrast optimization of a polarized beacon through fog

International Nuclear Information System (INIS)

Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi

2015-01-01

We present a contrast-maximizing optimal linear representation of polarimetric images obtained from a snapshot polarimetric camera for enhanced vision of a polarized light source in obscured weather conditions (fog, haze, cloud) over long distances (above 1 km). We quantitatively compare the gain in contrast obtained by different linear representations of the experimental polarimetric images taken during rapidly varying foggy conditions. It is shown that the adaptive image representation that depends on the correlation in background noise fluctuations in the two polarimetric images provides an optimal contrast enhancement over all weather conditions as opposed to a simple difference image which underperforms during low visibility conditions. Finally, we derive the analytic expression of the gain in contrast obtained with this optimal representation and show that the experimental results are in agreement with the assumed correlated Gaussian noise model. (paper)

Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

Directory of Open Access Journals (Sweden)

Mingjian Sun

2015-01-01

Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

Application of off-line image processing for optimization in chest computed radiography using a low cost system.

Science.gov (United States)

Muhogora, Wilbroad E; Msaki, Peter; Padovani, Renato

2015-03-08

 The objective of this study was to improve the visibility of anatomical details by applying off-line postimage processing in chest computed radiography (CR). Four spatial domain-based external image processing techniques were developed by using MATLAB software version 7.0.0.19920 (R14) and image processing tools. The developed techniques were implemented to sample images and their visual appearances confirmed by two consultant radiologists to be clinically adequate. The techniques were then applied to 200 chest clinical images and randomized with other 100 images previously processed online. These 300 images were presented to three experienced radiologists for image quality assessment using standard quality criteria. The mean and ranges of the average scores for three radiologists were characterized for each of the developed technique and imaging system. The Mann-Whitney U-test was used to test the difference of details visibility between the images processed using each of the developed techniques and the corresponding images processed using default algorithms. The results show that the visibility of anatomical features improved significantly (0.005 ≤ p ≤ 0.02) with combinations of intensity values adjustment and/or spatial linear filtering techniques for images acquired using 60 ≤ kVp ≤ 70. However, there was no improvement for images acquired using 102 ≤ kVp ≤ 107 (0.127 ≤ p ≤ 0.48). In conclusion, the use of external image processing for optimization can be effective in chest CR, but should be implemented in consultations with the radiologists.

Multiparameter optimization of mammography: an update

Science.gov (United States)

Jafroudi, Hamid; Muntz, E. P.; Jennings, Robert J.

1994-05-01

Previously in this forum we have reported the application of multiparameter optimization techniques to the design of a minimum dose mammography system. The approach used a reference system to define the physical imaging performance required and the dose to which the dose for the optimized system should be compared. During the course of implementing the resulting design in hardware suitable for laboratory testing, the state of the art in mammographic imaging changed, so that the original reference system, which did not have a grid, was no longer appropriate. A reference system with a grid was selected in response to this change, and at the same time the optimization procedure was modified, to make it more general and to facilitate study of the optimized design under a variety of conditions. We report the changes in the procedure, and the results obtained using the revised procedure and the up- to-date reference system. Our results, which are supported by laboratory measurements, indicate that the optimized design can image small objects as well as the reference system using only about 30% of the dose required by the reference system. Hardware meeting the specification produced by the optimization procedure and suitable for clinical use is currently under evaluation in the Diagnostic Radiology Department at the Clinical Center, NH.

Optimized multiple linear mappings for single image super-resolution

Science.gov (United States)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Effects of optimization and image processing in digital chest radiography

International Nuclear Information System (INIS)

Kheddache, S.; Maansson, L.G.; Angelhed, J.E.; Denbratt, L.; Gottfridsson, B.; Schlossman, D.

1991-01-01

A digital system for chest radiography based on a large image intensifier was compared to a conventional film-screen system. The digital system was optimized with regard to spatial and contrast resolution and dose. The images were digitally processed for contrast and edge enhancement. A simulated pneumothorax and two and two simulated nodules were positioned over the lungs and the mediastinum of an anthro-pomorphic phantom. Observer performance was evaluated with Receiver Operating Characteristic (ROC) analysis. Five observers assessed the processed digital images and the conventional full-size radiographs. The time spent viewing the full-size radiographs and the digital images was recorded. For the simulated pneumothorax, the results showed perfect performance for the full-size radiographs and detectability was high also for the processed digital images. No significant differences in the detectability of the simulated nodules was seen between the two imaging systems. The results for the digital images showed a significantly improved detectability for the nodules in the mediastinum as compared to a previous ROC study where no optimization and image processing was available. No significant difference in detectability was seen between the former and the present ROC study for small nodules in the lung. No difference was seen in the time spent assessing the conventional full-size radiographs and the digital images. The study indicates that processed digital images produced by a large image intensifier are equal in image quality to conventional full-size radiographs for low-contrast objects such as nodules. (author). 38 refs.; 4 figs.; 1 tab

The effect of nanoparticle size on theranostic systems: the optimal particle size for imaging is not necessarily optimal for drug delivery

Science.gov (United States)

Dreifuss, Tamar; Betzer, Oshra; Barnoy, Eran; Motiei, Menachem; Popovtzer, Rachela

2018-02-01

Theranostics is an emerging field, defined as combination of therapeutic and diagnostic capabilities in the same material. Nanoparticles are considered as an efficient platform for theranostics, particularly in cancer treatment, as they offer substantial advantages over both common imaging contrast agents and chemotherapeutic drugs. However, the development of theranostic nanoplatforms raises an important question: Is the optimal particle for imaging also optimal for therapy? Are the specific parameters required for maximal drug delivery, similar to those required for imaging applications? Herein, we examined this issue by investigating the effect of nanoparticle size on tumor uptake and imaging. Anti-epidermal growth factor receptor (EGFR)-conjugated gold nanoparticles (GNPs) in different sizes (diameter range: 20-120 nm) were injected to tumor bearing mice and their uptake by tumors was measured, as well as their tumor visualization capabilities as tumor-targeted CT contrast agent. Interestingly, the results showed that different particles led to highest tumor uptake or highest contrast enhancement, meaning that the optimal particle size for drug delivery is not necessarily optimal for tumor imaging. These results have important implications on the design of theranostic nanoplatforms.

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

DEFF Research Database (Denmark)

Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

2012-01-01

The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...

Guided color consistency optimization for image mosaicking

Science.gov (United States)

Xie, Renping; Xia, Menghan; Yao, Jian; Li, Li

2018-01-01

This paper studies the problem of color consistency correction for sequential images with diverse color characteristics. Existing algorithms try to adjust all images to minimize color differences among images under a unified energy framework, however, the results are prone to presenting a consistent but unnatural appearance when the color difference between images is large and diverse. In our approach, this problem is addressed effectively by providing a guided initial solution for the global consistency optimization, which avoids converging to a meaningless integrated solution. First of all, to obtain the reliable intensity correspondences in overlapping regions between image pairs, we creatively propose the histogram extreme point matching algorithm which is robust to image geometrical misalignment to some extents. In the absence of the extra reference information, the guided initial solution is learned from the major tone of the original images by searching some image subset as the reference, whose color characteristics will be transferred to the others via the paths of graph analysis. Thus, the final results via global adjustment will take on a consistent color similar to the appearance of the reference image subset. Several groups of convincing experiments on both the synthetic dataset and the challenging real ones sufficiently demonstrate that the proposed approach can achieve as good or even better results compared with the state-of-the-art approaches.

l0TV: A Sparse Optimization Method for Impulse Noise Image Restoration

KAUST Repository

Yuan, Ganzhao; Ghanem, Bernard

2017-01-01

Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on total variation for removing impulse noise in image restoration. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with l02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new sparse optimization method, called l0TV-PADMM, which solves the TV-based restoration problem with l0-norm data fidelity. To effectively deal with the resulting non-convex non-smooth optimization problem, we first reformulate it as an equivalent biconvex Mathematical Program with Equilibrium Constraints (MPEC), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our l0TV-PADMM method finds a desirable solution to the original l0-norm optimization problem and is proven to be convergent under mild conditions. We apply l0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that l0TV-PADMM outperforms state-of-the-art image restoration methods.

l0TV: A Sparse Optimization Method for Impulse Noise Image Restoration

KAUST Repository

Yuan, Ganzhao

2017-12-18

Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on total variation for removing impulse noise in image restoration. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with l02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new sparse optimization method, called l0TV-PADMM, which solves the TV-based restoration problem with l0-norm data fidelity. To effectively deal with the resulting non-convex non-smooth optimization problem, we first reformulate it as an equivalent biconvex Mathematical Program with Equilibrium Constraints (MPEC), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our l0TV-PADMM method finds a desirable solution to the original l0-norm optimization problem and is proven to be convergent under mild conditions. We apply l0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that l0TV-PADMM outperforms state-of-the-art image restoration methods.

Magnetic resonance imaging in clinically-definite multiple sclerosis

International Nuclear Information System (INIS)

Noakes, J.B.; Herkes, G.K.; Frith, J.A.

1990-01-01

Forty-two patients with clinically-definite multiple sclerosis were examined by magnetic resonance imaging using a 1.5-T instrument. Magnetic resonance imaging detected an abnormality in 90% of patients. In four patients, no lesions were demonstrated. The number, size and site of the lesions by magnetic resonance imaging were compared with the patients' clinical status and other variables. The Kurtzke disability status scale score increased in patients with corpus callosum atrophy, brainstem and basal ganglia lesions, and correlated with the total number of lesions. No correlation was shown between the findings of magnetic resonance imaging and disease duration, age, sex or pattern-reversal visual-evoked potentials. The variety of magnetic resonance images that could be obtained in patients with clinically-definite multiple sclerosis is highlighted. 24 refs., 8 figs., 1 tab

Modeling digital breast tomosynthesis imaging systems for optimization studies

Science.gov (United States)

Lau, Beverly Amy

Digital breast tomosynthesis (DBT) is a new imaging modality for breast imaging. In tomosynthesis, multiple images of the compressed breast are acquired at different angles, and the projection view images are reconstructed to yield images of slices through the breast. One of the main problems to be addressed in the development of DBT is the optimal parameter settings to obtain images ideal for detection of cancer. Since it would be unethical to irradiate women multiple times to explore potentially optimum geometries for tomosynthesis, it is ideal to use a computer simulation to generate projection images. Existing tomosynthesis models have modeled scatter and detector without accounting for oblique angles of incidence that tomosynthesis introduces. Moreover, these models frequently use geometry-specific physical factors measured from real systems, which severely limits the robustness of their algorithms for optimization. The goal of this dissertation was to design the framework for a computer simulation of tomosynthesis that would produce images that are sensitive to changes in acquisition parameters, so an optimization study would be feasible. A computer physics simulation of the tomosynthesis system was developed. The x-ray source was modeled as a polychromatic spectrum based on published spectral data, and inverse-square law was applied. Scatter was applied using a convolution method with angle-dependent scatter point spread functions (sPSFs), followed by scaling using an angle-dependent scatter-to-primary ratio (SPR). Monte Carlo simulations were used to generate sPSFs for a 5-cm breast with a 1-cm air gap. Detector effects were included through geometric propagation of the image onto layers of the detector, which were blurred using depth-dependent detector point-spread functions (PRFs). Depth-dependent PRFs were calculated every 5-microns through a 200-micron thick CsI detector using Monte Carlo simulations. Electronic noise was added as Gaussian noise as a

Radiation exposure and image quality in X-ray diagnostic radiology. Physical principles and clinical applications. 2. ed.

International Nuclear Information System (INIS)

Saebel, Manfred; Aichinger, Horst; Dierker, Joachim; Joite-Barfuss, Sigrid

2012-01-01

Diagnostic X-rays are the largest contributor to radiation exposure to the general population, and protecting the patient from radiation damage is a major aim of modern health policy. Once the decision has been taken to use ionising radiation for imaging in a particular patient, it is necessary to optimize the image acquisition process taking into account the diagnostic quality of the images and the radiation dose to the patient. Both image quality and radiation dose are affected by a number of parameters, knowledge of which permits scientifically based decision making. The authors of this second edition of Radiation Exposure and Image Quality in X-ray Diagnostic Radiology have spent many years studying the optimization of radiological imaging. In this book they present in detail the basic physical principles of diagnostic radiology and their application to clinical problems. Particular attention is devoted to evaluation of the dose to the patient, the influence of scattered radiation on image quality, the use of antiscatter grids, and optimization of image quality and dose. The final section is a supplement containing tables of data and graphical depictions of X-ray spectra, interaction coefficients, characteristics of X-ray beams, and other aspects relevant to patient dose calculations. In addition, a complementary CD-ROM contains a user-friendly Excel file database covering these aspects that can be used in the reader's own programs. Since the first edition, the text, figures, tables, and references have all been thoroughly updated, and more detailed attention is now paid to image quality and radiation exposure when using digital imaging and computed tomography. This book will be an invaluable aid to medical physicists when performing calculations relating to patient dose and image quality, and will also prove useful for diagnostic radiologists and engineers. (orig.)

A hand-held imaging probe for radio-guided surgery: physical performance and preliminary clinical experience

International Nuclear Information System (INIS)

Pitre, S.; Menard, L.; Charon, Y.; Solal, M.; Garbay, J.R.

2003-01-01

Improvements in the specificity of radiopharmaceutical compounds have been paralleled by an upsurge of interest in developing small detectors to assist surgeons in localizing tumour tissue during surgery. This study reports the main technical features and physical characteristics of a new hand-held gamma camera dedicated to accurate and real-time intra-operative imaging. First clinical experience is also reported. The POCI (Per-operative Compact Imager) camera consists of a head module composed of a high-resolution interchangeable lead collimator and a CsI(Na) crystal plate optically coupled to an intensified position-sensitive diode. The current prototype has a 40-mm diameter field of view, an outer diameter of 9.5 cm, a length of 9 cm and a weight of 1.2 kg. Overall detector imaging characteristics were evaluated by technetium-99m phantom measurements. Three patients with breast cancer previously scheduled to undergo sentinel lymph node detection were selected for the preliminary clinical experience. Preoperative images of the lymphatic basin obtained using the POCI camera were compared with conventional transcutaneous explorations using a non-imaging gamma probe. The full-width at half-maximum (FWHM) spatial resolution was investigated in both air and scattering medium; when the phantom was placed in contact with the collimator, the POCI camera exhibited a 3.2 mm FWHM. The corresponding sensitivity was 290 cps/MBq. The preliminary clinical results showed that POCI was able to predict the number and location of all SLNs. In one case, two deep radioactive nodes missed by the gamma probe were detected on the intra-operative images. This very initial experience demonstrates that the physical performance of the POCI camera is adequate for radio-guided surgery. These results are sufficiently encouraging to prompt further evaluation studies designed to determine the specific and optimal clinical role of intra-operative imaging devices

Radiation dose optimization research: Exposure technique approaches in CR imaging – A literature review

International Nuclear Information System (INIS)

Seeram, Euclid; Davidson, Rob; Bushong, Stewart; Swan, Hans

2013-01-01

The purpose of this paper is to review the literature on exposure technique approaches in Computed Radiography (CR) imaging as a means of radiation dose optimization in CR imaging. Specifically the review assessed three approaches: optimization of kVp; optimization of mAs; and optimization of the Exposure Indicator (EI) in practice. Only papers dating back to 2005 were described in this review. The major themes, patterns, and common findings from the literature reviewed showed that important features are related to radiation dose management strategies for digital radiography include identification of the EI as a dose control mechanism and as a “surrogate for dose management”. In addition the use of the EI has been viewed as an opportunity for dose optimization. Furthermore optimization research has focussed mainly on optimizing the kVp in CR imaging as a means of implementing the ALARA philosophy, and studies have concentrated on mainly chest imaging using different CR systems such as those commercially available from Fuji, Agfa, Kodak, and Konica-Minolta. These studies have produced “conflicting results”. In addition, a common pattern was the use of automatic exposure control (AEC) and the measurement of constant effective dose, and the use of a dose-area product (DAP) meter

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

Science.gov (United States)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Optimization of wavelet decomposition for image compression and feature preservation.

Science.gov (United States)

Lo, Shih-Chung B; Li, Huai; Freedman, Matthew T

2003-09-01

A neural-network-based framework has been developed to search for an optimal wavelet kernel that can be used for a specific image processing task. In this paper, a linear convolution neural network was employed to seek a wavelet that minimizes errors and maximizes compression efficiency for an image or a defined image pattern such as microcalcifications in mammograms and bone in computed tomography (CT) head images. We have used this method to evaluate the performance of tap-4 wavelets on mammograms, CTs, magnetic resonance images, and Lena images. We found that the Daubechies wavelet or those wavelets with similar filtering characteristics can produce the highest compression efficiency with the smallest mean-square-error for many image patterns including general image textures as well as microcalcifications in digital mammograms. However, the Haar wavelet produces the best results on sharp edges and low-noise smooth areas. We also found that a special wavelet whose low-pass filter coefficients are 0.32252136, 0.85258927, 1.38458542, and -0.14548269) produces the best preservation outcomes in all tested microcalcification features including the peak signal-to-noise ratio, the contrast and the figure of merit in the wavelet lossy compression scheme. Having analyzed the spectrum of the wavelet filters, we can find the compression outcomes and feature preservation characteristics as a function of wavelets. This newly developed optimization approach can be generalized to other image analysis applications where a wavelet decomposition is employed.

Image quality comparison between single energy and dual energy CT protocols for hepatic imaging

International Nuclear Information System (INIS)

Yao, Yuan; Pelc, Norbert J.; Ng, Joshua M.; Megibow, Alec J.

2016-01-01

Purpose: Multi-detector computed tomography (MDCT) enables volumetric scans in a single breath hold and is clinically useful for hepatic imaging. For simple tasks, conventional single energy (SE) computed tomography (CT) images acquired at the optimal tube potential are known to have better quality than dual energy (DE) blended images. However, liver imaging is complex and often requires imaging of both structures containing iodinated contrast media, where atomic number differences are the primary contrast mechanism, and other structures, where density differences are the primary contrast mechanism. Hence it is conceivable that the broad spectrum used in a dual energy acquisition may be an advantage. In this work we are interested in comparing these two imaging strategies at equal-dose and more complex settings. Methods: We developed numerical anthropomorphic phantoms to mimic realistic clinical CT scans for medium size and large size patients. MDCT images based on the defined phantoms were simulated using various SE and DE protocols at pre- and post-contrast stages. For SE CT, images from 60 kVp through 140 with 10 kVp steps were considered; for DE CT, both 80/140 and 100/140 kVp scans were simulated and linearly blended at the optimal weights. To make a fair comparison, the mAs of each scan was adjusted to match the reference radiation dose (120 kVp, 200 mAs for medium size patients and 140 kVp, 400 mAs for large size patients). Contrast-to-noise ratio (CNR) of liver against other soft tissues was used to evaluate and compare the SE and DE protocols, and multiple pre- and post-contrasted liver-tissue pairs were used to define a composite CNR. To help validate the simulation results, we conducted a small clinical study. Eighty-five 120 kVp images and 81 blended 80/140 kVp images were collected and compared through both quantitative image quality analysis and an observer study. Results: In the simulation study, we found that the CNR of pre-contrast SE image mostly

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

Science.gov (United States)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

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

Directory of Open Access Journals (Sweden)

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.

