Functional magnetic resonance imaging by visual stimulation

International Nuclear Information System (INIS)

Nishimura, Yukiko; Negoro, Kiyoshi; Morimatsu, Mitsunori; Hashida, Masahiro

1996-01-01

We evaluated functional magnetic resonance images obtained in 8 healthy subjects in response to visual stimulation using a conventional clinical magnetic resonance imaging system with multi-slice spin-echo echo planar imaging. Activation in the visual cortex was clearly demonstrated by the multi-slice experiment with a task-related change in signal intensity. In addition to the primary visual cortex, other areas were also activated by a complicated visual task. Multi-slice spin-echo echo planar imaging offers high temporal resolution and allows the three-dimensional analysis of brain function. Functional magnetic resonance imaging provides a useful noninvasive method of mapping brain function. (author)

Unbiased group-wise image registration: applications in brain fiber tract atlas construction and functional connectivity analysis.

Science.gov (United States)

Geng, Xiujuan; Gu, Hong; Shin, Wanyong; Ross, Thomas J; Yang, Yihong

2011-10-01

We propose an unbiased implicit-reference group-wise (IRG) image registration method and demonstrate its applications in the construction of a brain white matter fiber tract atlas and the analysis of resting-state functional MRI (fMRI) connectivity. Most image registration techniques pair-wise align images to a selected reference image and group analyses are performed in the reference space, which may produce bias. The proposed method jointly estimates transformations, with an elastic deformation model, registering all images to an implicit reference corresponding to the group average. The unbiased registration is applied to build a fiber tract atlas by registering a group of diffusion tensor images. Compared to reference-based registration, the IRG registration improves the fiber track overlap within the group. After applying the method in the fMRI connectivity analysis, results suggest a general improvement in functional connectivity maps at a group level in terms of larger cluster size and higher average t-scores.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

Science.gov (United States)

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS.

Science.gov (United States)

Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method. The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint. Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

Science.gov (United States)

Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

2017-03-21

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

Subband/Transform MATLAB Functions For Processing Images

Science.gov (United States)

Glover, D.

1995-01-01

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

The rice growth image files - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive [Life Science Database Archive metadata

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Full Text Available List Contact us The Rice Growth Monitoring for The Phenotypic Functional Analysis The rice growth image file...s Data detail Data name The rice growth image files DOI 10.18908/lsdba.nbdc00945-004 Description of data contents The rice growth ima...ge files categorized based on file size. Data file File name: image files (director...y) File URL: ftp://ftp.biosciencedbc.jp/archive/agritogo-rice-phenome/LATEST/image...ite Policy | Contact Us The rice growth image files - The Rice Growth Monitoring for The Phenotypic Functional Analysis | LSDB Archive ...

Is functional MR imaging assessment of hemispheric language dominance as good as the Wada test?: a meta-analysis.

Science.gov (United States)

Dym, R Joshua; Burns, Judah; Freeman, Katherine; Lipton, Michael L

2011-11-01

To perform a systematic review and meta-analysis to quantitatively assess functional magnetic resonance (MR) imaging lateralization of language function in comparison with the Wada test. This study was determined to be exempt from review by the institutional review board. A systematic review and meta-analysis were performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A structured Medline search was conducted to identify all studies that compared functional MR imaging with the Wada test for determining hemispheric language dominance prior to brain surgery. Studies meeting predetermined inclusion criteria were selected independently by two radiologists who also assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies tool. Language dominance was classified as typical (left hemispheric language dominance) or atypical (right hemispheric language dominance or bilateral language representation) for each patient. A meta-analysis was then performed by using a bivariate random-effects model to derive estimates of sensitivity and specificity, with Wada as the standard of reference. Subgroup analyses were also performed to compare the different functional MR imaging techniques utilized by the studies. Twenty-three studies, comprising 442 patients, met inclusion criteria. The sensitivity and specificity of functional MR imaging for atypical language dominance (compared with the Wada test) were 83.5% (95% confidence interval: 80.2%, 86.7%) and 88.1% (95% confidence interval: 87.0%, 89.2%), respectively. Functional MR imaging provides an excellent, noninvasive alternative for language lateralization and should be considered for the initial preoperative assessment of hemispheric language dominance. Further research may help determine which functional MR methods are most accurate for specific patient populations. RSNA, 2011

Nuclear magnetic resonance imaging and brain functional exploration

International Nuclear Information System (INIS)

Le Bihan, D.; CEA, 91 - Orsay

1997-01-01

The utilization of nuclear magnetic resonance imaging for functional analysis of the brain is presented: the oxygenated and deoxygenated blood flowing in the brain do not have the same effect on NMR images; the oxygenated blood, related to brain activity, may be detected and the corresponding activity zone in the brain, identified; functional NMR imaging could be used to gain a better understanding of functional troubles linked to neurological or psychiatric diseases

Psychophysical analysis of monitor display functions affecting observer diagnostic performance of CT image on liquid crystal display monitors

International Nuclear Information System (INIS)

Yamaguchi, M.; Fujita, H.; Asai, Y.; Uemura, M.; Ookura, Y.; Matsumoto, M.; Johkoh, T.

2005-01-01

The aim of the present study was to propose suitable display functions for CT image representation on liquid crystal display (LCD) monitors by analyzing the characteristics of the monitor's typical display functions using psychophysical analysis. The luminance of the LCD monitor was adjusted to a maximum of 275 cd/m 2 and 480 cd/m 2 . Three types of postcalibrated display functions (i.e., GSDF, CIELAB, and Exponential γ 2.2) were evaluated. Luminance calculation of a new grayscale test pattern (NGTP) was done for the conversion of the digital driving level (DDL) into the CT value. The psychophysical gradient δ of display functions for the CT value was evaluated and compared via statistical analysis. The δ value of GSDF and CIE decreased exponentially; however, the δ value of Exponential γ 2.2 showed a convex curve with a peak at a specific point. There was a statistically significant difference among the δ values of the three types of display functions on the 480 cd/m 2 maximum via Kruskal Wallis test (P<0.001). The GSDF was suitable for observation of abdominal and lung CT images; however, the display function combined the Exponential γ 2.2 and the GSDF functions and was ideal for observation of brain CT images by psychophysical analysis. (orig.)

Estimating variability in functional images using a synthetic resampling approach

International Nuclear Information System (INIS)

Maitra, R.; O'Sullivan, F.

1996-01-01

Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods

Shape analysis in medical image analysis

CERN Document Server

Tavares, João

2014-01-01

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...

A Functional Approach to Hyperspectral Image Analysis in the Cloud

Science.gov (United States)

Wilson, A.; Lindholm, D. M.; Coddington, O.; Pilewskie, P.

2017-12-01

Hyperspectral image volumes are very large. A hyperspectral image analysis (HIA) may use 100TB of data, a huge barrier to their use. Hylatis is a new NASA project to create a toolset for HIA. Through web notebook and cloud technology, Hylatis will provide a more interactive experience for HIA by defining and implementing concepts and operations for HIA, identified and vetted by subject matter experts, and callable within a general purpose language, particularly Python. Hylatis leverages LaTiS, a data access framework developed at LASP. With an OPeNDAP compliant interface plus additional server side capabilities, the LaTiS API provides a uniform interface to virtually any data source, and has been applied to various storage systems, including: file systems, databases, remote servers, and in various domains including: space science, systems administration and stock quotes. In the LaTiS architecture, data `adapters' read data into a data model, where server-side computations occur. Data `writers' write data from the data model into the desired format. The Hylatis difference is the data model. In LaTiS, data are represented as mathematical functions of independent and dependent variables. Domain semantics are not present at this level, but are instead present in higher software layers. The benefit of a domain agnostic, mathematical representation is having the power of math, particularly functional algebra, unconstrained by domain semantics. This agnosticism supports reusable server side functionality applicable in any domain, such as statistical, filtering, or projection operations. Algorithms to aggregate or fuse data can be simpler because domain semantics are separated from the math. Hylatis will map the functional model onto the Spark relational interface, thereby adding a functional interface to that big data engine.This presentation will discuss Hylatis goals, strategies, and current state.

Functional Store Image and Corporate Social Responsibility Image: A Congruity Analysis on Store Loyalty

OpenAIRE

Jamaliah Mohd. Yusof; Rosidah Musa; Sofiah Abd. Rahman

2011-01-01

With previous studies that examined the importance of functional store image and CSR, this study is aimed at examining their effects in the self-congruity model in influencing store loyalty. In particular, this study developed and tested a structural model in the context of retailing industry on the self-congruity theory. Whilst much of the self-congruity studies have incorporated functional store image, there has been lack of studies that examined social responsibility i...

A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis

Science.gov (United States)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2011-03-01

This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).

Merits and limitations of functional imaging techniques

International Nuclear Information System (INIS)

Holman, B.L.

1982-01-01

The functional image is a powerful tool to look at physiologic information. It is ideally suited to the radiotracer method which measures regional physiology. It is ideal for regional analysis, providing a format which nicely complements the more traditional and anatomically oriented data displays. The functional image must be used intelligently, however, with the user aware of its limitations and of the meaning of indices which it is measuring. (orig.)