Study, development and clinical evaluation of a per-operative γ imager

International Nuclear Information System (INIS)

Menard, Laurent

1999-01-01

The precise localization and complete surgical ablation of tumors are one of the most important procedures in cancer treatment. In that context, the use, in operating room, of light hand-held detectors associated to radiopharmaceutical compounds for tumor labelling, plays a significant role in assisting surgeons in real-time detection of lesion. The POCI gamma imaging probe (Per-Operative Compact Imager), which is presented here, is precisely dedicated to improve the radio-guided operative cancer surgery efficiency by bringing a new tool discriminating between healthy and pathological tissues. To match the specifications of intra-operative detection, we chose to build our camera around an intensified position sensitive diode which appeared to be particularly suitable to achieve a high resolution small size imager. The optimal geometry of two gamma detection head modules, composed of parallel hole collimators and scintillation crystals, was then investigated by numerical simulations. From these technological solutions, a first prototype of POCI with a 24 mm diameter field of view has been developed. Its characterization has put forward a millimeter spatial resolution and a detection efficiency comparable to that of clinical gamma cameras and in agreement with the numerical predictions. Finally, in collaboration with Gustave Roussy, a first clinical evaluation of the POCI camera has been performed for sentinel ganglion pre-operative localization in patients afflicted by malignant melanomas or breast cancers. The preliminary results have already shown that the performances of POCI are compatible with intraoperative imaging purposes and suggest how this camera can boost the success rate of tumor removal surgeries for other cancerous diseases. (author)

Optimization of a Biometric System Based on Acoustic Images

Directory of Open Access Journals (Sweden)

Alberto Izquierdo Fuente

2014-01-01

Full Text Available On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced.

Optimization of a Biometric System Based on Acoustic Images

Science.gov (United States)

Izquierdo Fuente, Alberto; Del Val Puente, Lara; Villacorta Calvo, Juan J.; Raboso Mateos, Mariano

2014-01-01

On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced. PMID:24616643

[Microdose clinical trial--impact of PET molecular imaging].

Science.gov (United States)

Yano, Tsuneo; Watanabe, Yasuyoshi

2010-10-01

Microdose (MD) clinical trial and exploratory IND study including sub-therapeutic dose and therapeutic dose which are higher than microdoses are expected to bring about innovations in drug development. The outlines of guidances for microdose clinical trial and ICH-M3 (R2) issued by the MHLW in June, 2008, and February, 2010, are first explained, respectively, and some examples of their application to clinical developments of therapeutic drugs in the infection and cancer fields are introduced. Especially, thanks to the progress of molecular imaging research, a new field of drug development is explored by using imaging biomarkers for efficacy or safety evaluation which visualize biomarkers by PET imaging agents. Finally, the roadmap for drug development in infection and cancer fields utilizing PET molecular imaging is discussed.

Improved identification of cranial nerves using paired-agent imaging: topical staining protocol optimization through experimentation and simulation

Science.gov (United States)

Torres, Veronica C.; Wilson, Todd; Staneviciute, Austeja; Byrne, Richard W.; Tichauer, Kenneth M.

2018-03-01

Skull base tumors are particularly difficult to visualize and access for surgeons because of the crowded environment and close proximity of vital structures, such as cranial nerves. As a result, accidental nerve damage is a significant concern and the likelihood of tumor recurrence is increased because of more conservative resections that attempt to avoid injuring these structures. In this study, a paired-agent imaging method with direct administration of fluorophores is applied to enhance cranial nerve identification. Here, a control imaging agent (ICG) accounts for non-specific uptake of the nerve-targeting agent (Oxazine 4), and ratiometric data analysis is employed to approximate binding potential (BP, a surrogate of targeted biomolecule concentration). For clinical relevance, animal experiments and simulations were conducted to identify parameters for an optimized stain and rinse protocol using the developed paired-agent method. Numerical methods were used to model the diffusive and kinetic behavior of the imaging agents in tissue, and simulation results revealed that there are various combinations of stain time and rinse number that provide improved contrast of cranial nerves, as suggested by optimal measures of BP and contrast-to-noise ratio.

Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

Science.gov (United States)

Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

2018-02-01

Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

Clinical efficiency, image quality and dosimetric considerations

Energy Technology Data Exchange (ETDEWEB)

Arreola, M. [Director of Clinical Radiological Physics, Shands Hospital at the University of Florida College of Medicine, Gainesville, FL (United States)

2000-07-01

Three decades have passed since the first clinical use of the famous EMI Computed Axial Tomography (Cat) scanner. At the time, the prospects for clinical success of this innovative idea were not very good. Time, however, has proven otherwise as what is now simply known as Computed tomography (CT) has been boosted in each one of these decades for different reasons. In the 1970s, technological progress augmented by the realization of the importance of tomographic imaging got everything started; in the 1980s, the boom in health care demand in the US solidified its position and in the 1990s the technological explosion in computers and the imperative need to lower costs in the health care industry have prompted the most dramatic changes in the wy CT is utilized in the year 2000. Thus, different motivations have led the way of progress in CT at various times, and in spite of amazing developments in other crucial imaging modalities, such as ultrasound, Doppler ultrasound, digital subtraction angiography and magnetic resonance imaging, CT maintains its rightful place as the premiere imaging modality in the modern radiology department. This work covers the basic principles of tomographic image reconstruction, and how axial CT scanners progressed historically in the first two decades. Developments in X-ray tubes, and detection systems are highlighted, as well as the impact of clinical efficiency, image quality and patient doses. The basic construction of translate-rotate (1st and 2nd generation), rotate-rotate (3rd generation) and detector ring (4th generation) scanners are described. The so-called 5th generation scanner, the electron beam scanner, is also described, with its clinical and technical advantages and its inherent financial and maintenance disadvantages, which brought the advent of spiral and multi-slice scanners. These most recent developments in CT technology have opened a new era in the clinical use of CT; and although image quality has reached an expected

Clinical efficiency, image quality and dosimetric considerations

International Nuclear Information System (INIS)

Arreola, M.

2000-01-01

Three decades have passed since the first clinical use of the famous EMI Computed Axial Tomography (Cat) scanner. At the time, the prospects for clinical success of this innovative idea were not very good. Time, however, has proven otherwise as what is now simply known as Computed tomography (CT) has been boosted in each one of these decades for different reasons. In the 1970s, technological progress augmented by the realization of the importance of tomographic imaging got everything started; in the 1980s, the boom in health care demand in the US solidified its position and in the 1990s the technological explosion in computers and the imperative need to lower costs in the health care industry have prompted the most dramatic changes in the wy CT is utilized in the year 2000. Thus, different motivations have led the way of progress in CT at various times, and in spite of amazing developments in other crucial imaging modalities, such as ultrasound, Doppler ultrasound, digital subtraction angiography and magnetic resonance imaging, CT maintains its rightful place as the premiere imaging modality in the modern radiology department. This work covers the basic principles of tomographic image reconstruction, and how axial CT scanners progressed historically in the first two decades. Developments in X-ray tubes, and detection systems are highlighted, as well as the impact of clinical efficiency, image quality and patient doses. The basic construction of translate-rotate (1st and 2nd generation, rotate-rotate (3rd generation) and detector ring (4th generation) scanners are described. The so-called 5th generation scanner, the electron beam scanner, is also described, with its clinical and technical advantages and its inherent financial and maintenance disadvantages, which brought the advent of spiral and multi-slice scanners. These most recent developments in CT technology have opened a new era in the clinical use of CT; and although image quality has reached an expected

Application of Genetic Algorithm and Particle Swarm Optimization techniques for improved image steganography systems

Directory of Open Access Journals (Sweden)

Jude Hemanth Duraisamy

2016-01-01

Full Text Available Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA and Particle Swarm Optimization (PSO have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT and Finite Ridgelet Transform (FRIT are used in combination with GA and PSO to improve the efficiency of the image steganography system.

ProxImaL: efficient image optimization using proximal algorithms

KAUST Repository

Heide, Felix; Diamond, Steven; Nieß ner, Matthias; Ragan-Kelley, Jonathan; Heidrich, Wolfgang; Wetzstein, Gordon

2016-01-01

domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety

Computational Modeling of Medical Images of Brain Tumor Patients for Optimized Radiation Therapy Planning

DEFF Research Database (Denmark)

Agn, Mikael

In brain tumor radiation therapy, the aim is to maximize the delivered radiation dose to the targeted tumor and at the same time minimize the dose to sensitive healthy structures – so-called organs-at-risk (OARs). When planning a radiation therapy session, the tumor and the OARs therefore need...... to be delineated on medical images of the patient’s head, to be able to optimize a radiation dose plan. In clinical practice, the delineation is performed manually with limited assistance from automatic procedures, which is both time-consuming and typically suffers from poor reproducibility. There is, therefore...

Clinical PET/MR Imaging in Oncology

DEFF Research Database (Denmark)

Kjær, Andreas; Torigian, Drew A.

2016-01-01

. The question, therefore, arises regarding what the future clinical applications of PET/MR imaging will be. In this article, the authors discuss ways in which PET/MR imaging may be used in future applications that justify the added cost, predominantly focusing on oncologic applications. The authors suggest...

Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.

Science.gov (United States)

Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar

2017-11-03

Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.

Optimization of parameter values for complex pulse sequences by simulated annealing: application to 3D MP-RAGE imaging of the brain.

Science.gov (United States)

Epstein, F H; Mugler, J P; Brookeman, J R

1994-02-01

A number of pulse sequence techniques, including magnetization-prepared gradient echo (MP-GRE), segmented GRE, and hybrid RARE, employ a relatively large number of variable pulse sequence parameters and acquire the image data during a transient signal evolution. These sequences have recently been proposed and/or used for clinical applications in the brain, spine, liver, and coronary arteries. Thus, the need for a method of deriving optimal pulse sequence parameter values for this class of sequences now exists. Due to the complexity of these sequences, conventional optimization approaches, such as applying differential calculus to signal difference equations, are inadequate. We have developed a general framework for adapting the simulated annealing algorithm to pulse sequence parameter value optimization, and applied this framework to the specific case of optimizing the white matter-gray matter signal difference for a T1-weighted variable flip angle 3D MP-RAGE sequence. Using our algorithm, the values of 35 sequence parameters, including the magnetization-preparation RF pulse flip angle and delay time, 32 flip angles in the variable flip angle gradient-echo acquisition sequence, and the magnetization recovery time, were derived. Optimized 3D MP-RAGE achieved up to a 130% increase in white matter-gray matter signal difference compared with optimized 3D RF-spoiled FLASH with the same total acquisition time. The simulated annealing approach was effective at deriving optimal parameter values for a specific 3D MP-RAGE imaging objective, and may be useful for other imaging objectives and sequences in this general class.

Blurred image restoration using knife-edge function and optimal window Wiener filtering

Science.gov (United States)

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

Science.gov (United States)

Rong, Xing; Frey, Eric C

2013-08-01

Post-therapy quantitative 90Y bremsstrahlung single photon emission computed tomography (SPECT) has shown great potential to provide reliable activity estimates, which are essential for dose verification. Typically 90Y imaging is performed with high- or medium-energy collimators. However, the energy spectrum of 90Y bremsstrahlung photons is substantially different than typical for these collimators. In addition, dosimetry requires quantitative images, and collimators are not typically optimized for such tasks. Optimizing a collimator for 90Y imaging is both novel and potentially important. Conventional optimization methods are not appropriate for 90Y bremsstrahlung photons, which have a continuous and broad energy distribution. In this work, the authors developed a parallel-hole collimator optimization method for quantitative tasks that is particularly applicable to radionuclides with complex emission energy spectra. The authors applied the proposed method to develop an optimal collimator for quantitative 90Y bremsstrahlung SPECT in the context of microsphere radioembolization. To account for the effects of the collimator on both the bias and the variance of the activity estimates, the authors used the root mean squared error (RMSE) of the volume of interest activity estimates as the figure of merit (FOM). In the FOM, the bias due to the null space of the image formation process was taken in account. The RMSE was weighted by the inverse mass to reflect the application to dosimetry; for a different application, more relevant weighting could easily be adopted. The authors proposed a parameterization for the collimator that facilitates the incorporation of the important factors (geometric sensitivity, geometric resolution, and septal penetration fraction) determining collimator performance, while keeping the number of free parameters describing the collimator small (i.e., two parameters). To make the optimization results for quantitative 90Y bremsstrahlung SPECT more

An optimal big data workflow for biomedical image analysis

Directory of Open Access Journals (Sweden)

Aurelle Tchagna Kouanou

Full Text Available Background and objective: In the medical field, data volume is increasingly growing, and traditional methods cannot manage it efficiently. In biomedical computation, the continuous challenges are: management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of data, using machine learning and artificial intelligence techniques. It also allows a quick access to data using the NoSQL database. Thus, big data technologies include new frameworks to process medical data in a manner similar to biomedical images. It becomes very important to develop methods and/or architectures based on big data technologies, for a complete processing of biomedical image data. Method: This paper describes big data analytics for biomedical images, shows examples reported in the literature, briefly discusses new methods used in processing, and offers conclusions. We argue for adapting and extending related work methods in the field of big data software, using Hadoop and Spark frameworks. These provide an optimal and efficient architecture for biomedical image analysis. This paper thus gives a broad overview of big data analytics to automate biomedical image diagnosis. A workflow with optimal methods and algorithm for each step is proposed. Results: Two architectures for image classification are suggested. We use the Hadoop framework to design the first, and the Spark framework for the second. The proposed Spark architecture allows us to develop appropriate and efficient methods to leverage a large number of images for classification, which can be customized with respect to each other. Conclusions: The proposed architectures are more complete, easier, and are adaptable in all of the steps from conception. The obtained Spark architecture is the most complete, because it facilitates the implementation of algorithms with its embedded libraries. Keywords: Biomedical images, Big

Traceable working standards with SI units of radiance for characterizing the measurement performance of investigational clinical NIRF imaging devices

Science.gov (United States)

Zhu, Banghe; Rasmussen, John C.; Litorja, Maritoni; Sevick-Muraca, Eva M.

2017-03-01

All medical devices for Food and Drug market approval require specifications of performance based upon International System of Units (SI) or units derived from SI for reasons of traceability. Recently, near-infrared fluorescence (NIRF) imaging devices of a variety of designs have emerged on the market and in investigational clinical studies. Yet the design of devices used in the clinical studies vary widely, suggesting variable device performance. Device performance depends upon optimal excitation of NIRF imaging agents, rejection of backscattered excitation and ambient light, and selective collection of fluorescence emanating from the fluorophore. There remains no traceable working standards with SI units of radiance to enable prediction that a given molecular imaging agent can be detected in humans by a given NIRF imaging device. Furthermore, as technologies evolve and as NIRF imaging device components change, there remains no standardized means to track device improvements over time and establish clinical performance without involving clinical trials, often costly. In this study, we deployed a methodology to calibrate luminescent radiance of a stable, solid phantom in SI units of mW/cm2/sr for characterizing the measurement performance of ICCD and IsCMOS camera based NIRF imaging devices, such as signal-to-noise ratio (SNR) and contrast. The methodology allowed determination of superior SNR of the ICCD over the IsCMOS system; comparable contrast of ICCD and IsCMOS depending upon binning strategies.

Clinical and imaging findings in spinal cord arteriovenous malformations

International Nuclear Information System (INIS)

Kim, Sang Heum; Kim, Dong Ik; Yoon, Pyeong Ho; Jeon, Pyoung; Ihn, Yeon Kwon

1997-01-01

The purpose of this study is to evaluate the findings of magnetic resonance (MR) imaging and selective spinal angiography of spinal cord arteriovenous malformations (SCAVMs) and to investigate the correlation of these findings with the development of clinical symptoms. In 16 patients diagnosed as suffering from SCAVMs, MR imaging and selective spinal angiograms were retrospectively analyzed and correlated with clinical symptoms. Clinical data were reviewed, especially concerning the mode of onset of clinical symptoms, and MR images of SCAVMs were evaluated with regard to the following parameters: spinal cord swelling with T2 hyperintensity, cord atrophy, intramedullary hemorrhage, and contrast enhancement of the spinal cord. Selective spinal angiographic findings of SCAVMs were also evaluated in terms of the following , parameters: type of SCAVM, presence of aneurysms, and patterns of venous drainage. Imaging findings were also correlated with the development of clinical symptoms. Systematic evaluation of the findings of MR imaging and angiography provides detailed information on the type of AVM and status of the spinal cord parenchyma, and this can be correlated with clinical manifestations of SCAVM. In patients suffering from this condition, spinal cord dysfunction due to venous congestion appears to be the main cause of clinical symptoms. (author). 18 refs., 2 tabs., 3 figs

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization.

Science.gov (United States)

Pavan, Ana Luiza Menegatti; Rosa, Maria Eugênia Dela; Giacomini, Guilherme; Bacchim Neto, Fernando Antonio; Yamashita, Seizo; Vulcano, Luiz Carlos; Duarte, Sergio Barbosa; Miranda, José Ricardo de Arruda; de Pina, Diana Rodrigues

2016-01-01

Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone) in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air). Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p optimize veterinary X-ray procedures.

Optimization-based reconstruction for reduction of CBCT artifact in IGRT

Science.gov (United States)

Xia, Dan; Zhang, Zheng; Paysan, Pascal; Seghers, Dieter; Brehm, Marcus; Munro, Peter; Sidky, Emil Y.; Pelizzari, Charles; Pan, Xiaochuan

2016-04-01

Kilo-voltage cone-beam computed tomography (CBCT) plays an important role in image guided radiation therapy (IGRT) by providing 3D spatial information of tumor potentially useful for optimizing treatment planning. In current IGRT CBCT system, reconstructed images obtained with analytic algorithms, such as FDK algorithm and its variants, may contain artifacts. In an attempt to compensate for the artifacts, we investigate optimization-based reconstruction algorithms such as the ASD-POCS algorithm for potentially reducing arti- facts in IGRT CBCT images. In this study, using data acquired with a physical phantom and a patient subject, we demonstrate that the ASD-POCS reconstruction can significantly reduce artifacts observed in clinical re- constructions. Moreover, patient images reconstructed by use of the ASD-POCS algorithm indicate a contrast level of soft-tissue improved over that of the clinical reconstruction. We have also performed reconstructions from sparse-view data, and observe that, for current clinical imaging conditions, ASD-POCS reconstructions from data collected at one half of the current clinical projection views appear to show image quality, in terms of spatial and soft-tissue-contrast resolution, higher than that of the corresponding clinical reconstructions.

Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images.

Science.gov (United States)

Basset, Antoine; Boulanger, Jérôme; Salamero, Jean; Bouthemy, Patrick; Kervrann, Charles

2015-11-01

Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) automatically selects the optimal scale corresponding to the most frequent spot size in the image. Four criteria are proposed and compared to determine the optimal scale in a scale-space framework. Then, the segmentation stage amounts to thresholding the LoG of the intensity image. In contrast to other methods, the threshold is locally adapted given a probability of false alarm (PFA) specified by the user for the whole set of images to be processed. The local threshold is automatically derived from the PFA value and local image statistics estimated in a window whose size is not a critical parameter. We also propose a new data set for benchmarking, consisting of six collections of one hundred images each, which exploits backgrounds extracted from real microscopy images. We have carried out an extensive comparative evaluation on several data sets with ground-truth, which demonstrates that ATLAS outperforms existing methods. ATLAS does not need any fine parameter tuning and requires very low computation time. Convincing results are also reported on real total internal reflection fluorescence microscopy images.

Practical Approach for the Clinical Use of Dopamine Transporter Imaging

International Nuclear Information System (INIS)

Kim, Jae Seung

2008-01-01

Dopamine transporter imaging is useful in the diagnosis of Parkinson's disease and the most successful technique in the clinical use of neuroreceptor imaging. Recently, several radiopharmaceuticals including I-123 FP-CIT, Tc-99m TRODAT, and F-18 FP-CIT for dopamine transporter imaging have been approved for the routine clinical use in several European countries, Taiwan and Korea, respectively. This review summarized the practical issue for the routine clinical examination of dopamine transporter imaging

Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

Directory of Open Access Journals (Sweden)

Chae Young Lee

Full Text Available The purposes of this study were to optimize a proton computed tomography system (pCT for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

Science.gov (United States)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

International Nuclear Information System (INIS)

Raghunath, N; Faber, T L; Suryanarayanan, S; Votaw, J R

2009-01-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

Energy Technology Data Exchange (ETDEWEB)

Raghunath, N; Faber, T L; Suryanarayanan, S; Votaw, J R [Department of Radiology, Emory University Hospital, 1364 Clifton Road, N.E. Atlanta, GA 30322 (United States)], E-mail: John.Votaw@Emory.edu

2009-02-07

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

First-order Convex Optimization Methods for Signal and Image Processing

DEFF Research Database (Denmark)

Jensen, Tobias Lindstrøm

2012-01-01

In this thesis we investigate the use of first-order convex optimization methods applied to problems in signal and image processing. First we make a general introduction to convex optimization, first-order methods and their iteration complexity. Then we look at different techniques, which can...... be used with first-order methods such as smoothing, Lagrange multipliers and proximal gradient methods. We continue by presenting different applications of convex optimization and notable convex formulations with an emphasis on inverse problems and sparse signal processing. We also describe the multiple...

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

Science.gov (United States)

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Zhiwei Ye

2015-01-01

Full Text Available Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Optimism and recovery after acute coronary syndrome: a clinical cohort study.

Science.gov (United States)

Ronaldson, Amy; Molloy, Gerard J; Wikman, Anna; Poole, Lydia; Kaski, Juan-Carlos; Steptoe, Andrew

2015-04-01

Optimism is associated with reduced cardiovascular mortality, but its impact on recovery after acute coronary syndrome (ACS) is poorly understood. We hypothesized that greater optimism would lead to more effective physical and emotional adaptation after ACS and would buffer the impact of persistent depressive symptoms on clinical outcomes. This prospective observational clinical study took place in an urban general hospital and involved 369 patients admitted with a documented ACS. Optimism was assessed with a standardized questionnaire. The main outcomes were physical health status, depressive symptoms, smoking, physical activity, and fruit and vegetable consumption measured 12 months after ACS, and composite major adverse cardiac events (cardiovascular death, readmission with reinfarction or unstable angina, and coronary artery bypass graft surgery) assessed over an average of 45.7 months. We found that optimism predicted better physical health status 12 months after ACS independently of baseline physical health, age, sex, ethnicity, social deprivation, and clinical risk factors (B = 0.65, 95% confidence interval [CI] = 0.10-1.20). Greater optimism also predicted reduced risk of depressive symptoms (odds ratio = 0.82, 95% CI = 0.74-0.90), more smoking cessation, and more fruit and vegetable consumption at 12 months. Persistent depressive symptoms 12 months after ACS predicted major adverse cardiac events over subsequent years (odds ratio = 2.56, 95% CI = 1.16-5.67), but only among individuals low in optimism (optimism × depression interaction; p = .014). Optimism predicts better physical and emotional health after ACS. Measuring optimism may help identify individuals at risk. Pessimistic outlooks can be modified, potentially leading to improved recovery after major cardiac events.

A phase 2 clinical study of 99mTc-MAG3 injectable, a dynamic renal imaging agent

International Nuclear Information System (INIS)

Torizuka, Kanji; Yamamoto, Kazutaka; Nishibuchi, Shigeo; Ishibashi, Akira; Ikekubo, Katsuji.

1993-01-01

A phase 2 clinical study of 99m Tc-mercapto acetyl glycylglycylglycine ( 99m Tc-MAG3) injectable, a new dynamic renal imaging agent, was performed in 110 patients with renal and/or urinary disorders to evaluate the safety, efficacy and optimal dose of this agent. Neither adverse reactions nor abnormal laboratory findings due to intravenous administration of 99m Tc-MAG3 were observed. The investigators evaluated the clinical efficacy of 99m Tc-MAG3 was to be effective in 96 of 97 cases. Among the doses of 92.5 MBq, 370 MBq and 555 MBq, the dose of 92.5 MBq was not large enough to provide adequate-quality blood flow images or reliable information for evaluation of the renal blood flow. It was concluded that the optimal dose range of 99m Tc-MAG3 was 185-555 MBq with 370 MBq as the standard dose. Also, we summarize that 555 MBq is especially recommendable when detailed blood flow information is required. These results indicate that 99m Tc-MAG3 injectable is useful for the diagnosis of renal and urinary disorders. (author)

Optimization of an Image-Based Talking Head System

Directory of Open Access Journals (Sweden)

Kang Liu

2009-01-01

Full Text Available This paper presents an image-based talking head system, which includes two parts: analysis and synthesis. The audiovisual analysis part creates a face model of a recorded human subject, which is composed of a personalized 3D mask as well as a large database of mouth images and their related information. The synthesis part generates natural looking facial animations from phonetic transcripts of text. A critical issue of the synthesis is the unit selection which selects and concatenates these appropriate mouth images from the database such that they match the spoken words of the talking head. Selection is based on lip synchronization and the similarity of consecutive images. The unit selection is refined in this paper, and Pareto optimization is used to train the unit selection. Experimental results of subjective tests show that most people cannot distinguish our facial animations from real videos.

Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis

DEFF Research Database (Denmark)

Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan

2012-01-01

Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization s...

Carotid and vertebral artery dissections: clinical aspects, imaging features and endovascular treatment

International Nuclear Information System (INIS)

Flis, Christine M.; Jaeger, H.R.; Sidhu, Paul S.

2007-01-01

Extracranial arterial dissections are a recognised cause of stroke, particularly in young adults. Clinical diagnosis may be difficult, and the classical triad of symptoms is uncommon. Imaging plays a pivotal role in the diagnosis of extracranial arterial dissections, and this review provides a detailed discussion of the relative merits and limitations of currently available imaging modalities. Conventional arteriography has been the reference standard for demonstrating an intimal flap and double lumen, which are the hallmarks of a dissection, and for detecting complications such as stenosis, occlusion or pseudoaneurysm. Noninvasive vascular imaging methods, such as ultrasound (US), magnetic resonance angiography (MRA) and computed tomography angiography (CTA) are increasingly replacing conventional angiography for the diagnosis of carotid and vertebral dissections. Ultrasound provides dynamic and ''real-time'' information regarding blood flow. Source data of MRA and CTA and additional cross-sectional images can provide direct visualisation of the mural haematoma and information about the vessel lumen. Anticoagulation to prevent strokes is the mainstay of medical treatment, but randomised trials to define the optimal treatment regime are lacking. Surgery has a limited role in management of dissections, but endovascular procedures are gaining importance for treatment of complications and if medical management fails. (orig.)

Clinical advance in radionuclide imaging of pulmonary cancer

International Nuclear Information System (INIS)

Deng Zhiyong; Yang Lichun

2008-01-01

Radionuclide imaging of pulmonary cancer develops very rapidly in recent years. Its important value on the diagnosis, staging, monitoring recur and metastasis after treatment, and judging the curative effect and prognosis has been demonstrated. Clinicians pay more attention to it than before. This present article introduces the imaging principle, clinical use, good and bad points, progress situation of 67 Ga, 201 Tl, 99 Tc m , 18 F and their labelled compounds, which are more commonly used in clinical. And introduces the clinical progress of radionuclide imaging of pulmonary neoplasm concerning 99 Tc m -sestamibi ( 99 Tc m -MIBI), 99 Tc m -HL91 and 18 F-fluorodeoxyglucose ( 18 F-FDG) with emphasis. (authors)

How to COAAD Images. II. A Coaddition Image that is Optimal for Any Purpose in the Background-dominated Noise Limit

Energy Technology Data Exchange (ETDEWEB)

Zackay, Barak; Ofek, Eran O. [Department of Particle Physics and Astrophysics, Weizmann Institute of Science, 76100 Rehovot (Israel)

2017-02-20

Image coaddition is one of the most basic operations that astronomers perform. In Paper I, we presented the optimal ways to coadd images in order to detect faint sources and to perform flux measurements under the assumption that the noise is approximately Gaussian. Here, we build on these results and derive from first principles a coaddition technique that is optimal for any hypothesis testing and measurement (e.g., source detection, flux or shape measurements, and star/galaxy separation), in the background-noise-dominated case. This method has several important properties. The pixels of the resulting coadded image are uncorrelated. This image preserves all the information (from the original individual images) on all spatial frequencies. Any hypothesis testing or measurement that can be done on all the individual images simultaneously, can be done on the coadded image without any loss of information. The PSF of this image is typically as narrow, or narrower than the PSF of the best image in the ensemble. Moreover, this image is practically indistinguishable from a regular single image, meaning that any code that measures any property on a regular astronomical image can be applied to it unchanged. In particular, the optimal source detection statistic derived in Paper I is reproduced by matched filtering this image with its own PSF. This coaddition process, which we call proper coaddition, can be understood as the maximum signal-to-noise ratio measurement of the Fourier transform of the image, weighted in such a way that the noise in the entire Fourier domain is of equal variance. This method has important implications for multi-epoch seeing-limited deep surveys, weak lensing galaxy shape measurements, and diffraction-limited imaging via speckle observations. The last topic will be covered in depth in future papers. We provide an implementation of this algorithm in MATLAB.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los

2013-11-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los; Schö nlieb, Carola-Bibiane

2013-01-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Optimization of MR imaging for extracranial head and neck lesions

International Nuclear Information System (INIS)

Dalley, R.W.; Maravilla, K.R.; Cohen, W.

1989-01-01

The authors have used a 1.5T MR imager to study 28 pathologically proven extracranial head and neck lesions. Multiple pulse sequences were performed pre-and/or post-gadolinium, including T1-weighted, short TI inversion-recovery (STIR), spin-density, and T2-weighted sequences. T1-weighted images provided excellent anatomic detail but relatively poor muscle/lesion contrast. Gadolinium often improved lesion visibility; however, discrimination from surrounding fat was impaired. Postcontrast T2-weighted images seemed to provide better lesion conspicuity than did pre-gadolinium images. STIR imaging provided the highest lesion conspicuity in fatty areas. No single sequence was optimal for all head and neck imaging. The authors analyze the advantages and limitations of each sequence and formulate rational imaging protocols based on the primary region of interest

Optimization of Iron Oxide Tracer Synthesis for Magnetic Particle Imaging

Directory of Open Access Journals (Sweden)

Sabina Ziemian

2018-03-01

Full Text Available The optimization of iron oxide nanoparticles as tracers for magnetic particle imaging (MPI alongside the development of data acquisition equipment and image reconstruction techniques is crucial for the required improvements in image resolution and sensitivity of MPI scanners. We present a large-scale water-based synthesis of multicore superparamagnetic iron oxide nanoparticles stabilized with dextran (MC-SPIONs. We also demonstrate the preparation of single core superparamagnetic iron oxide nanoparticles in organic media, subsequently coated with a poly(ethylene glycol gallic acid polymer and phase transferred to water (SC-SPIONs. Our aim was to obtain long-term stable particles in aqueous media with high MPI performance. We found that the amplitude of the third harmonic measured by magnetic particle spectroscopy (MPS at 10 mT is 2.3- and 5.8-fold higher than Resovist for the MC-SPIONs and SC-SPIONs, respectively, revealing excellent MPI potential as compared to other reported MPI tracer particle preparations. We show that the reconstructed MPI images of phantoms using optimized multicore and specifically single-core particles are superior to that of commercially available Resovist, which we utilize as a reference standard, as predicted by MPS.

Perinatal clinical and imaging features of CLOVES syndrome

Energy Technology Data Exchange (ETDEWEB)

Fernandez-Pineda, Israel [Virgen del Rocio Children' s Hospital, Department of Pediatric Surgery, Seville (Spain); Fajardo, Manuel [Virgen del Rocio Children' s Hospital, Department of Pediatric Radiology, Seville (Spain); Chaudry, Gulraiz; Alomari, Ahmad I. [Children' s Hospital Boston and Harvard Medical School, Division of Vascular and Interventional Radiology, Boston, MA (United States)

2010-08-15

We report a neonate with antenatal imaging features suggestive of CLOVES syndrome. Postnatal clinical and imaging findings confirmed the diagnosis, with the constellation of truncal overgrowth, cutaneous capillary malformation, lymphatic and musculoskeletal anomalies. The clinical, radiological and histopathological findings noted in this particular phenotype help differentiate it from other overgrowth syndromes with complex vascular anomalies. (orig.)

Optimization of SPECT calibration for quantification of images applied to dosimetry with iodine-131

International Nuclear Information System (INIS)

Carvalho, Samira Marques de

2018-01-01

SPECT systems calibration plays an essential role in the accuracy of the quantification of images. In this work, in its first stage, an optimized SPECT calibration method was proposed for 131 I studies, considering the partial volume effect (PVE) and the position of the calibration source. In the second stage, the study aimed to investigate the impact of count density and reconstruction parameters on the determination of the calibration factor and the quantification of the image in dosimetry studies, considering the reality of clinical practice in Brazil. In the final step, the study aimed evaluating the influence of several factors in the calibration for absorbed dose calculation using Monte Carlo simulations (MC) GATE code. Calibration was performed by determining a calibration curve (sensitivity versus volume) obtained by applying different thresholds. Then, the calibration factors were determined with an exponential function adjustment. Images were performed with high and low counts densities for several source positions within the simulator. To validate the calibration method, the calibration factors were used for absolute quantification of the total reference activities. The images were reconstructed adopting two approaches of different parameters, usually used in patient images. The methodology developed for the calibration of the tomographic system was easier and faster to implement than other procedures suggested to improve the accuracy of the results. The study also revealed the influence of the location of the calibration source, demonstrating better precision in the absolute quantification considering the location of the target region during the calibration of the system. The study applied in the Brazilian thyroid protocol suggests the revision of the calibration of the SPECT system, including different positions for the reference source, besides acquisitions considering the Signal to Noise Ratio (SNR) of the images. Finally, the doses obtained with the

Magnetic resonance cardiac perfusion imaging-a clinical perspective

International Nuclear Information System (INIS)

Hunold, Peter; Schlosser, Thomas; Barkhausen, Joerg

2006-01-01

Coronary artery disease (CAD) with its clinical appearance of stable or unstable angina and acute myocardial infarction is the leading cause of death in developed countries. In view of increasing costs and the rising number of CAD patients, there has been a major interest in reliable non-invasive imaging techniques to identify CAD in an early (i.e. asymptomatic) stage. Since myocardial perfusion deficits appear very early in the ''ischemic cascade'', a major breakthrough would be the non-invasive quantification of myocardial perfusion before functional impairment might be detected. Therefore, there is growing interest in other, target-organ-specific parameters, such as relative and absolute myocardial perfusion imaging. Magnetic resonance (MR) imaging has been proven to offer attractive concepts in this respect. However, some important difficulties have not been resolved so far, which still causes uncertainty and prevents the broad application of MR perfusion imaging in a clinical setting. This review explores recent technical developments in MR hardware, software and contrast agents, as well as their impact on the current and future clinical status of MR imaging of first-pass myocardial perfusion imaging. (orig.)

Magnetic resonance cardiac perfusion imaging-a clinical perspective

Energy Technology Data Exchange (ETDEWEB)

Hunold, Peter; Schlosser, Thomas; Barkhausen, Joerg [University Hospital, Department of Diagnostic and Interventional Radiology and Neuroradiology, Essen (Germany)

2006-08-15

Coronary artery disease (CAD) with its clinical appearance of stable or unstable angina and acute myocardial infarction is the leading cause of death in developed countries. In view of increasing costs and the rising number of CAD patients, there has been a major interest in reliable non-invasive imaging techniques to identify CAD in an early (i.e. asymptomatic) stage. Since myocardial perfusion deficits appear very early in the ''ischemic cascade'', a major breakthrough would be the non-invasive quantification of myocardial perfusion before functional impairment might be detected. Therefore, there is growing interest in other, target-organ-specific parameters, such as relative and absolute myocardial perfusion imaging. Magnetic resonance (MR) imaging has been proven to offer attractive concepts in this respect. However, some important difficulties have not been resolved so far, which still causes uncertainty and prevents the broad application of MR perfusion imaging in a clinical setting. This review explores recent technical developments in MR hardware, software and contrast agents, as well as their impact on the current and future clinical status of MR imaging of first-pass myocardial perfusion imaging. (orig.)

Optimizing value utilizing Toyota Kata methodology in a multidisciplinary clinic.

Science.gov (United States)

Merguerian, Paul A; Grady, Richard; Waldhausen, John; Libby, Arlene; Murphy, Whitney; Melzer, Lilah; Avansino, Jeffrey

2015-08-01

Value in healthcare is measured in terms of patient outcomes achieved per dollar expended. Outcomes and cost must be measured at the patient level to optimize value. Multidisciplinary clinics have been shown to be effective in providing coordinated and comprehensive care with improved outcomes, yet tend to have higher cost than typical clinics. We sought to lower individual patient cost and optimize value in a pediatric multidisciplinary reconstructive pelvic medicine (RPM) clinic. The RPM clinic is a multidisciplinary clinic that takes care of patients with anomalies of the pelvic organs. The specialties involved include Urology, General Surgery, Gynecology, and Gastroenterology/Motility. From May 2012 to November 2014 we performed time-driven activity-based costing (TDABC) analysis by measuring provider time for each step in the patient flow. Using observed time and the estimated hourly cost of each of the providers we calculated the final cost at the individual patient level, targeting clinic preparation. We utilized Toyota Kata methodology to enhance operational efficiency in an effort to optimize value. Variables measured included cost, time to perform a task, number of patients seen in clinic, percent value-added time (VAT) to patients (face to face time) and family experience scores (FES). At the beginning of the study period, clinic costs were $619 per patient. We reduced conference time from 6 min/patient to 1 min per patient, physician preparation time from 8 min to 6 min and increased Medical Assistant (MA) preparation time from 9.5 min to 20 min, achieving a cost reduction of 41% to $366 per patient. Continued improvements further reduced the MA preparation time to 14 min and the MD preparation time to 5 min with a further cost reduction to $194 (69%) (Figure). During this study period, we increased the number of appointments per clinic. We demonstrated sustained improvement in FES with regards to the families overall experience with their providers

Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm

Directory of Open Access Journals (Sweden)

N. Sri Madhava Raja

2014-01-01

Full Text Available Histogram based multilevel thresholding approach is proposed using Brownian distribution (BD guided firefly algorithm (FA. A bounded search technique is also presented to improve the optimization accuracy with lesser search iterations. Otsu’s between-class variance function is maximized to obtain optimal threshold level for gray scale images. The performances of the proposed algorithm are demonstrated by considering twelve benchmark images and are compared with the existing FA algorithms such as Lévy flight (LF guided FA and random operator guided FA. The performance assessment comparison between the proposed and existing firefly algorithms is carried using prevailing parameters such as objective function, standard deviation, peak-to-signal ratio (PSNR, structural similarity (SSIM index, and search time of CPU. The results show that BD guided FA provides better objective function, PSNR, and SSIM, whereas LF based FA provides faster convergence with relatively lower CPU time.