Three-dimensional reconstruction of functional brain images

International Nuclear Information System (INIS)

Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao

1999-01-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface

Three-dimensional reconstruction of functional brain images

Energy Technology Data Exchange (ETDEWEB)

Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao [Kyoto Univ. (Japan)

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface

Analysis of a multi-frequency electromagnetic imaging functional for thin, crack-like electromagnetic inclusions

OpenAIRE

Park, Won-Kwang

2012-01-01

Recently, a non-iterative multi-frequency subspace migration imaging algorithm was developed based on an asymptotic expansion formula for thin, curve-like electromagnetic inclusions and the structure of singular vectors in the Multi-Static Response (MSR) matrix. The present study examines the structure of subspace migration imaging functional and proposes an improved imaging functional weighted by the frequency. We identify the relationship between the imaging functional and Bessel functions ...

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS

OpenAIRE

Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

Objective: This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. Methods: A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, a...

Effect of phase-encoding direction on group analysis of resting-state functional magnetic resonance imaging.

Science.gov (United States)

Mori, Yasuo; Miyata, Jun; Isobe, Masanori; Son, Shuraku; Yoshihara, Yujiro; Aso, Toshihiko; Kouchiyama, Takanori; Murai, Toshiya; Takahashi, Hidehiko

2018-05-17

Echo-planar imaging is a common technique used in functional magnetic resonance imaging (fMRI), however it suffers from image distortion and signal loss because of large susceptibility effects that are related to the phase-encoding direction of the scan. Despite this relationship, the majority of neuroimaging studies have not considered the influence of phase-encoding direction. Here, we aimed to clarify how phase-encoding direction can affect the outcome of an fMRI connectivity study of schizophrenia. Resting-state fMRI using anterior to posterior (A-P) and posterior to anterior (P-A) directions was used to examine 25 patients with schizophrenia (SC) and 37 matched healthy controls (HC). We conducted a functional connectivity analysis using independent component analysis and performed three group comparisons: A-P vs. P-A (all participants), SC vs. HC for the A-P and P-A datasets, and the interaction between phase-encoding direction and participant group. The estimated functional connectivity differed between the two phase-encoding directions in areas that were more extensive than those where signal loss has been reported. Although functional connectivity in the SC group was lower than that in the HC group for both directions, the A-P and P-A conditions did not exhibit the same specific pattern of differences. Further, we observed an interaction between participant group and the phase-encoding direction in the left temporo-parietal junction and left fusiform gyrus. Phase-encoding direction can influence the results of functional connectivity studies. Thus, appropriate selection and documentation of phase-encoding direction will be important in future resting-state fMRI studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Functional imaging of the pancreas

International Nuclear Information System (INIS)

Nakanishi, Fumiko

1984-01-01

An image processing technique for functional imaging of the pancreas was developed and is here reported. In this paper, clinical efficacy of the technique for detecting pancreatic abnormality is evaluated in comparison with conventional pancreatic scintigraphy and CT. For quantitative evaluation, functional rate, i.e. the rate of normal functioning pancreatic area, was calculated from the functional image and subtraction image. Two hundred and ninety-five cases were studied using this technique. Conventional image had a sensitivity of 65 % and a specificity of 78 %, while the use of functional imaging improved sensitivity to 88 % and specificity to 88 %. The mean functional rate in patients with pancreatic disease was significantly lower (33.3+-24.5 in patients with chronic pancreatitis, 28.1+-26.9 in patients with acute pancreatitis, 43.4+-22.3 in patients with diabetes mellitus, 20.4+-23.4 in patients with pancreatic cancer) than the mean functional rate in cases without pancreatic disease (86.4+-14.2). It is suggested that functional image of the pancreas reflecting pancreatic exocrine function and functional rate is a useful indicator of pancreatic exocrine function. (author)

Studies on renal function in the elderly by analysis of radioisotope renal images

International Nuclear Information System (INIS)

Ohishi, Yukihiko

1990-01-01

This study was carried out to evaluate the potential of radionuclide renal imagings for examining senile renal function in a total of 178 subjects. Single photon emission computed tomography (SPECT) with Tc-99m-dimercaptosuccinic acid (Tc-DMSA) was performed in the senile group (60-87 years) and in the adult group to determine renal uptake rate of Tc-DMSA and renal volume. Renography studies with I-131 hippuran (n=100) and Tc-99m diethylentriaminepentaacetic acid (Tc-DTPA) (n=20) were also performed for deconvolution analysis. Mean transit time (MTT) was mainly assessed as one of the retention function parameters. Blood residual rates (R15%) at fifteen minutes were also investigated. Renal volume and renal uptake rate for healthy persons were significantly lower in the senile group (n=17) than the adult group (n=24), 205±50 ml vs 225±27 ml; and 22±5% vs 26±2%. I-133 hippuran renography in healthy persons (n=35) showed a tendency toward higher MTT values with aging; however, there was no significant difference among age groups. R15%, obtained by I-133 hippuran renograms, tended to be higher with aging in age groups of persons younger than 70 years. A decreased number of effective nephrons was considered to result in higher R15% values even when aged persons had normal MTT values of I-131 hippuran. Split renal function values for healthy persons, calculated by the two radionuclide imagings, were lower in the senile group than the adult group, suggesting the usefulness of radionuclide imagings in renal function examination. (N.K.)