Incidental ferumoxytol artifacts in clinical brain MR imaging

Energy Technology Data Exchange (ETDEWEB)

Bowser, Bruce A.; Campeau, Norbert G.; Carr, Carrie M.; Diehn, Felix E.; McDonald, Jennifer S.; Miller, Gary M.; Kaufmann, Timothy J. [Mayo Clinic, Department of Radiology, Rochester, MN (United States)

2016-11-15

Ferumoxytol (Feraheme) is a parenteral therapy approved for treatment of iron deficiency anemia. The product insert for ferumoxytol states that it may affect the diagnostic ability of MRI for up to 3 months. However, the expected effects may not be commonly recognized among clinical neuroradiologists. Our purpose is to describe the artifacts we have seen at our institution during routine clinical practice. We reviewed the patients at our institution that had brain MRI performed within 90 days of receiving intravenous ferumoxytol. The imaging was reviewed for specific findings, including diffusion-weighted imaging vascular susceptibility artifact, gradient-echo echo-planar T2*-weighted vascular susceptibility artifact, SWI/SWAN vascular susceptibility artifact, hypointense vascular signal on T2-weighted images, pre-gadolinium contrast vascular enhancement on magnetization-prepared rapid acquisition gradient echo (MPRAGE) imaging, and effects on post-gadolinium contrast T1 imaging. Multiple artifacts were observed in patients having a brain MRI within 3 days of receiving intravenous ferumoxytol. These included susceptibility artifact on DWI, GRE, and SWAN/SWI imaging, pre-gadolinium contrast increased vascular signal on MPRAGE imaging, and decreased expected enhancement on post-gadolinium contrast T1-weighted imaging. Ferumoxytol can create imaging artifacts which complicate clinical interpretation when brain MRI is performed within 3 days of administration. Recognition of the constellation of artifacts produced by ferumoxytol is important in order to obviate additional unnecessary examinations and mitigate errors in interpretation. (orig.)

Clinical stage T1c prostate cancer: evaluation with endorectal MR imaging and MR spectroscopic imaging.

Science.gov (United States)

Zhang, Jingbo; Hricak, Hedvig; Shukla-Dave, Amita; Akin, Oguz; Ishill, Nicole M; Carlino, Lauren J; Reuter, Victor E; Eastham, James A

2009-11-01

To assess the diagnostic accuracy of endorectal magnetic resonance (MR) imaging and MR spectroscopic imaging for prediction of the pathologic stage of prostate cancer and the presence of clinically nonimportant disease in patients with clinical stage T1c prostate cancer. The institutional review board approved-and waived the informed patient consent requirement for-this HIPAA-compliant study involving 158 patients (median age, 58 years; age range, 40-76 years) who had clinical stage T1c prostate cancer, had not been treated preoperatively, and underwent combined 1.5-T endorectal MR imaging-MR spectroscopic imaging between January 2003 and March 2004 before undergoing radical prostatectomy. On the MR images and combined endorectal MR-MR spectroscopic images, two radiologists retrospectively and independently rated the likelihood of cancer in 12 prostate regions and the likelihoods of extracapsular extension (ECE), seminal vesicle invasion (SVI), and adjacent organ invasion by using a five-point scale, and they determined the probability of clinically nonimportant prostate cancer by using a four-point scale. Whole-mount step-section pathology maps were used for imaging-pathologic analysis correlation. Receiver operating characteristic curves were constructed and areas under the curves (AUCs) were estimated nonparametrically for assessment of reader accuracy. At surgical-pathologic analysis, one (0.6%) patient had no cancer; 124 (78%) patients, organ-confined (stage pT2) disease; 29 (18%) patients, ECE (stage pT3a); two (1%) patients, SVI (stage pT3b); and two (1%) patients, bladder neck invasion (stage pT4). Forty-six (29%) patients had a total tumor volume of less than 0.5 cm(3). With combined MR imaging-MR spectroscopic imaging, the two readers achieved 80% accuracy in disease staging and AUCs of 0.62 and 0.71 for the prediction of clinically nonimportant cancer. Clinical stage T1c prostate cancers are heterogeneous in pathologic stage and volume. MR imaging may

Parotid lymphomas - clinical and computed tomogrphic imaging ...

African Journals Online (AJOL)

Parotid lymphomas - clinical and computed tomogrphic imaging features. ... South African Journal of Surgery ... Lymphoma has a clinical presentation similar ... CT scanning is a useful adjunctive investigation to determine the site and extent of ...

The Impact of Optimal Respiratory Gating and Image Noise on Evaluation of Intratumor Heterogeneity on 18F-FDG PET Imaging of Lung Cancer.

Science.gov (United States)

Grootjans, Willem; Tixier, Florent; van der Vos, Charlotte S; Vriens, Dennis; Le Rest, Catherine C; Bussink, Johan; Oyen, Wim J G; de Geus-Oei, Lioe-Fee; Visvikis, Dimitris; Visser, Eric P

2016-11-01

Accurate measurement of intratumor heterogeneity using parameters of texture on PET images is essential for precise characterization of cancer lesions. In this study, we investigated the influence of respiratory motion and varying noise levels on quantification of textural parameters in patients with lung cancer. We used an optimal-respiratory-gating algorithm on the list-mode data of 60 lung cancer patients who underwent 18 F-FDG PET. The images were reconstructed using a duty cycle of 35% (percentage of the total acquired PET data). In addition, nongated images of varying statistical quality (using 35% and 100% of the PET data) were reconstructed to investigate the effects of image noise. Several global image-derived indices and textural parameters (entropy, high-intensity emphasis, zone percentage, and dissimilarity) that have been associated with patient outcome were calculated. The clinical impact of optimal respiratory gating and image noise on assessment of intratumor heterogeneity was evaluated using Cox regression models, with overall survival as the outcome measure. The threshold for statistical significance was adjusted for multiple comparisons using Bonferroni correction. In the lower lung lobes, respiratory motion significantly affected quantification of intratumor heterogeneity for all textural parameters (P 0.007). The mean increase in entropy, dissimilarity, zone percentage, and high-intensity emphasis was 1.3% ± 1.5% (P = 0.02), 11.6% ± 11.8% (P = 0.006), 2.3% ± 2.2% (P = 0.002), and 16.8% ± 17.2% (P = 0.006), respectively. No significant differences were observed for lesions in the upper lung lobes (P > 0.007). Differences in the statistical quality of the PET images affected the textural parameters less than respiratory motion, with no significant difference observed. The median follow-up time was 35 mo (range, 7-39 mo). In multivariate analysis for overall survival, total lesion glycolysis and high-intensity emphasis were the two most

Iterative choice of the optimal regularization parameter in TV image deconvolution

International Nuclear Information System (INIS)

Sixou, B; Toma, A; Peyrin, F; Denis, L

2013-01-01

We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section

Applying GA for Optimizing the User Query in Image and Video Retrieval

OpenAIRE

Ehsan Lotfi

2014-01-01

In an information retrieval system, the query can be made by user sketch. The new method presented here, optimizes the user sketch and applies the optimized query to retrieval the information. This optimization may be used in Content-Based Image Retrieval (CBIR) and Content-Based Video Retrieval (CBVR) which is based on trajectory extraction. To optimize the retrieval process, one stage of retrieval is performed by the user sketch. The retrieval criterion is based on the proposed distance met...

16-slice multi-detector row CT coronary angiography: image quality and optimization of the image reconstruction window

International Nuclear Information System (INIS)

Kim, Yoo Kyung; Shim, Sung Shine; Lim, Soo Mee; Hwang, Ji Young; Kim, Yoon Kyung

2005-01-01

The purpose of this experiment is to investigate the image quality of CT coronary angiography using a 16-slice multi-detector row CT and to determine the optimal image reconstruction window. CT coronary angiography was obtained in 36 nonsymptomatic volunteers using a 16-slice multi-detector row CT (SOMATOM Sensation, Siemens Medical System). The mean heart rates were 70 beats per minute (bpm) or less in 18 persons and more than 70 bpm in 18 persons. Eleven data sets were obtained for each patient (reconstructed at 30%-80% of the cardiac cycle with an increment of 5%). Image quality of the eight coronary segments [left main coronary artery (LM), proximal and middle segments of left anterior descending artery (p-LAD, m-LAN) and left circumflex coronary artery (p-LCx, m-LCx) and proximal, middle and distal segments of right coronary artery (p-RCA, m-RCA, d-RCA)] was assessed. The optimal reconstruction windows in the cardiac cycle for the best image quality were 60-70% for the segments of the LM, LAD, and LC arteries in two groups (bpm 70) and 55-65% (bpm 70) for the segments of the RCA. On the best dataset for each coronary segment, the following diagnostic image quality was achieved in the two groups: LM: 100%, 83%; p-LAD: 100%, 88% m-LAD: 100%, 72%; p-LCx: 100%, 72%; m-LCx: 100%, 72%; p-RCA: 94%, 72%; m-RCA: 61%, 50%; d-RCA: 100%, 80%. The 16 slice multi-detector row CT scan provided visualization of the coronary arteries with high resolution. Especially in the group with a mean heart rate of 70 bpm or less, all the coronary segments except the RCA showed diagnostic image quality. Optimal image quality was achieved with a 60-70% trigger delay for all coronary arterial segments, but the best images of RCA were achieved in the earlier cardiac phase in the patients with a mean heart rate of more than 70 bpm

Optimized curve design for image analysis using localized geodesic distance transformations

Science.gov (United States)

Braithwaite, Billy; Niska, Harri; Pöllänen, Irene; Ikonen, Tiia; Haataja, Keijo; Toivanen, Pekka; Tolonen, Teemu

2015-03-01

We consider geodesic distance transformations for digital images. Given a M × N digital image, a distance image is produced by evaluating local pixel distances. Distance Transformation on Curved Space (DTOCS) evaluates shortest geodesics of a given pixel neighborhood by evaluating the height displacements between pixels. In this paper, we propose an optimization framework for geodesic distance transformations in a pattern recognition scheme, yielding more accurate machine learning based image analysis, exemplifying initial experiments using complex breast cancer images. Furthermore, we will outline future research work, which will complete the research work done for this paper.

Joubert syndrome: Clinical manifestations and magnetic resonance imaging

International Nuclear Information System (INIS)

Kim, Seung Cheol; Kim, In One; Yoon, Yong Kyu; Yeon, Kyung Mo; Kim, Woo Sun; Song, Jong Gi; Hwang, Yong Seung

1994-01-01

Joubert syndrome presents neonatal respiratory abnormalities and other clinical manifestations. Pathologically the patients show hypoplasia or agenesis of cerebellar vermis and other intracranial anomalies. Our purpose is to evaluate the clinical manifestations and MR findings of Joubert syndrome. Among the patient presenting with clinical stigmata of Joubert syndrome and agenesis of vermis on MR imaging, eight patients who did not satisfied the criteria of Dandy-Walker malformation, tectocerebellar dysraphia and rhombencephalosynapsis were selected. MR findings and clinical manifestation were analyzed. On MR imaging, agenesis of the cerebellar vermis (all cases), hypoplasia of the cerebellar peduncle (6 cases), fourth ventricular contour deformity (6 cases), tentorial elevation (4 caes), deformity of the lateral ventricles (4 cases), dysgenesis of the straight sinus (3 cases) were demonstrated. Other findings were abnormalities of corpus callosum (3 cases), falx anomalies (3 case), occipital encephalomeningocele (2 cases) and fluid collection in posterior cranial fossa (2 cases). Clinical manifestations were developmental delay (5 cases), abnormal eyeball movement (3 cases), hypotonia (2 cases), neonatal respiratory abnormality (2 cases), etc. Joubert syndrome showed various clinical manifestations and intracranial anomalies. MR imaging is an useful modality in detection of the cerebellar vermian agenesis and other anomalies of the patients

Barrett's esophagus: clinical features, obesity, and imaging.

LENUS (Irish Health Repository)

Quigley, Eamonn M M

2011-09-01

The following includes commentaries on clinical features and imaging of Barrett\\'s esophagus (BE); the clinical factors that influence the development of BE; the influence of body fat distribution and central obesity; the role of adipocytokines and proinflammatory markers in carcinogenesis; the role of body mass index (BMI) in healing of Barrett\\'s epithelium; the role of surgery in prevention of carcinogenesis in BE; the importance of double-contrast esophagography and cross-sectional images of the esophagus; and the value of positron emission tomography\\/computed tomography.

Optimization of hybrid imaging systems based on maximization of kurtosis of the restored point spread function

DEFF Research Database (Denmark)

Demenikov, Mads

2011-01-01

to optimization results based on full-reference image measures of restored images. In comparison with full-reference measures, the kurtosis measure is fast to compute and requires no images, noise distributions, or alignment of restored images, but only the signal-to-noise-ratio. © 2011 Optical Society of America.......I propose a novel, but yet simple, no-reference, objective image quality measure based on the kurtosis of the restored point spread function. Using this measure, I optimize several phase masks for extended-depth-of-field in hybrid imaging systems and obtain results that are identical...

Optimization of image processing algorithms on mobile platforms

Science.gov (United States)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Magnetic resonance imaging- physical principles and clinical application

International Nuclear Information System (INIS)

Tavri, Omprakash J.

1996-01-01

The advances in equipment and knowledge related to radiology are occurring at an astonishingly rapid rate. On November 8, 1895, William Conrad Roentgen discovered x-rays. In 1972, Godfrey Hounsfield and George Ambrose introduced computec tomography at a meeting of the British Institute of Radiology. In the same year, Paul Lauterbur published the idea of spatially resolving nuclear magnetic resonance samples, naming it zeugmatography. In 1977, Waldo Hinshaw and co-workers published a magnetic resonance image of a human hand and wrist, and by 1981 several centres were obtaining clinical magnetic resonance (MR) images. In a very short time, magnetic resonance imaging (MRI) has gained acceptance as a clinically useful imaging tool. (author)

Otimização de imagens mamográficas Optimization of mammographic images

Directory of Open Access Journals (Sweden)

Diana Rodrigues de Pina

2006-10-01

Full Text Available OBJETIVO: Este trabalho tem como objetivo a otimização de imagens mamográficas, com consideráveis reduções de doses. MATERIAIS E MÉTODOS: Neste estudo o feixe de raios-X foi calibrado para cada tensão (kVp, de modo a determinar a melhor combinação de kVp e mAs que irá proporcionar uma densidade ótica (DO em torno de 1.0 acima da base mais véu do filme utilizado. RESULTADOS: Serão discutidas questões sobre os métodos empregados para a seleção de parâmetros de exposição do feixe de raios-X, seleção da melhor imagem utilizando o método de avaliação gradativa visual, comparações entre as doses e carga do tubo (kVp × mAs proporcionadas pelas técnicas determinadas neste estudo e pelas utilizadas na rotina clínica do Serviço de Diagnóstico por Imagem do Hospital das Clínicas da Faculdade de Medicina de Botucatu. Neste estudo foram obtidas imagens radiográficas de mama de excelente qualidade, com redução de dose e carga de tubo, respectivamente, de 36,8% e 46,2%, quando comparadas com a técnica utilizada pela rotina clínica da instituição. CONCLUSÃO: Esta pesquisa vem contribuir com a otimização da relação risco-benefício para o paciente e custo-benefício para a instituição.OBJECTIVE: The aim of this study is the optimization of mammographic images with a considerable radiation dose reduction. MATERIALS AND METHODS: In the present study the X-ray beam was calibrated for each tension (kVp, aiming at determining the best combination between kVp and mAs, resulting in optical densities of about 1.0 above the base-plus-fog density. RESULTS: This study will bring into question the methods for X-ray beam calibration, the choice of the best image by means of visual grading analysis, comparisons between doses and tube load (kVp × mAs delivered by the techniques described in this study and by those adopted in the clinical routine at Service of Diagnostic Imaging of Faculdade de Medicina de Botucatu Clinics

A fast inverse treatment planning strategy facilitating optimized catheter selection in image-guided high-dose-rate interstitial gynecologic brachytherapy.

Science.gov (United States)

Guthier, Christian V; Damato, Antonio L; Hesser, Juergen W; Viswanathan, Akila N; Cormack, Robert A

2017-12-01

Interstitial high-dose rate (HDR) brachytherapy is an important therapeutic strategy for the treatment of locally advanced gynecologic (GYN) cancers. The outcome of this therapy is determined by the quality of dose distribution achieved. This paper focuses on a novel yet simple heuristic for catheter selection for GYN HDR brachytherapy and their comparison against state of the art optimization strategies. The proposed technique is intended to act as a decision-supporting tool to select a favorable needle configuration. The presented heuristic for catheter optimization is based on a shrinkage-type algorithm (SACO). It is compared against state of the art planning in a retrospective study of 20 patients who previously received image-guided interstitial HDR brachytherapy using a Syed Neblett template. From those plans, template orientation and position are estimated via a rigid registration of the template with the actual catheter trajectories. All potential straight trajectories intersecting the contoured clinical target volume (CTV) are considered for catheter optimization. Retrospectively generated plans and clinical plans are compared with respect to dosimetric performance and optimization time. All plans were generated with one single run of the optimizer lasting 0.6-97.4 s. Compared to manual optimization, SACO yields a statistically significant (P ≤ 0.05) improved target coverage while at the same time fulfilling all dosimetric constraints for organs at risk (OARs). Comparing inverse planning strategies, dosimetric evaluation for SACO and "hybrid inverse planning and optimization" (HIPO), as gold standard, shows no statistically significant difference (P > 0.05). However, SACO provides the potential to reduce the number of used catheters without compromising plan quality. The proposed heuristic for needle selection provides fast catheter selection with optimization times suited for intraoperative treatment planning. Compared to manual optimization, the

Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

Directory of Open Access Journals (Sweden)

Irene Erlyn Wina Rachmawan

2015-06-01

Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

An Optimized Online Verification Imaging Procedure for External Beam Partial Breast Irradiation

International Nuclear Information System (INIS)

Willis, David J.; Kron, Tomas; Chua, Boon

2011-01-01

The purpose of this study was to evaluate the capabilities of a kilovoltage (kV) on-board imager (OBI)-equipped linear accelerator in the setting of on-line verification imaging for external-beam partial breast irradiation. Available imaging techniques were optimized and assessed for image quality using a modified anthropomorphic phantom. Imaging dose was also assessed. Imaging techniques were assessed for physical clearance between patient and treatment machine using a volunteer. Nonorthogonal kV image pairs were identified as optimal in terms of image quality, clearance, and dose. After institutional review board approval, this approach was used for 17 patients receiving accelerated partial breast irradiation. Imaging was performed before every fraction verification with online correction of setup deviations >5 mm (total image sessions = 170). Treatment staff rated risk of collision and visibility of tumor bed surgical clips where present. Image session duration and detected setup deviations were recorded. For all cases, both image projections (n = 34) had low collision risk. Surgical clips were rated as well as visualized in all cases where they were present (n = 5). The average imaging session time was 6 min, 16 sec, and a reduction in duration was observed as staff became familiar with the technique. Setup deviations of up to 1.3 cm were detected before treatment and subsequently confirmed offline. Nonorthogonal kV image pairs allowed effective and efficient online verification for partial breast irradiation. It has yet to be tested in a multicenter study to determine whether it is dependent on skilled treatment staff.

Optimizing the magnetization-prepared rapid gradient-echo (MP-RAGE sequence.

Directory of Open Access Journals (Sweden)

Jinghua Wang

Full Text Available The three-dimension (3D magnetization-prepared rapid gradient-echo (MP-RAGE sequence is one of the most popular sequences for structural brain imaging in clinical and research settings. The sequence captures high tissue contrast and provides high spatial resolution with whole brain coverage in a short scan time. In this paper, we first computed the optimal k-space sampling by optimizing the contrast of simulated images acquired with the MP-RAGE sequence at 3.0 Tesla using computer simulations. Because the software of our scanner has only limited settings for k-space sampling, we then determined the optimal k-space sampling for settings that can be realized on our scanner. Subsequently we optimized several major imaging parameters to maximize normal brain tissue contrasts under the optimal k-space sampling. The optimal parameters are flip angle of 12°, effective inversion time within 900 to 1100 ms, and delay time of 0 ms. In vivo experiments showed that the quality of images acquired with our optimal protocol was significantly higher than that of images obtained using recommended protocols in prior publications. The optimization of k-spacing sampling and imaging parameters significantly improved the quality and detection sensitivity of brain images acquired with MP-RAGE.

New software developments for quality mesh generation and optimization from biomedical imaging data.

Science.gov (United States)

Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

2014-01-01

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Functional brain imaging - baric and clinical questions

International Nuclear Information System (INIS)

Mager, T.; Moeller, H.J.

1997-01-01

The advancing biological knowledge of disease processes plays a central part in the progress of modern psychiatry. An essential contribution comes from the functional and structural brain imaging techniques (CT, MRI, SPECT, PET). Their application is important for biological oriented research in psychiatry and there is also a growing relevance in clinical aspects. This development is taken into account by recent diagnostic classification systems in psychiatry. The capabilities and limitations of functional brain imaging in the context of research and clinic will be presented and discussed by examples and own investigations. (orig.) [de

Optimal image alignment with random projections of manifolds: algorithm and geometric analysis.

Science.gov (United States)

Kokiopoulou, Effrosyni; Kressner, Daniel; Frossard, Pascal

2011-06-01

This paper addresses the problem of image alignment based on random measurements. Image alignment consists of estimating the relative transformation between a query image and a reference image. We consider the specific problem where the query image is provided in compressed form in terms of linear measurements captured by a vision sensor. We cast the alignment problem as a manifold distance minimization problem in the linear subspace defined by the measurements. The transformation manifold that represents synthesis of shift, rotation, and isotropic scaling of the reference image can be given in closed form when the reference pattern is sparsely represented over a parametric dictionary. We show that the objective function can then be decomposed as the difference of two convex functions (DC) in the particular case where the dictionary is built on Gaussian functions. Thus, the optimization problem becomes a DC program, which in turn can be solved globally by a cutting plane method. The quality of the solution is typically affected by the number of random measurements and the condition number of the manifold that describes the transformations of the reference image. We show that the curvature, which is closely related to the condition number, remains bounded in our image alignment problem, which means that the relative transformation between two images can be determined optimally in a reduced subspace.

Optimal scanning and image processing with the STEM

International Nuclear Information System (INIS)

Crewe, A.V.; Ohtsuki, M.

1981-01-01

We have recently published a theory of an optimal scanning system which is particularly suited for the STEM. One concludes from the theory that the diffraction limit of the electron probe should be a fixed fraction of the full-scale deflection in order to avoid scanning artifacts. More recently, we have confirmed the value of this technique by direct experiments. Our program now is to combine the use of optimal scanning with the use of a programmable digital refresh memory for image analysis. Limited experience to date indicates that false color conversion is probably more useful than histogram equalization in black and white and that this system is particularly valuable for rotational averaging and selected area Fourier transforms. (orig.)

Potential clinical impact of radionuclide imaging technologies: highlights of the ITBS 2003 meeting

Energy Technology Data Exchange (ETDEWEB)

Itti, Roland E-mail: roland.itti@univ-lyon1.fr

2004-07-11

Radiopharmaceuticals are major determinants of progress in Nuclear Medicine. Besides {sup 18}FDG, the most common PET tracer, several other molecules are under evaluation, such as {sup 18}F-fluoride for bone studies, numerous ligands for neurotransmission, {sup 18}F-DOPA for neuro-endocrine tumors or generator produced {sup 68}Ga-peptides for various cancers. Nuclear medicine gradually changes for 'molecular imaging' and medical imaging, which was at the beginning mainly anatomic, has progressed in the direction of functional and metabolic imaging. The present challenge is to achieve some degree of 'in vivo' biochemistry or even histology or genetics. The importance of anatomic/functional image fusion justifies the development of combined PET-CT instrumentation, whose objectives have to be discussed in terms of anatomical landmarks and/or additional clinical information. The question of 'hard' or 'soft' image co-registration remains open, involving not only CT, but also SPECT or MRI. Development of dedicated imaging devices, whether single photon or positron, is of major interest for breast imaging, allowing optimal imaging conditions, with results definitely superior to classical gamma-cameras or PET. The patient population concerned with scintimammography is still controversial, as well as the imaging modalities: FDG or sestaMIBI, planar or tomographic, scintillators or semi-conductors, and the research field remains open. This is also valid for external or per-operative probe systems for tumor or lymph nodes localization.

Optimization of patient protection using rare earth screen in conventional imaging procedure

International Nuclear Information System (INIS)

Inkoom, S.; Schandorf, C.; Fletcher, J.J.

2008-01-01

The purpose of this study was to optimize patient protection using rare earth screen of speed 400 in place of conventional screen-film of speed 200. The entrance surface dose (ESD) for the two screen-film systems was determined for patients undergoing simple radiographic examinations (chest, lumbar spine and pelvis series). The determination of the ESD included backscatter factors. The ESD was the optimizing parameter and its trade off with the image quality assessment, which was surveyed based on the information obtained through standardized questionnaire. The estimated ESDs were compared with reference levels set by the Community of European Commission (CEC) for a standard adult patient. For chest PA, ESD estimates were lower than the CEC reference levels whilst that of lumbar spine AP and LAT and pelvis AP were high. Upon the adoption of rare earth screen of speed 400, a dose reduction of 33% for chest, 17% for lumbar spine and 28% for pelvis examinations was achieved. From the observations made from this study, some corrective actions such as equipment quality control of parameters that affect patient dose and image quality like kVp accuracy and consistency, mAs accuracy and consistency, optimal film processing conditions, regular film reject analysis to detect and minimize the root causes and contributory factors to poor image quality and periodic training of staff on dose reduction techniques must be undertaken. Regular assessment of patient dose and image quality, equipment quality control, adoption of faster rare earth screens and optimum radiographic technique are therefore recommended in order to achieve optimization goals. (author)

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

Science.gov (United States)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Microvascular imaging: techniques and opportunities for clinical physiological measurements

International Nuclear Information System (INIS)

Allen, John; Howell, Kevin

2014-01-01

The microvasculature presents a particular challenge in physiological measurement because the vessel structure is spatially inhomogeneous and perfusion can exhibit high variability over time. This review describes, with a clinical focus, the wide variety of methods now available for imaging of the microvasculature and their key applications. Laser Doppler perfusion imaging and laser speckle contrast imaging are established, commercially-available techniques for determining microvascular perfusion, with proven clinical utility for applications such as burn-depth assessment. Nailfold capillaroscopy is also commercially available, with significant published literature that supports its use for detecting microangiopathy secondary to specific connective tissue diseases in patients with Raynaud's phenomenon. Infrared thermography measures skin temperature and not perfusion directly, and it has only gained acceptance for some surgical and peripheral microvascular applications. Other emerging technologies including imaging photoplethysmography, optical coherence tomography, photoacoustic tomography, hyperspectral imaging, and tissue viability imaging are also described to show their potential as techniques that could become established tools for clinical microvascular assessment. Growing interest in the microcirculation has helped drive the rapid development in perfusion imaging of the microvessels, bringing exciting opportunities in microvascular research. (topical review)

Third version of vendor-specific model-based iterativereconstruction (Veo 3.0): evaluation of CT image quality in the abdomen using new noise reduction presets and varied slice optimization.

Science.gov (United States)

Telesmanich, Morgan E; Jensen, Corey T; Enriquez, Jose L; Wagner-Bartak, Nicolaus A; Liu, Xinming; Le, Ott; Wei, Wei; Chandler, Adam G; Tamm, Eric P

2017-08-01

To qualitatively and quantitatively compare abdominal CT images reconstructed with a newversion of model-based iterative reconstruction (Veo 3.0; GE Healthcare Waukesha, WI) utilizing varied presetsof resolution preference, noise reduction and slice optimization. This retrospective study was approved by our Institutional Review Board and was Health Insurance Portability and Accountability Act compliant. The raw datafrom 30 consecutive patients who had undergone CT abdomen scanning were used to reconstructfour clinical presets of 3.75mm axial images using Veo 3.0: 5% resolution preference (RP05n), 5%noise reduction (NR05) and 40% noise reduction (NR40) with new 3.75mm "sliceoptimization," as well as one set using RP05 with conventional 0.625mm "slice optimization" (RP05c). The images were reviewed by two independent readers in a blinded, randomized manner using a 5-point Likert scale as well as a 5-point comparative scale. Multiple two-dimensional circular regions of interest were defined for noise and contrast-to-noise ratio measurements. Line profiles were drawn across the 7 lp cm -1 bar pattern of the Catphan 600 phantom for evaluation of spatial resolution. The NR05 image set was ranked as the best series in overall image quality (mean difference inrank 0.48, 95% CI [0.081-0.88], p = 0.01) and with specific reference to liver evaluation (meandifference 0.46, 95% CI [0.030-0.89], p = 0.03), when compared with the secondbest series ineach category. RP05n was ranked as the best for bone evaluation. NR40 was ranked assignificantly inferior across all assessed categories. Although the NR05 and RP05c image setshad nearly the same contrast-to-noise ratio and spatial resolution, NR05 was generally preferred. Image noise and spatial resolution increased along a spectrum with RP05n the highest and NR40the lowest. Compared to RP05n, the average noise was 21.01% lower for NR05, 26.88%lower for RP05c and 50.86% lower for NR40. Veo 3.0 clinical presets allow for

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

International Nuclear Information System (INIS)

De Angelis, L; Landry, G; Dedes, G; Parodi, K; Hansen, D; Rit, S; Belka, C

2016-01-01

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBs was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

Energy Technology Data Exchange (ETDEWEB)

De Angelis, L; Landry, G; Dedes, G; Parodi, K [Ludwig-Maximilians-Universitaet Muenchen (LMU Munich), Garching b. Muenchen (Germany); Hansen, D [Aarhus University Hospital, Aarhus, Jutland (Denmark); Rit, S [University Lyon, Lyon, Auvergne-Rhone-Alpes (France); Belka, C [LMU Munich, Munich (Germany)

2016-06-15

Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBs was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)

Numerical simulation and optimal design of Segmented Planar Imaging Detector for Electro-Optical Reconnaissance

Science.gov (United States)

Chu, Qiuhui; Shen, Yijie; Yuan, Meng; Gong, Mali

2017-12-01

Segmented Planar Imaging Detector for Electro-Optical Reconnaissance (SPIDER) is a cutting-edge electro-optical imaging technology to realize miniaturization and complanation of imaging systems. In this paper, the principle of SPIDER has been numerically demonstrated based on the partially coherent light theory, and a novel concept of adjustable baseline pairing SPIDER system has further been proposed. Based on the results of simulation, it is verified that the imaging quality could be effectively improved by adjusting the Nyquist sampling density, optimizing the baseline pairing method and increasing the spectral channel of demultiplexer. Therefore, an adjustable baseline pairing algorithm is established for further enhancing the image quality, and the optimal design procedure in SPIDER for arbitrary targets is also summarized. The SPIDER system with adjustable baseline pairing method can broaden its application and reduce cost under the same imaging quality.

Algorithm-enabled exploration of image-quality potential of cone-beam CT in image-guided radiation therapy

International Nuclear Information System (INIS)

Han, Xiao; Sidky, Emil Y; Pan, Xiaochuan; Pearson, Erik; Pelizzari, Charles; Al-Hallaq, Hania; Bian, Junguo

2015-01-01

Kilo-voltage (KV) cone-beam computed tomography (CBCT) unit mounted onto a linear accelerator treatment system, often referred to as on-board imager (OBI), plays an increasingly important role in image-guided radiation therapy. While the FDK algorithm is currently used for reconstructing images from clinical OBI data, optimization-based reconstruction has also been investigated for OBI CBCT. An optimization-based reconstruction involves numerous parameters, which can significantly impact reconstruction properties (or utility). The success of an optimization-based reconstruction for a particular class of practical applications thus relies strongly on appropriate selection of parameter values. In the work, we focus on tailoring the constrained-TV-minimization-based reconstruction, an optimization-based reconstruction previously shown of some potential for CBCT imaging conditions of practical interest, to OBI imaging through appropriate selection of parameter values. In particular, for given real data of phantoms and patient collected with OBI CBCT, we first devise utility metrics specific to OBI-quality-assurance tasks and then apply them to guiding the selection of parameter values in constrained-TV-minimization-based reconstruction. The study results show that the reconstructions are with improvement, relative to clinical FDK reconstruction, in both visualization and quantitative assessments in terms of the devised utility metrics. (paper)

A novel 1050nm handheld OCT imaging system for pediatric retinoblastoma patients: technology development and clinical study (Conference Presentation)

Science.gov (United States)

Nadiarnykh, Oleg; Moll, Annette C.; de Boer, Johannes F.

2016-03-01

We demonstrate a novel optical coherence tomography system specifically developed and validated for clinical imaging of retinoblastoma tumors in pediatric patients. The existing treatment options for this malignant tumor of the retina aim at reduction of tumor (re)growth risks, and vision preservation. The choice of optimal treatment strongly depends on skilled and detailed clinical assessment. Due to the limitations of the existing real-time diagnostic tools the patients at risk are periodically monitored with retinal imaging to confirm the absence of new tumor seedings. Three-dimensional visualization of tissue layer and microvasculature at improved axial and lateral resolution of interference-based OCT imaging provides sensitivity for detection of vital tumor tissue concurrent with local treatment. Our METC-approved system accommodates for the range of optical parameters of infants' eyes, and uses the 1050nm wavelength to access the deeper choroid layers of retina. The prototype is designed for patients in supine position under general anesthesia, where ergonomic handheld module is connected to fiber-based optical setup via umbilical cord. The system conforms to clinical safety requirements, including fully isolated low-voltage electric circuit. Focusing is performed with a mechanically tunable lens, where resolution is 6 µm axially, and varies with focusing at 10-18µm laterally. We will present optical design, performance limitations, and results of the ongoing clinical study, including the increased OCT diagnostic sensitivity in three dimensions in comparison with the established clinical imaging modalities. We will discuss images of early, active, and treated tumors, as well as follow-up on patients after local and systemic treatments.

Optimizing the design of vertical seismic profiling (VSP) for imaging fracture zones over hardrock basement geothermal environments

Science.gov (United States)

Reiser, Fabienne; Schmelzbach, Cedric; Maurer, Hansruedi; Greenhalgh, Stewart; Hellwig, Olaf

2017-04-01

A primary focus of geothermal seismic imaging is to map dipping faults and fracture zones that control rock permeability and fluid flow. Vertical seismic profiling (VSP) is therefore a most valuable means to image the immediate surroundings of an existing borehole to guide, for example, the placing of new boreholes to optimize production from known faults and fractures. We simulated 2D and 3D acoustic synthetic seismic data and processed it through to pre-stack depth migration to optimize VSP survey layouts for mapping moderately to steeply dipping fracture zones within possible basement geothermal reservoirs. Our VSP survey optimization procedure for sequentially selecting source locations to define the area where source points are best located for optimal imaging makes use of a cross-correlation statistic, by which a subset of migrated shot gathers is compared with a target or reference image from a comprehensive set of source gathers. In geothermal exploration at established sites, it is reasonable to assume that sufficient à priori information is available to construct such a target image. We generally obtained good results with a relatively small number of optimally chosen source positions distributed over an ideal source location area for different fracture zone scenarios (different dips, azimuths, and distances from the surveying borehole). Adding further sources outside the optimal source area did not necessarily improve the results, but rather resulted in image distortions. It was found that fracture zones located at borehole-receiver depths and laterally offset from the borehole by 300 m can be imaged reliably for a range of the different dips, but more source positions and large offsets between sources and the borehole are required for imaging steeply dipping interfaces. When such features cross-cut the borehole, they are particularly difficult to image. For fracture zones with different azimuths, 3D effects are observed. Far offset source positions

Basics concepts and clinical applications of oxygen-enhanced MR imaging

International Nuclear Information System (INIS)

Ohno, Yoshiharu; Hatabu, Hiroto

2007-01-01

Oxygen-enhanced MR imaging is a new technique, and its physiological significance has not yet been fully elucidated. This review article covers (1) the theory of oxygen enhancement and its relationship with respiratory physiology; (2) design for oxygen-enhanced MR imaging sequencing; (3) a basic study of oxygen-enhanced MR imaging in animal models and humans; (4) a clinical study of oxygen-enhanced MR imaging; and (5) a comparison of advantages and disadvantages of this technique with those of hyperpolarized noble gas MR ventilation imaging. Oxygen-enhanced MR imaging provides not only the ventilation-related, but also respiration-related information. Oxygen-enhanced MR imaging has the potential to replace nuclear medicine studies for the identification of regional pulmonary function, and many investigators are now attempting to adapt this technique for routine clinical studies. We believe that further basic studies as well as clinical applications of this new technique will define the real significance of oxygen-enhanced MR imaging for the future of pulmonary functional imaging and its usefulness for diagnostic radiology and pulmonary medicine

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

Science.gov (United States)

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Clinical software for MR imaging system, 4

International Nuclear Information System (INIS)

Shimizu, Koji; Kasai, Akira; Okamura, Shoichi

1992-01-01

Magnetic resonance imaging continues to elicit new application software through the recent technological advances of MR equipment. This paper describes several applications of our newly developed clinical software. The fast SE sequence (RISE) has proved to reduce routine examination time and to improve image quality, and ultra-fast FE sequence (SMASH) was found to extend the diagnostic capabilities in the field of cardiac study. Diffusion/perfusion imaging achieved in our MR system showed significant promise for providing novel information regarding tissue characterization. Furthermore, Image quality and practicalities of MR angiography have been improved by advanced imaging sequences and sophisticated post-processing software. (author)

Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research.

Science.gov (United States)

Mancini, Marcello; Summers, Paul; Faita, Francesco; Brunetto, Maurizia R; Callea, Francesco; De Nicola, Andrea; Di Lascio, Nicole; Farinati, Fabio; Gastaldelli, Amalia; Gridelli, Bruno; Mirabelli, Peppino; Neri, Emanuele; Salvadori, Piero A; Rebelos, Eleni; Tiribelli, Claudio; Valenti, Luca; Salvatore, Marco; Bonino, Ferruccio

2018-02-27

The rapidly growing field of functional, molecular and structural bio-imaging is providing an extraordinary new opportunity to overcome the limits of invasive liver biopsy and introduce a "digital biopsy" for in vivo study of liver pathophysiology. To foster the application of bio-imaging in clinical and translational research, there is a need to standardize the methods of both acquisition and the storage of the bio-images of the liver. It can be hoped that the combination of digital, liquid and histologic liver biopsies will provide an innovative synergistic tri-dimensional approach to identifying new aetiologies, diagnostic and prognostic biomarkers and therapeutic targets for the optimization of personalized therapy of liver diseases and liver cancer. A group of experts of different disciplines (Special Interest Group for Personalized Hepatology of the Italian Association for the Study of the Liver, Institute for Biostructures and Bio-imaging of the National Research Council and Bio-banking and Biomolecular Resources Research Infrastructure) discussed criteria, methods and guidelines for facilitating the requisite application of data collection. This manuscript provides a multi-Author review of the issue with special focus on fatty liver.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

Science.gov (United States)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

OpenAIRE

Kotasidis Fotis A.; Kotasidis Fotis A.; Angelis Georgios I.; Anton-Rodriguez Jose; Matthews Julian C.; Reader Andrew J.; Reader Andrew J.; Zaidi Habib; Zaidi Habib; Zaidi Habib

2014-01-01

Purpose: Measuring and incorporating a scanner specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However due to the short half life of clinically used isotopes other long lived isotopes not used in clinical practice are used to perform the PSF measurements. As such non optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction usuall...

Studies of dose optimization and image quality in technological transition in mammography; Estudos de otimizacao de dose e qualidade de imagem em processos de transicao tecnologica em mamografia

Energy Technology Data Exchange (ETDEWEB)

Furquim, Tania C.; Nersissian, Denise Y., E-mail: tfurquim@iee.usp.b [Universidade de Sao Paulo (IEE/USP), SP (Brazil). Inst. de Eletrotecnica e Energia

2011-07-01

The introduction of new technologies in mammography may improve image quality; however, it may unnecessarily increase doses if optimization processes are not studied. In this work, radiation doses of the moment of transition of conventional to digital mammography have been analyzed. The presented data have been acquired from 2005 to 2009, in hospitals and clinics of Sao Paulo city, to 4 conventional and 5 digital equipment. The results show that even after optimization processes, new technologies still impart higher doses. Thus, individualized studies are needed when technological transitions occur, in order to maintain image quality without significant dose increase. (author)

An Lq–Lp optimization framework for image reconstruction of electrical resistance tomography

International Nuclear Information System (INIS)

Zhao, Jia; Xu, Yanbin; Dong, Feng

2014-01-01

Image reconstruction in electrical resistance tomography (ERT) is an ill-posed and nonlinear problem, which is easily affected by measurement noise. The regularization method with L 2 constraint term or L 1 constraint term is often used to solve the inverse problem of ERT. It shows that the reconstruction method with L 2 regularization puts smoothness to obtain stability in the image reconstruction process, which is blurry at the interface of different conductivities. The regularization method with L 1 norm is powerful at dealing with the over-smoothing effects, which is beneficial in obtaining a sharp transaction in conductivity distribution. To find the reason for these effects, an L q –L p optimization framework (1 ⩽ q ⩽ 2, 1 ⩽ p ⩽ 2) for the image reconstruction of ERT is presented in this paper. The L q –L p optimization framework is solved based on an approximation handling with Gauss–Newton iteration algorithm. The optimization framework is tested for image reconstruction of ERT with different models and the effects of the L p regularization term on the quality of the reconstructed images are discussed with both simulation and experiment. By comparing the reconstructed results with different p in the regularization term, it is found that a large penalty is implemented on small data in the solution when p is small and a lesser penalty is implemented on small data in the solution when p is larger. It also makes the reconstructed images smoother and more easily affected by noise when p is larger. (paper)

An Optimized Method for Terrain Reconstruction Based on Descent Images

Directory of Open Access Journals (Sweden)

Xu Xinchao

2016-02-01

Full Text Available An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang’e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang’e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions.

Optimizing 4DCBCT projection allocation to respiratory bins

International Nuclear Information System (INIS)

O’Brien, Ricky T; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J

2014-01-01

4D cone beam computed tomography (4DCBCT) is an emerging image guidance strategy used in radiotherapy where projections acquired during a scan are sorted into respiratory bins based on the respiratory phase or displacement. 4DCBCT reduces the motion blur caused by respiratory motion but increases streaking artefacts due to projection under-sampling as a result of the irregular nature of patient breathing and the binning algorithms used. For displacement binning the streak artefacts are so severe that displacement binning is rarely used clinically. The purpose of this study is to investigate if sharing projections between respiratory bins and adjusting the location of respiratory bins in an optimal manner can reduce or eliminate streak artefacts in 4DCBCT images. We introduce a mathematical optimization framework and a heuristic solution method, which we will call the optimized projection allocation algorithm, to determine where to position the respiratory bins and which projections to source from neighbouring respiratory bins. Five 4DCBCT datasets from three patients were used to reconstruct 4DCBCT images. Projections were sorted into respiratory bins using equispaced, equal density and optimized projection allocation. The standard deviation of the angular separation between projections was used to assess streaking and the consistency of the segmented volume of a fiducial gold marker was used to assess motion blur. The standard deviation of the angular separation between projections using displacement binning and optimized projection allocation was 30%–50% smaller than conventional phase based binning and 59%–76% smaller than conventional displacement binning indicating more uniformly spaced projections and fewer streaking artefacts. The standard deviation in the marker volume was 20%–90% smaller when using optimized projection allocation than using conventional phase based binning suggesting more uniform marker segmentation and less motion blur. Images

Imaging and Data Acquisition in Clinical Trials for Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

FitzGerald, Thomas J., E-mail: Thomas.Fitzgerald@umassmed.edu [Imaging and Radiation Oncology Core Rhode Island, University of Massachusetts Memorial Medical Center, University of Massachusetts Medical School, Worcester, Massachusetts (United States); Bishop-Jodoin, Maryann [Imaging and Radiation Oncology Core Rhode Island, University of Massachusetts Medical School, Worcester, Massachusetts (United States); Followill, David S. [Imaging and Radiation Oncology Core Houston, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Galvin, James [Imaging and Radiation Oncology Core Philadelphia, Thomas Jefferson University, Philadelphia, Pennsylvania (United States); Knopp, Michael V. [Imaging and Radiation Oncology Core Ohio, Wexner Medical Center, Ohio State University, Columbus, Ohio (United States); Michalski, Jeff M. [Imaging and Radiation Oncology Core St. Louis, Washington University School of Medicine, St. Louis, Missouri (United States); Rosen, Mark A. [Imaging and Radiation Oncology Core Philadelphia, University of Pennsylvania Health System, Philadelphia, Pennsylvania (United States); Bradley, Jeffrey D. [Washington University School of Medicine–Radiation Oncology, St. Louis, Missouri (United States); Shankar, Lalitha K. [National Cancer Institute, Clinical Radiation Oncology Branch, Rockville, Maryland (United States); Laurie, Fran [Imaging and Radiation Oncology Core Rhode Island, University of Massachusetts Medical School, Worcester, Massachusetts (United States); Cicchetti, M. Giulia; Moni, Janaki [Imaging and Radiation Oncology Core Rhode Island, University of Massachusetts Memorial Medical Center, University of Massachusetts Medical School, Worcester, Massachusetts (United States); Coleman, C. Norman; Deye, James A.; Capala, Jacek; Vikram, Bhadrasain [National Cancer Institute, Clinical Radiation Oncology Branch, Rockville, Maryland (United States)

2016-02-01

Cancer treatment evolves through oncology clinical trials. Cancer trials are multimodal and complex. Assuring high-quality data are available to answer not only study objectives but also questions not anticipated at study initiation is the role of quality assurance. The National Cancer Institute reorganized its cancer clinical trials program in 2014. The National Clinical Trials Network (NCTN) was formed and within it was established a Diagnostic Imaging and Radiation Therapy Quality Assurance Organization. This organization is Imaging and Radiation Oncology Core, the Imaging and Radiation Oncology Core Group, consisting of 6 quality assurance centers that provide imaging and radiation therapy quality assurance for the NCTN. Sophisticated imaging is used for cancer diagnosis, treatment, and management as well as for image-driven technologies to plan and execute radiation treatment. Integration of imaging and radiation oncology data acquisition, review, management, and archive strategies are essential for trial compliance and future research. Lessons learned from previous trials are and provide evidence to support diagnostic imaging and radiation therapy data acquisition in NCTN trials.

Imaging and Data Acquisition in Clinical Trials for Radiation Therapy

International Nuclear Information System (INIS)

FitzGerald, Thomas J.; Bishop-Jodoin, Maryann; Followill, David S.; Galvin, James; Knopp, Michael V.; Michalski, Jeff M.; Rosen, Mark A.; Bradley, Jeffrey D.; Shankar, Lalitha K.; Laurie, Fran; Cicchetti, M. Giulia; Moni, Janaki; Coleman, C. Norman; Deye, James A.; Capala, Jacek; Vikram, Bhadrasain

2016-01-01

Cancer treatment evolves through oncology clinical trials. Cancer trials are multimodal and complex. Assuring high-quality data are available to answer not only study objectives but also questions not anticipated at study initiation is the role of quality assurance. The National Cancer Institute reorganized its cancer clinical trials program in 2014. The National Clinical Trials Network (NCTN) was formed and within it was established a Diagnostic Imaging and Radiation Therapy Quality Assurance Organization. This organization is Imaging and Radiation Oncology Core, the Imaging and Radiation Oncology Core Group, consisting of 6 quality assurance centers that provide imaging and radiation therapy quality assurance for the NCTN. Sophisticated imaging is used for cancer diagnosis, treatment, and management as well as for image-driven technologies to plan and execute radiation treatment. Integration of imaging and radiation oncology data acquisition, review, management, and archive strategies are essential for trial compliance and future research. Lessons learned from previous trials are and provide evidence to support diagnostic imaging and radiation therapy data acquisition in NCTN trials.

Echo planar perfusion imaging with high spatial and temporal resolution: methodology and clinical aspects

International Nuclear Information System (INIS)

Bitzer, M.; Klose, U.; Naegele, T.; Friese, S.; Kuntz, R.; Voigt, K.; Fetter, M.; Opitz, H.

1999-01-01

The purpose of the present study was to analyse specific advantages of calculated parameter images and their limitations using an optimized echo-planar imaging (EPI) technique with high spatial and temporal resolution. Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) was performed in 12 patients with cerebrovascular disease and in 13 patients with brain tumours. For MR imaging of cerebral perfusion an EPI sequence was developed which provides a temporal resolution of 0.68 s for three slices with a 128 x 128 image matrix. To evaluate DSC-MRI, the following parameter images were calculated pixelwise: (1) Maximum signal reduction (MSR); (2) maximum signal difference (ΔSR); (3) time-to-peak (T p ); and (4) integral of signal-intensity-time curve until T p (S Int ). The MSR maps were superior in the detection of acute infarctions and ΔSR maps in the delineation of vasogenic brain oedema. The time-to-peak (T p ) maps seemed to be highly sensitive in the detection of poststenotic malperfused brain areas (sensitivity 90 %). Hyperperfused areas of brain tumours were detectable down to a diameter of 1 cm with high sensitivity (> 90 %). Distinct clinical and neuroradiological conditions revealed different suitabilities for the parameter images. The time-to-peak (T p ) maps may be an important advantage in the detection of poststenotic ''areas at risk'', due to an improved temporal resolution using an EPI technique. With regard to spatial resolution, a matrix size of 128 x 128 is sufficient for all clinical conditions. According to our results, a further increase in matrix size would not improve the spatial resolution in DSC-MRI, since the degree of the vascularization of lesions and the susceptibility effect itself seem to be the limiting factors. (orig.)

Selection of optimal multispectral imaging system parameters for small joint arthritis detection

Science.gov (United States)

Dolenec, Rok; Laistler, Elmar; Stergar, Jost; Milanic, Matija

2018-02-01

Early detection and treatment of arthritis is essential for a successful outcome of the treatment, but it has proven to be very challenging with existing diagnostic methods. Novel methods based on the optical imaging of the affected joints are becoming an attractive alternative. A non-contact multispectral imaging (MSI) system for imaging of small joints of human hands and feet is being developed. In this work, a numerical simulation of the MSI system is presented. The purpose of the simulation is to determine the optimal design parameters. Inflamed and unaffected human joint models were constructed with a realistic geometry and tissue distributions, based on a MRI scan of a human finger with a spatial resolution of 0.2 mm. The light transport simulation is based on a weighted-photon 3D Monte Carlo method utilizing CUDA GPU acceleration. An uniform illumination of the finger within the 400-1100 nm spectral range was simulated and the photons exiting the joint were recorded using different acceptance angles. From the obtained reflectance and transmittance images the spectral and spatial features most indicative of inflammation were identified. Optimal acceptance angle and spectral bands were determined. This study demonstrates that proper selection of MSI system parameters critically affects ability of a MSI system to discriminate the unaffected and inflamed joints. The presented system design optimization approach could be applied to other pathologies.

CT Image Contrast of High-Z Elements: Phantom Imaging Studies and Clinical Implications.

Science.gov (United States)

FitzGerald, Paul F; Colborn, Robert E; Edic, Peter M; Lambert, Jack W; Torres, Andrew S; Bonitatibus, Peter J; Yeh, Benjamin M

2016-03-01

To quantify the computed tomographic (CT) image contrast produced by potentially useful contrast material elements in clinically relevant imaging conditions. Equal mass concentrations (grams of active element per milliliter of solution) of seven radiodense elements, including iodine, barium, gadolinium, tantalum, ytterbium, gold, and bismuth, were formulated as compounds in aqueous solutions. The compounds were chosen such that the active element dominated the x-ray attenuation of the solution. The solutions were imaged within a modified 32-cm CT dose index phantom at 80, 100, 120, and 140 kVp at CT. To simulate larger body sizes, 0.2-, 0.5-, and 1.0-mm-thick copper filters were applied. CT image contrast was measured and corrected for measured concentrations and presence of chlorine in some compounds. Each element tested provided higher image contrast than iodine at some tube potential levels. Over the range of tube potentials that are clinically practical for average-sized and larger adults-that is, 100 kVp and higher-barium, gadolinium, ytterbium, and tantalum provided consistently increased image contrast compared with iodine, respectively demonstrating 39%, 56%, 34%, and 24% increases at 100 kVp; 39%, 66%, 53%, and 46% increases at 120 kVp; and 40%, 72%, 65%, and 60% increases at 140 kVp, with no added x-ray filter. The consistently high image contrast produced with 100-140 kVp by tantalum compared with bismuth and iodine at equal mass concentration suggests that tantalum could potentially be favorable for use as a clinical CT contrast agent.

Seismic image watermarking using optimized wavelets

International Nuclear Information System (INIS)

Mufti, M.

2010-01-01

Geotechnical processes and technologies are becoming more and more sophisticated by the use of computer and information technology. This has made the availability, authenticity and security of geo technical data even more important. One of the most common methods of storing and sharing seismic data images is through standardized SEG- Y file format.. Geo technical industry is now primarily data centric. The analytic and detection capability of seismic processing tool is heavily dependent on the correctness of the contents of the SEG-Y data file. This paper describes a method through an optimized wavelet transform technique which prevents unauthorized alteration and/or use of seismic data. (author)

Methylphenidate dose optimization for ADHD treatment: review of safety, efficacy, and clinical necessity

Directory of Open Access Journals (Sweden)

Huss M

2017-07-01

Full Text Available Michael Huss,1 Praveen Duhan,2 Preetam Gandhi,3 Chien-Wei Chen,4 Carsten Spannhuth,3 Vinod Kumar5 1Child and Adolescent Psychiatry, University Medicine, Mainz, Germany; 2Global Medical Affairs, Novartis Healthcare Pvt. Ltd., Hyderabad, India; 3Development Franchise, Established Medicine Neuroscience, Novartis Pharma AG, Basel, Switzerland; 4Biostatistics Cardio-Metabolic & Established Medicine, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 5Established Medicines, Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA Abstract: Attention-deficit/hyperactivity disorder (ADHD is a chronic psychiatric disorder characterized by hyperactivity and/or inattention and is often associated with a substantial impact on psychosocial functioning. Methylphenidate (MPH, a central nervous system stimulant, is commonly used for pharmacological treatment of adults and children with ADHD. Current practice guidelines recommend optimizing MPH dosage to individual patient needs; however, the clinical benefits of individual dose optimization compared with fixed-dose regimens remain unclear. Here we review the available literature on MPH dose optimization from clinical trials and real-world experience on ADHD management. In addition, we report safety and efficacy data from the largest MPH modified-release long-acting Phase III clinical trial conducted to examine benefits of dose optimization in adults with ADHD. Overall, MPH is an effective ADHD treatment with a good safety profile; data suggest that dose optimization may enhance the safety and efficacy of treatment. Further research is required to establish the extent to which short-term clinical benefits of MPH dose optimization translate into improved long-term outcomes for patients with ADHD. Keywords: methylphenidate, dose optimization, attention-deficit/hyperactivity disorder, ADHD

Objective Lens Optimized for Wavefront Delivery, Pupil Imaging, and Pupil Ghosting

Science.gov (United States)

Olzcak, Gene

2009-01-01

An interferometer objective lens (or diverger) may be used to transform a collimated beam into a diverging or converging beam. This innovation provides an objective lens that has diffraction-limited optical performance that is optimized at two sets of conjugates: imaging to the objective focus and imaging to the pupil. The lens thus provides for simultaneous delivery of a high-quality beam and excellent pupil resolution properties.

A Novel Optimization-Based Approach for Content-Based Image Retrieval

Directory of Open Access Journals (Sweden)

Manyu Xiao

2013-01-01

Full Text Available Content-based image retrieval is nowadays one of the possible and promising solutions to manage image databases effectively. However, with the large number of images, there still exists a great discrepancy between the users’ expectations (accuracy and efficiency and the real performance in image retrieval. In this work, new optimization strategies are proposed on vocabulary tree building, retrieval, and matching methods. More precisely, a new clustering strategy combining classification and conventional K-Means method is firstly redefined. Then a new matching technique is built to eliminate the error caused by large-scaled scale-invariant feature transform (SIFT. Additionally, a new unit mechanism is proposed to reduce the cost of indexing time. Finally, the numerical results show that excellent performances are obtained in both accuracy and efficiency based on the proposed improvements for image retrieval.

An Image Enhancement Method Using the Quantum-Behaved Particle Swarm Optimization with an Adaptive Strategy

Directory of Open Access Journals (Sweden)

Xiaoping Su

2013-01-01

Full Text Available Image enhancement techniques are very important to image processing, which are used to improve image quality or extract the fine details in degraded images. In this paper, two novel objective functions based on the normalized incomplete Beta transform function are proposed to evaluate the effectiveness of grayscale image enhancement and color image enhancement, respectively. Using these objective functions, the parameters of transform functions are estimated by the quantum-behaved particle swarm optimization (QPSO. We also propose an improved QPSO with an adaptive parameter control strategy. The QPSO and the AQPSO algorithms, along with genetic algorithm (GA and particle swarm optimization (PSO, are tested on several benchmark grayscale and color images. The results show that the QPSO and AQPSO perform better than GA and PSO for the enhancement of these images, and the AQPSO has some advantages over QPSO due to its adaptive parameter control strategy.

Intracranial Infections: Clinical and Imaging Characteristics

Energy Technology Data Exchange (ETDEWEB)

Foerster, B.R.; Thurnher, M.M.; Malani, P.N.; Petrou, M.; Carets-Zumelzu, F.; Sundgren, P.C. [Dept. of Radiology, and Divisions of Infectious Diseases and G eriatric Medicine, Dept. of Internal Medicine, Univ. of Michigan Medical Center, Ann Arbor, MI (United States)

2007-10-15

The radiologist plays a crucial role in identifying and narrowing the differential diagnosis of intracranial infections. A thorough understanding of the intracranial compartment anatomy and characteristic imaging findings of specific pathogens, as well incorporation of the clinical information, is essential to establish correct diagnosis. Specific types of infections have certain propensities for different anatomical regions within the brain. In addition, the imaging findings must be placed in the context of the clinical setting, particularly in immunocompromised and human immunodeficiency virus (HIV)-positive patients. This paper describes and depicts infections within the different compartments of the brain. Pathology-proven infectious cases are presented in both immunocompetent and immunocompromised patients, with a discussion of the characteristic findings of each pathogen. Magnetic resonance spectroscopy (MRS) characteristics for several infections are also discussed.

Fuzzy Logic Based Edge Detection in Smooth and Noisy Clinical Images.

Directory of Open Access Journals (Sweden)

Izhar Haq

Full Text Available Edge detection has beneficial applications in the fields such as machine vision, pattern recognition and biomedical imaging etc. Edge detection highlights high frequency components in the image. Edge detection is a challenging task. It becomes more arduous when it comes to noisy images. This study focuses on fuzzy logic based edge detection in smooth and noisy clinical images. The proposed method (in noisy images employs a 3 × 3 mask guided by fuzzy rule set. Moreover, in case of smooth clinical images, an extra mask of contrast adjustment is integrated with edge detection mask to intensify the smooth images. The developed method was tested on noise-free, smooth and noisy images. The results were compared with other established edge detection techniques like Sobel, Prewitt, Laplacian of Gaussian (LOG, Roberts and Canny. When the developed edge detection technique was applied to a smooth clinical image of size 270 × 290 pixels having 24 dB 'salt and pepper' noise, it detected very few (22 false edge pixels, compared to Sobel (1931, Prewitt (2741, LOG (3102, Roberts (1451 and Canny (1045 false edge pixels. Therefore it is evident that the developed method offers improved solution to the edge detection problem in smooth and noisy clinical images.

Homogeneous Canine Chest Phantom Construction: A Tool for Image Quality Optimization.

Directory of Open Access Journals (Sweden)

Ana Luiza Menegatti Pavan

Full Text Available Digital radiographic imaging is increasing in veterinary practice. The use of radiation demands responsibility to maintain high image quality. Low doses are necessary because workers are requested to restrain the animal. Optimizing digital systems is necessary to avoid unnecessary exposure, causing the phenomenon known as dose creep. Homogeneous phantoms are widely used to optimize image quality and dose. We developed an automatic computational methodology to classify and quantify tissues (i.e., lung tissue, adipose tissue, muscle tissue, and bone in canine chest computed tomography exams. The thickness of each tissue was converted to simulator materials (i.e., Lucite, aluminum, and air. Dogs were separated into groups of 20 animals each according to weight. Mean weights were 6.5 ± 2.0 kg, 15.0 ± 5.0 kg, 32.0 ± 5.5 kg, and 50.0 ± 12.0 kg, for the small, medium, large, and giant groups, respectively. The one-way analysis of variance revealed significant differences in all simulator material thicknesses (p < 0.05 quantified between groups. As a result, four phantoms were constructed for dorsoventral and lateral views. In conclusion, the present methodology allows the development of phantoms of the canine chest and possibly other body regions and/or animals. The proposed phantom is a practical tool that may be employed in future work to optimize veterinary X-ray procedures.

Optimized control of X-ray exposure and image noise using a particular multislice CT scanner

International Nuclear Information System (INIS)

Yamamoto, Shuji; Suzuki, Masahiro; Kakinuma, Ryutaro; Moriyama, Noriyuki; Koyama, Yoshihiro; Nagasawa, Hirofumi

2008-01-01

Patient dose reduction in computed tomography (CT) always results in a trade off between radiation exposure and image quality. There are few reports that estimate the relationship between image quality and X-ray exposure in CT examinations as one optimal index. The purpose of this study was to determine the optimal parameter settings enabling a low radiation exposure without compromising image quality using a particular 4-row multislice CT (MSCT) scanner (Aquilion VZ 4-slice CT scanner, Toshiba Medical Systems Corporation, Otawara, Tochigi, Japan). Normalized dose divided by image noise for helical pitches (nDNR: normalized dose to noise ratio) were calculated in consideration of beam collimation and tube current-time product. Optimal tube current-time product was calculated using the nDNR for the helical pitches based on user-defined standards of quality of the CT image. As a result, the nDNR proved to be well-supported to decrease the patient exposure in various exposure conditions of MSCT scans; however, the dose and image noise did not show a linear relation to the helical pitch. In conclusion, nDNR can be applied to patient dose reduction while keeping an acceptable image quality using a particular 4-row MSCT scanner. (author)

Clinical advantages of three dimensional cine cardiac images

International Nuclear Information System (INIS)

Kinosada, Yasutomi; Okuda, Yasuyuki; Nakagawa, Tsuyoshi; Itou, Takafumi; Hattori, Takao.

1996-01-01

We evaluated clinical advantages and the quantitativeness of computerized three-dimensional (3D) cinematic images of a human heart, which were produced with a set of magnetic resonance (MR) images by using the computer graphic technique. Many contiguous, multi-location and multi-phase short axis images were obtained with the ECG gated conventional and fast cardiac imaging sequences in normal volunteers and selected patients with myocardial infarction, hypertrophic cardiomyopathy, dilated cardiomyopathy and left ventricular dysfunction. Judging by visual impressions of the computerized 3D cinematic cardiac images, we could easily understand and evaluate the myocardial motions or the anatomic and volumetric changes of a heart according to the cardiac phases. These images were especially useful to compare the wall motion, the left ventricular ejection-fraction (LVEF), or other cardiac functions and conditions between before and after therapeutic procedures such as percutaneous transluminal coronary angioplasty for patients with myocardial infarction. A good correlation between the LVEF calculated from a set of computerized 3D cinematic images and the ultra sound examinations were found. The results of our study showed that computerized 3D cinematic cardiac images were clinically useful to understand the myocardial motions qualitatively and to evaluate cardiac functions such as the LVEF quantitatively. (author)

WE-FG-206-08: Pulmonary Functional Imaging Biomarkers of NSCLC to Guide and Optimize Functional Lung Avoidance Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Sheikh, Khadija; Capaldi, Dante PI; Parraga, Grace [Robarts Research Institute (Canada); Hoover, Douglas A; Palma, David A [Department of Medical Biophysics, Department of Oncology, The University of Western Ontario, London (Canada); Yaremko, Brian P [Department of Oncology, The University of Western Ontario, London (Canada)

2016-06-15

Purpose: Functional lung avoidance radiotherapy promises optimized therapy planning by minimizing dose to well-functioning lung and maximizing dose to the rest of the lung. Patients with NSCLC commonly present with co-morbid COPD and heterogeneously distributed ventilation abnormalities stemming from emphysema, airways disease, and tumour burden. We hypothesized that pulmonary functional imaging methods may be used to optimize radiotherapy plans to avoid regions of well-functioning lung and significantly improve outcomes like quality-of-life and survival. To ascertain the utility of functional lung avoidance therapy in clinical practice, we measured COPD phenotypes in NSCLC patients enrolled in a randomized-controlled-clinical-trial prior to curative intent therapy. Methods: Thirty stage IIIA/IIIB NSCLC patients provided written informed consent to a randomized-controlled-clinical-trial ( http://clinicaltrials.gov/ct2/show/NCT02002052 ) comparing outcomes in patients randomized to standard or image-guided radiotherapy. Hyperpolarized noble gas MRI ventilation-defect-percent (VDP) (Kirby et al, Acad Radiol, 2012) as well as CT-emphysema measurements were determined. Patients were stratified based on quantitative imaging evidence of ventilation-defects and emphysema into two subgroups: 1) tumour-specific ventilation defects only (TSD), and, 2) tumour-specific and other ventilation defects with and without emphysema (TSD{sub VE}). Receiver-operating-characteristic (ROC) curves were used to characterize the performance of clinical measures as predictors of the presence of non-tumour specific ventilation defects. Results: Twenty-one out of thirty subjects (70%) had non-tumour specific ventilation defects (TSD{sub VE}) and nine subjects had ONLY tumour-specific defects (TSD). Subjects in the TSD{sub VE} group had significantly greater smoking-history (p=.006) and airflow obstruction (FEV{sub 1}/FVC) (p=.001). ROC analysis demonstrated an 87% classification rate for

Optimization of super-resolution processing using incomplete image sets in PET imaging.

Science.gov (United States)

Chang, Guoping; Pan, Tinsu; Clark, John W; Mawlawi, Osama R

2008-12-01

Super-resolution (SR) techniques are used in PET imaging to generate a high-resolution image by combining multiple low-resolution images that have been acquired from different points of view (POVs). The number of low-resolution images used defines the processing time and memory storage necessary to generate the SR image. In this paper, the authors propose two optimized SR implementations (ISR-1 and ISR-2) that require only a subset of the low-resolution images (two sides and diagonal of the image matrix, respectively), thereby reducing the overall processing time and memory storage. In an N x N matrix of low-resolution images, ISR-1 would be generated using images from the two sides of the N x N matrix, while ISR-2 would be generated from images across the diagonal of the image matrix. The objective of this paper is to investigate whether the two proposed SR methods can achieve similar performance in contrast and signal-to-noise ratio (SNR) as the SR image generated from a complete set of low-resolution images (CSR) using simulation and experimental studies. A simulation, a point source, and a NEMA/IEC phantom study were conducted for this investigation. In each study, 4 (2 x 2) or 16 (4 x 4) low-resolution images were reconstructed from the same acquired data set while shifting the reconstruction grid to generate images from different POVs. SR processing was then applied in each study to combine all as well as two different subsets of the low-resolution images to generate the CSR, ISR-1, and ISR-2 images, respectively. For reference purpose, a native reconstruction (NR) image using the same matrix size as the three SR images was also generated. The resultant images (CSR, ISR-1, ISR-2, and NR) were then analyzed using visual inspection, line profiles, SNR plots, and background noise spectra. The simulation study showed that the contrast and the SNR difference between the two ISR images and the CSR image were on average 0.4% and 0.3%, respectively. Line profiles of

An improved technique for the prediction of optimal image resolution ...

African Journals Online (AJOL)

Past studies to predict optimal image resolution required for generating spatial information for savannah ecosystems have yielded different outcomes, hence providing a knowledge gap that was investigated in the present study. The postulation, for the present study, was that by graphically solving two simultaneous ...

Optimal imaging parameters to visualize lumbar spinal nerve roots in MRI

Energy Technology Data Exchange (ETDEWEB)

Yamato, Hidetada; Takahashi, Toshiyuki; Funata, Tomonari; Nitta, Masaru; Nakazawa, Yasuo [Showa Univ., Tokyo (Japan). Hospital

2001-05-01

Radiculopathy due to lumber spine disorders is diagnosed mainly by radiculography. Recent advances in MRI have enabled non-invasive visualization of the lumbar nerve roots. Fifty normal volunteers were evaluated for optimal imaging angle to visualize the lumbar nerve roots and optimal imaging sequences. Results showed that in the coronal oblique plane, angles that visualized the nerve roots best were L4 17, L5 29.6, and S1 36.8. In the left sagittal oblique plane, the angles were L4 17.9, L5 21.4, and S1 12.6, and in the right sagittal oblique plane, L4 16.3, L5 19.4 and S1 12.6. SPGR showed the best results both in CNR values and visually. In summary, the optimal angle by which to visualize the lumbar spinal nerve roots increased as the roots became more caudal, except for S1 of the sagittal oblique plane, where individual variations were pronounced. SPGR was the best sequence for visualizing the nerve roots. (author)

Clinical PET/CT imaging. Promises and misconceptions

International Nuclear Information System (INIS)

Czernin, J.; Auerbach, M.A.

2005-01-01

PET/CT is now established as the most important imaging tool in oncology. PET/CT stages and restages cancer with a higher accuracy than PET or CT alone. The sometimes irrational approach to combine state of the art PET with the highest end CT devices should give way to a more reasonable equipment design tailored towards the specific clinical indications in well-defined patient populations. The continuing success of molecular PET/CT now depends more upon advances in molecular imaging with the introduction of targeted imaging probes for individualized therapy approaches in cancer patients and less upon technological advances of imaging equipment. (orig.)

Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation

Science.gov (United States)

Wen, Bo; Zhang, Qiheng; Zhang, Jianlin

2011-11-01

Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice. Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main optimization covers that, the structure's modularization for good implementation feasibility, reducing the data computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the real-time application.

Brain imaging with synthetic MR in children: clinical quality assessment

Energy Technology Data Exchange (ETDEWEB)

Betts, Aaron M.; Serai, Suraj [Cincinnati Children' s Hospital Medical Center, Department of Radiology, Cincinnati, OH (United States); Leach, James L.; Jones, Blaise V. [Cincinnati Children' s Hospital Medical Center, Department of Radiology, Cincinnati, OH (United States); University of Cincinnati College of Medicine, Cincinnati, OH (United States); Zhang, Bin [Cincinnati Children' s Hospital Medical Center, Biostatistics and Epidemiology, Cincinnati, OH (United States)

2016-10-15

Synthetic magnetic resonance imaging is a quantitative imaging technique that measures inherent T1-relaxation, T2-relaxation, and proton density. These inherent tissue properties allow synthesis of various imaging sequences from a single acquisition. Clinical use of synthetic MR imaging has been described in adult populations. However, use of synthetic MR imaging has not been previously reported in children. The purpose of this study is to report our assessment of diagnostic image quality using synthetic MR imaging in children. Synthetic MR acquisition was obtained in a sample of children undergoing brain MR imaging. Image quality assessments were performed on conventional and synthetic T1-weighted, T2-weighted, and FLAIR images. Standardized linear measurements were performed on conventional and synthetic T2 images. Estimates of patient age based upon myelination patterns were also performed. Conventional and synthetic MR images were evaluated on 30 children. Using a 4-point assessment scale, conventional imaging performed better than synthetic imaging for T1-weighted, T2-weighted, and FLAIR images. When the assessment was simplified to a dichotomized scale, the conventional and synthetic T1-weighted and T2-weighted images performed similarly. However, the superiority of conventional FLAIR images persisted in the dichotomized assessment. There were no statistically significant differences between linear measurements made on T2-weighted images. Estimates of patient age based upon pattern of myelination were also similar between conventional and synthetic techniques. Synthetic MR imaging may be acceptable for clinical use in children. However, users should be aware of current limitations that could impact clinical utility in the software version used in this study. (orig.)

Microwave imaging for conducting scatterers by hybrid particle swarm optimization with simulated annealing

International Nuclear Information System (INIS)

Mhamdi, B.; Grayaa, K.; Aguili, T.

2011-01-01

In this paper, a microwave imaging technique for reconstructing the shape of two-dimensional perfectly conducting scatterers by means of a stochastic optimization approach is investigated. Based on the boundary condition and the measured scattered field derived by transverse magnetic illuminations, a set of nonlinear integral equations is obtained and the imaging problem is reformulated in to an optimization problem. A hybrid approximation algorithm, called PSO-SA, is developed in this work to solve the scattering inverse problem. In the hybrid algorithm, particle swarm optimization (PSO) combines global search and local search for finding the optimal results assignment with reasonable time and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The hybrid approach elegantly combines the exploration ability of PSO with the exploitation ability of SA. Reconstruction results are compared with exact shapes of some conducting cylinders; and good agreements with the original shapes are observed.

Progress toward clinical implementation of the first flat-panel amorphous silicon imager

International Nuclear Information System (INIS)

Antonuk, Larry E.; El-Mohri, Youcef; Weidong, Huang; Sandler, Howard; Siewerdsen, Jeffrey H.; Yorkston, John

1995-01-01

Purpose: Approximately 7 years after the development of the general concept, megavoltage imagers based on thin-film, flat-panel electronics will likely enter routine clinical use within the next few years. In this paper, current capabilities and anticipated development of this imaging technology as pertains to clinical use will be presented. The results of the first use of this technology with an early prototype imager in a clinical setting are reported. The development of a more advanced clinical prototype imager designed for routine clinical use is described and the clinically-relevant capabilities, advantages, and limitations of this device are described. Materials and Methods: Flat-panel amorphous silicon imagers consist of an imaging array, an x-ray converter, external data acquisition electronics, along with appropriate software and a host workstation. The array consists of a two-dimensional grid of imaging pixels with each pixel consisting of a transistor coupled to a photodiode. An initial study of patient imaging has been performed with an early prototype imager which incorporates a 512x560 array with 450 μm pixels giving an imaging surface of 23x25 cm 2 . Portal images acquired with this prototype imager and with film under similar geometric and irradiation conditions were acquired and compared. In addition, a clinical prototype imager based upon a 26x26 cm 2 array with 508 μm pixels (512x512 pixels) is under development. This prototype incorporates advanced analog and digital external electronics which will improve imaging performance thereby increasing clinical utility of the device. The imagers are interfaced to the operation of a treatment machine so as to allow both radiographic and fluoroscopic operation. Results: The image quality is limited by the presence of pixel and line defects in the array and by the presence of correlated and uncorrelated noise sources in the acquisition system. Nevertheless, the contrast and spatial resolution offered by

Optimization of a hardware implementation for pulse coupled neural networks for image applications

Science.gov (United States)

Gimeno Sarciada, Jesús; Lamela Rivera, Horacio; Warde, Cardinal

2010-04-01

Pulse Coupled Neural Networks are a very useful tool for image processing and visual applications, since it has the advantages of being invariant to image changes as rotation, scale, or certain distortion. Among other characteristics, the PCNN changes a given image input into a temporal representation which can be easily later analyzed for pattern recognition. The structure of a PCNN though, makes it necessary to determine all of its parameters very carefully in order to function optimally, so that the responses to the kind of inputs it will be subjected are clearly discriminated allowing for an easy and fast post-processing yielding useful results. This tweaking of the system is a taxing process. In this paper we analyze and compare two methods for modeling PCNNs. A purely mathematical model is programmed and a similar circuital model is also designed. Both are then used to determine the optimal values of the several parameters of a PCNN: gain, threshold, time constants for feed-in and threshold and linking leading to an optimal design for image recognition. The results are compared for usefulness, accuracy and speed, as well as the performance and time requirements for fast and easy design, thus providing a tool for future ease of management of a PCNN for different tasks.

A method for energy window optimization for quantitative tasks that includes the effects of model-mismatch on bias: application to Y-90 bremsstrahlung SPECT imaging

International Nuclear Information System (INIS)

Rong Xing; Du Yong; Frey, Eric C

2012-01-01

calculating the bias due to model-mismatch and the variance of the VOI activity estimates, respectively. To obtain the optimal acquisition energy window for general situations of interest in clinical 90 Y microsphere imaging, we generated phantoms with multiple tumors of various sizes and various tumor-to-normal activity concentration ratios using a digital phantom that realistically simulates human anatomy, simulated 90 Y microsphere imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo simulation code, and used a previously proposed method for modeling the image degrading effects in quantitative SPECT reconstruction. The obtained optimal acquisition energy window was 100–160 keV. The values of the proposed FOM were much larger than the FOM taking into account only the variance of the activity estimates, thus demonstrating in our experiment that the bias of the activity estimates due to model-mismatch was a more important factor than the variance in terms of limiting the reliability of activity estimates. (paper)

A method for energy window optimization for quantitative tasks that includes the effects of model-mismatch on bias: application to Y-90 bremsstrahlung SPECT imaging.

Science.gov (United States)

Rong, Xing; Du, Yong; Frey, Eric C

2012-06-21

derived for calculating the bias due to model-mismatch and the variance of the VOI activity estimates, respectively. To obtain the optimal acquisition energy window for general situations of interest in clinical (90)Y microsphere imaging, we generated phantoms with multiple tumors of various sizes and various tumor-to-normal activity concentration ratios using a digital phantom that realistically simulates human anatomy, simulated (90)Y microsphere imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo simulation code, and used a previously proposed method for modeling the image degrading effects in quantitative SPECT reconstruction. The obtained optimal acquisition energy window was 100-160 keV. The values of the proposed FOM were much larger than the FOM taking into account only the variance of the activity estimates, thus demonstrating in our experiment that the bias of the activity estimates due to model-mismatch was a more important factor than the variance in terms of limiting the reliability of activity estimates.

Clinical images evaluation of mammograms: a national survey

International Nuclear Information System (INIS)

Moon, Woo Kyung; Kim, Tae Jung; Cha, Joo Hee

2003-01-01

The goal of this study was to survey the overall quality of mammographic images in Korea. A total of 598 mammographic images collected from 257 hospitals nationwide were reviewed in terms of eight images quality categories, namely positioning, compression, contrast, exposure, sharpness, noise, artifacts, and examination identification, and rated on a five-point scale: (1=severe deficiency, 2=major deficiency, 3=minor deficiency, 4=good, 5=best). Failure was defined as the occurrence of more than four major deficiencies or one severe deficiency (score of 1 or 2). The results were compared among hospitals of varying kinds, and common problems in clinical images quality were identified. Two hundred and seventeen mammographic images (36.3%) failed the evaluation. Poor images were found in descending order of frequency, at The Society for Medical Examination (33/69, 47.8%), non-radiologyclinics (42/88, 47.7%), general hospitals (92/216, 42.6%), radiology clinics (39/102, 38.2%), and university hospitals (11/123, 8.9%) (p<0.01, Chi-square test). Among the 598 images, serious problems which occurred were related to positioning in 23.7% of instances (n=142) (p<0.01, Chi-square test), examination identification in 5.7% (n=34), exposure in 5.4% (n=32), contrast in 4.2% (n=25), sharpness in 2.7% (n=16), compression in 2.5% (n=15), artifacts in 2.5% (n=15), and noise in 0.3% (n=2). This study showed that in Korea, 36.3% of the mammograms examined in this sampling had important image-related defects that might have led to serious errors in patient management. The failure rate was significantly higher in non-radiology clinics and at The Society for Medical Examination than at university hospitals

Optimization of contrast of MR images in imaging of knee joint; Optymalizacja kontrastu obrazow MR na przykladzie obrazow stawu kolanowego

Energy Technology Data Exchange (ETDEWEB)

Szyblinski, K. [Institute of Nuclear Physics, Cracow (Poland); Bacic, G. [Dartmouth College, Hanover, NH (United States)

1994-12-31

The work describes the method of contrast optimization in magnetic resonance imaging. Computer program presented in the report allows analysis of contrast in selected tissues as a function of experiment parameters. Application to imaging of knee joint is presented. 2 refs, 4 figs.

Collimator and energy window optimization for 90Y bremsstrahlung SPECT imaging: A SIMIND Monte Carlo study

International Nuclear Information System (INIS)

Roshan, Hoda Rezaei; Mahmoudian, Babak; Gharepapagh, Esmaeil; Azarm, Ahmadreza; Pirayesh Islamian, Jalil

2016-01-01

Treatment efficacy of radioembolization using Yttrium-90 ( 90 Y) microspheres is assessed by the 90 Y bremsstrahlung single photon emission computed tomography (SPECT) imaging following radioembolization. The radioisotopic image has the potential of providing reliable activity map of 90 Y microspheres distribution. One of the main reasons of the poor image quality in 90 Y bremsstrahlung SPECT imaging is the continuous and broad energy spectrum of the related bremsstrahlung photons. Furthermore, collimator geometry plays an impressive role in the spatial resolution, sensitivity and image contrast. Due to the relatively poor quality of the 90 Y bremsstrahlung SPECT images, we intend to optimize the medium-energy (ME) parallel-hole collimator and energy window. The Siemens e.cam gamma camera equipped with a ME collimator and a voxelized phantom was simulated by the SImulating Medical Imaging Nuclear Detectors (SIMIND) program. We used the SIMIND Monte Carlo program to generate the 90 Y bremsstrahlung SPECT projection of the digital Jaszczak phantom. The phantom consist of the six hot spheres ranging from 9.5 to 31.8 mm in diameter, which are used to evaluate the image contrast. In order to assess the effect of the energy window on the image contrast, three energy windows ranging from 60 to 160 KeV, 160 to 400 KeV, and 60 to 400 KeV were set on a 90 Y bremsstrahlung spectrum. As well, the effect of the hole diameter of a ME collimator on the image contrast and bremsstrahlung spectrum were investigated. For the fixed collimator and septa thickness values (3.28 cm and 1.14 mm, respectively), a hole diameter range (2.35–3.3 mm) was chosen based on the appropriate balance between the spatial resolution and sensitivity. The optimal energy window for 90 Y bremsstrahlung SPECT imaging was extended energy window from 60 to 400 KeV. Besides, The optimal value of the hole diameter of ME collimator was obtained 3.3 mm. Geometry of the ME parallel-hole collimator and energy

TH-A-18A-01: Innovation in Clinical Breast Imaging

International Nuclear Information System (INIS)

Liu, B; Yang, K; Yaffe, M; Chen, J

2014-01-01

Several novel modalities have been or are on the verge of being introduced into the breast imaging clinic. These include tomosynthesis imaging, dedicated breast CT, contrast-enhanced digital mammography, and automated breast ultrasound, all of which are covered in this course. Tomosynthesis and dedicated breast CT address the problem of tissue superimposition that limits mammography screening performance, by improved or full resolution of the 3D breast morphology. Contrast-enhanced digital mammography provides functional information that allows for visualization of tumor angiogenesis. 3D breast ultrasound has high sensitivity for tumor detection in dense breasts, but the imaging exam was traditionally performed by radiologists. In automated breast ultrasound, the scan is performed in an automated fashion, making for a more practical imaging tool, that is now used as an adjunct to digital mammography in breast cancer screening. This course will provide medical physicists with an in-depth understanding of the imaging physics of each of these four novel imaging techniques, as well as the rationale and implementation of QC procedures. Further, basic clinical applications and work flow issues will be discussed. Learning Objectives: To be able to describe the underlying physical and physiological principles of each imaging technique, and to understand the corresponding imaging acquisition process. To be able to describe the critical system components and their performance requirements. To understand the rationale and implementation of quality control procedures, as well as regulatory requirements for systems with FDA approval. To learn about clinical applications and understand risks and benefits/strength and weakness of each modality in terms of clinical breast imaging

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Energy Technology Data Exchange (ETDEWEB)

Ureba, A. [Dpto. Fisiología Médica y Biofísica. Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Salguero, F. J. [Nederlands Kanker Instituut, Antoni van Leeuwenhoek Ziekenhuis, 1066 CX Ámsterdam, The Nederlands (Netherlands); Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Leal, A., E-mail: alplaza@us.es [Dpto. Fisiología Médica y Biofísica, Facultad de Medicina, Universidad de Sevilla, E-41009 Sevilla (Spain); Miras, H. [Servicio de Radiofísica, Hospital Universitario Virgen Macarena, E-41009 Sevilla (Spain); Linares, R.; Perucha, M. [Servicio de Radiofísica, Hospital Infanta Luisa, E-41010 Sevilla (Spain)

2014-08-15

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

International Nuclear Information System (INIS)

Ureba, A.; Salguero, F. J.; Barbeiro, A. R.; Jimenez-Ortega, E.; Baeza, J. A.; Leal, A.; Miras, H.; Linares, R.; Perucha, M.

2014-01-01

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps.

Science.gov (United States)

Ureba, A; Salguero, F J; Barbeiro, A R; Jimenez-Ortega, E; Baeza, J A; Miras, H; Linares, R; Perucha, M; Leal, A

2014-08-01

The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called "biophysical" map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved

An improved technique for the prediction of optimal image resolution ...

African Journals Online (AJOL)

user

2010-10-04

Oct 4, 2010 ... Available online at http://www.academicjournals.org/AJEST ... robust technique for predicting optimal image resolution for the mapping of savannah ecosystems was developed. .... whether to purchase multi-spectral imagery acquired by GeoEye-2 ..... Analysis of the spectral behaviour of the pasture class in.

An experimental clinical evaluation of EIT imaging with ℓ1 data and image norms.

Science.gov (United States)

Mamatjan, Yasin; Borsic, Andrea; Gürsoy, Doga; Adler, Andy

2013-09-01

Electrical impedance tomography (EIT) produces an image of internal conductivity distributions in a body from current injection and electrical measurements at surface electrodes. Typically, image reconstruction is formulated using regularized schemes in which ℓ2-norms are used for both data misfit and image prior terms. Such a formulation is computationally convenient, but favours smooth conductivity solutions and is sensitive to outliers. Recent studies highlighted the potential of ℓ1-norm and provided the mathematical basis to improve image quality and robustness of the images to data outliers. In this paper, we (i) extended a primal-dual interior point method (PDIPM) algorithm to 2.5D EIT image reconstruction to solve ℓ1 and mixed ℓ1/ℓ2 formulations efficiently, (ii) evaluated the formulation on clinical and experimental data, and (iii) developed a practical strategy to select hyperparameters using the L-curve which requires minimum user-dependence. The PDIPM algorithm was evaluated using clinical and experimental scenarios on human lung and dog breathing with known electrode errors, which requires a rigorous regularization and causes the failure of reconstruction with an ℓ2-norm solution. The results showed that an ℓ1 solution is not only more robust to unavoidable measurement errors in a clinical setting, but it also provides high contrast resolution on organ boundaries.

Clinical PET/CT Atlas: A Casebook of Imaging in Oncology

International Nuclear Information System (INIS)

2015-01-01

Integrated positron emission tomography/computed tomography (PET/CT) has evolved since its introduction into the commercial market more than a decade ago. It is now a key procedure, particularly in oncological imaging. Over the last years in routine clinical service, PET/CT has had a significant impact on diagnosis, treatment planning, staging, therapy, and monitoring of treatment response and has therefore played an important role in the care of cancer patients. The high sensitivity from the PET component and the specificity of the CT component give this hybrid imaging modality the unique characteristics that make PET/CT, even after over 10 years of clinical use, one of the fastest growing imaging modalities worldwide. This publication combines over 90 comprehensive cases covering all major indications of fluorodeoxyglucose (18F-FDG)-PET/CT as well as some cases of clinically relevant special tracers. The cases provide an overview of what the specific disease can look like in PET/CT, the typical pattern of the disease’s spread as well as likely pitfalls and teaching points. This PET/CT Atlas will allow professionals interested in PET/CT imaging to embrace the variety of oncological imaging by providing clinically relevant teaching files on the effectiveness and diagnostic quality of FDG-PET/CT imaging in routine applications

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

Energy Technology Data Exchange (ETDEWEB)

Dong, F. [The Cleveland Clinic (United States)

2016-06-15

in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: Understand the function and impact of major components of X-ray tube on the image quality. Understand the function and impact of major components of CT detector on the image quality. Be familiar with the basic procedure of CT image reconstruction. Understand the effect of image reconstruction on CT image quality and artifacts. Understand the root causes of common CT image artifacts. Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. Be familiar with various CT dose metrics and their interaction with acquisition parameters. New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

International Nuclear Information System (INIS)

Dong, F.

2016-01-01

in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: Understand the function and impact of major components of X-ray tube on the image quality. Understand the function and impact of major components of CT detector on the image quality. Be familiar with the basic procedure of CT image reconstruction. Understand the effect of image reconstruction on CT image quality and artifacts. Understand the root causes of common CT image artifacts. Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. Be familiar with various CT dose metrics and their interaction with acquisition parameters. New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.

An optimized framework for quantitative magnetization transfer imaging of the cervical spinal cord in vivo.

Science.gov (United States)

Battiston, Marco; Grussu, Francesco; Ianus, Andrada; Schneider, Torben; Prados, Ferran; Fairney, James; Ourselin, Sebastien; Alexander, Daniel C; Cercignani, Mara; Gandini Wheeler-Kingshott, Claudia A M; Samson, Rebecca S

2018-05-01

To develop a framework to fully characterize quantitative magnetization transfer indices in the human cervical cord in vivo within a clinically feasible time. A dedicated spinal cord imaging protocol for quantitative magnetization transfer was developed using a reduced field-of-view approach with echo planar imaging (EPI) readout. Sequence parameters were optimized based in the Cramer-Rao-lower bound. Quantitative model parameters (i.e., bound pool fraction, free and bound pool transverse relaxation times [ T2F, T2B], and forward exchange rate [k FB ]) were estimated implementing a numerical model capable of dealing with the novelties of the sequence adopted. The framework was tested on five healthy subjects. Cramer-Rao-lower bound minimization produces optimal sampling schemes without requiring the establishment of a steady-state MT effect. The proposed framework allows quantitative voxel-wise estimation of model parameters at the resolution typically used for spinal cord imaging (i.e. 0.75 × 0.75 × 5 mm 3 ), with a protocol duration of ∼35 min. Quantitative magnetization transfer parametric maps agree with literature values. Whole-cord mean values are: bound pool fraction = 0.11(±0.01), T2F = 46.5(±1.6) ms, T2B = 11.0(±0.2) µs, and k FB  = 1.95(±0.06) Hz. Protocol optimization has a beneficial effect on reproducibility, especially for T2B and k FB . The framework developed enables robust characterization of spinal cord microstructure in vivo using qMT. Magn Reson Med 79:2576-2588, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc

Clinical advances in cardiovascular magnetic resonace imaging and angiography

NARCIS (Netherlands)

Bosch, van den H.C.M.

2018-01-01

Cardiovascular magnetic resonance imaging is an important noninvasive imaging modality for the diagnosis, clinical work‐up and treatment planning in patients suspected for a wide range of cardiovascular pathology. CMR imaging is accurate and reliable, and provides invaluable information to evaluate

An optimized strategy for real-time hemorrhage monitoring with electrical impedance tomography

International Nuclear Information System (INIS)

Xu, Canhua; Dai, Meng; You, Fusheng; Shi, Xuetao; Fu, Feng; Liu, Ruigang; Dong, Xiuzhen

2011-01-01

Delayed detection of an internal hemorrhage may result in serious disabilities and possibly death for a patient. Currently, there are no portable medical imaging instruments that are suitable for long-term monitoring of patients at risk of internal hemorrhage. Electrical impedance tomography (EIT) has the potential to monitor patients continuously as a novel functional image modality and instantly detect the occurrence of an internal hemorrhage. However, the low spatial resolution and high sensitivity to noise of this technique have limited its application in clinics. In addition, due to the circular boundary display mode used in current EIT images, it is difficult for clinicians to identify precisely which organ is bleeding using this technique. The aim of this study was to propose an optimized strategy for EIT reconstruction to promote the use of EIT for clinical studies, which mainly includes the use of anatomically accurate boundary shapes, rapid selection of optimal regularization parameters and image fusion of EIT and computed tomography images. The method was evaluated on retroperitoneal and intraperitoneal bleeding piglet data. Both traditional backprojection images and optimized images among different boundary shapes were reconstructed and compared. The experimental results demonstrated that EIT images with precise anatomical information can be reconstructed in which the image resolution and resistance to noise can be improved effectively

Narrow-Band Imaging: Clinical Application in Gastrointestinal Endoscopy

Directory of Open Access Journals (Sweden)

Sandra Barbeiro

2018-03-01

Full Text Available Narrow-band imaging is an advanced imaging system that applies optic digital methods to enhance endoscopic images and improves visualization of the mucosal surface architecture and microvascular pattern. Narrow-band imaging use has been suggested to be an important adjunctive tool to white-light endoscopy to improve the detection of lesions in the digestive tract. Importantly, it also allows the distinction between benign and malignant lesions, targeting biopsies, prediction of the risk of invasive cancer, delimitation of resection margins, and identification of residual neoplasia in a scar. Thus, in expert hands it is a useful tool that enables the physician to decide on the best treatment (endoscopic or surgical and management. Current evidence suggests that it should be used routinely for patients at increased risk for digestive neoplastic lesions and could become the standard of care in the near future, at least in referral centers. However, adequate training programs to promote the implementation of narrow-band imaging in daily clinical practice are needed. In this review, we summarize the current scientific evidence on the clinical usefulness of narrow-band imaging in the diagnosis and characterization of digestive tract lesions/cancers and describe the available classification systems.

Graphical user interface to optimize image contrast parameters used in object segmentation - biomed 2009.

Science.gov (United States)

Anderson, Jeffrey R; Barrett, Steven F

2009-01-01

Image segmentation is the process of isolating distinct objects within an image. Computer algorithms have been developed to aid in the process of object segmentation, but a completely autonomous segmentation algorithm has yet to be developed [1]. This is because computers do not have the capability to understand images and recognize complex objects within the image. However, computer segmentation methods [2], requiring user input, have been developed to quickly segment objects in serial sectioned images, such as magnetic resonance images (MRI) and confocal laser scanning microscope (CLSM) images. In these cases, the segmentation process becomes a powerful tool in visualizing the 3D nature of an object. The user input is an important part of improving the performance of many segmentation methods. A double threshold segmentation method has been investigated [3] to separate objects in gray scaled images, where the gray level of the object is among the gray levels of the background. In order to best determine the threshold values for this segmentation method the image must be manipulated for optimal contrast. The same is true of other segmentation and edge detection methods as well. Typically, the better the image contrast, the better the segmentation results. This paper describes a graphical user interface (GUI) that allows the user to easily change image contrast parameters that will optimize the performance of subsequent object segmentation. This approach makes use of the fact that the human brain is extremely effective in object recognition and understanding. The GUI provides the user with the ability to define the gray scale range of the object of interest. These lower and upper bounds of this range are used in a histogram stretching process to improve image contrast. Also, the user can interactively modify the gamma correction factor that provides a non-linear distribution of gray scale values, while observing the corresponding changes to the image. This

Image de-noising based on mathematical morphology and multi-objective particle swarm optimization

Science.gov (United States)

Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng

2017-07-01

To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.

A dedicated cone-beam CT system for musculoskeletal extremities imaging: Design, optimization, and initial performance characterization

International Nuclear Information System (INIS)

Zbijewski, W.; De Jean, P.; Prakash, P.; Ding, Y.; Stayman, J. W.; Packard, N.; Senn, R.; Yang, D.; Yorkston, J.; Machado, A.; Carrino, J. A.; Siewerdsen, J. H.

2011-01-01

cm diameter bore (20 x 20 x 20 cm 3 field of view); total acquisition arc of ∼240 deg. The system MTF declines to 50% at ∼1.3 mm -1 and to 10% at ∼2.7 mm -1 , consistent with sub-millimeter spatial resolution. Analysis of DQE suggested a nominal technique of 90 kVp (+0.3 mm Cu added filtration) to provide high imaging performance from ∼500 projections at less than ∼0.5 kW power, implying ∼6.4 mGy (0.064 mSv) for low-dose protocols and ∼15 mGy (0.15 mSv) for high-quality protocols. The experimental studies show improved image uniformity and contrast-to-noise ratio (without increase in dose) through incorporation of a custom 10:1 GR antiscatter grid. Cadaver images demonstrate exquisite bone detail, visualization of articular morphology, and soft-tissue visibility comparable to diagnostic CT (10-20 HU contrast resolution). Conclusions: The results indicate that the proposed system will deliver volumetric images of the extremities with soft-tissue contrast resolution comparable to diagnostic CT and improved spatial resolution at potentially reduced dose. Cascaded systems analysis provided a useful basis for system design and optimization without costly repeated experimentation. A combined process of design specification, image quality analysis, clinical feedback, and revision yielded a prototype that is now awaiting clinical pilot studies. Potential advantages of the proposed system include reduced space and cost, imaging of load-bearing extremities, and combined volumetric imaging with real-time fluoroscopy and digital radiography.

Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

Science.gov (United States)

Prescott, Jeffrey William

2013-02-01

The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.