Application of Improved Wavelet Thresholding Function in Image Denoising Processing

Directory of Open Access Journals (Sweden)

Hong Qi Zhang

2014-07-01

Full Text Available Wavelet analysis is a time – frequency analysis method, time-frequency localization problems are well solved, this paper analyzes the basic principles of the wavelet transform and the relationship between the signal singularity Lipschitz exponent and the local maxima of the wavelet transform coefficients mold, the principles of wavelet transform in image denoising are analyzed, the disadvantages of traditional wavelet thresholding function are studied, wavelet threshold function, the discontinuity of hard threshold and constant deviation of soft threshold are improved, image is denoised through using the improved threshold function.

Investigations of new cardiac functional imaging using Fourier analysis of gated blood-pool study

International Nuclear Information System (INIS)

Maeda, H.; Takeda, K.; Nakagawa, T.; Yamaguchi, N.; Taguchi, M.; Konishi, T.; Hamada, M.

1982-01-01

A new cardiac functional imaging, using temporal Fourier analysis of 28-frame gated cardiac blood-pool studies, was developed. A time-activity curve of each pixel was approximated by its Fourier series. Approximation by the sum for terms to the 3rd frequency of its Fourier series was considered to be most reasonable because of having the least aberration due to statistical fluctuation and close agreement between the global left ventricular curve and the regional fitted curves in normal subjects. To evaluate the ventricular systolic and diastolic performances, 9 parameters were analyzed from thus fitted curves on a pixel-by-pixel basis and displayed on a colour CRT in 64x64 matrix form. In patients with hypertrophic obstructive cardiomyopathy and other cardiac lesions, detailed information on the regional ventricular systolic and diastolic performances was clearly visualized by this method, which was difficult to obtain from the usual functional images of phase and amplitude at the fundamental frequency alone

Interhemispheric disconnectivity in the sensorimotor network in bipolar disorder revealed by functional connectivity and diffusion tensor imaging analysis

Directory of Open Access Journals (Sweden)

Takuya Ishida

2017-06-01

Full Text Available Background: Little is known regarding interhemispheric functional connectivity (FC abnormalities via the corpus callosum in subjects with bipolar disorder (BD, which might be a key pathophysiological basis of emotional processing alterations in BD. Methods: We performed tract-based spatial statistics (TBSS using diffusion tensor imaging (DTI in 24 healthy control (HC and 22 BD subjects. Next, we analyzed the neural networks with independent component analysis (ICA in 32HC and 25 BD subjects using resting-state functional magnetic resonance imaging. Results: In TBSS analysis, we found reduced fractional anisotropy (FA in the corpus callosum of BD subjects. In ICA, functional within-connectivity was reduced in two clusters in the sensorimotor network (SMN (right and left primary somatosensory areas of BD subjects compared with HCs. FC between the two clusters and FA values in the corpus callosum of BD subjects was significantly correlated. Further, the functional within-connectivity was related to Young Mania Rating Scale (YMRS total scores in the right premotor area in the SMN of BD subjects. Limitations: Almost all of our BD subjects were taking several medications which could be a confounding factor. Conclusions: Our findings suggest that interhemispheric FC dysfunction in the SMN is associated with the impaired nerve fibers in the corpus callosum, which could be one of pathophysiological bases of emotion processing dysregulation in BD patients. Keywords: Neuroscience, Medical imaging, Psychiatry

An image analysis system for near-infrared (NIR) fluorescence lymph imaging

Science.gov (United States)

Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

2011-03-01

Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

Functionalized Nanolipobubbles Embedded Within a Nanocomposite Hydrogel: a Molecular Bio-imaging and Biomechanical Analysis of the System.

Science.gov (United States)

Mufamadi, Maluta S; Choonara, Yahya E; Kumar, Pradeep; du Toit, Lisa C; Modi, Girish; Naidoo, Dinesh; Iyuke, Sunny E; Pillay, Viness

2017-04-01

The purpose of this study was to explore the use of molecular bio-imaging systems and biomechanical dynamics to elucidate the fate of a nanocomposite hydrogel system prepared by merging FITC-labeled nanolipobubbles within a cross-linked hydrogel network. The nanocomposite hydrogel system was characterized by size distribution analysis and zeta potential as well as shears thinning behavior, elastic modulus (G'), viscous loss moduli (G"), TEM, and FTIR. In addition, molecular bio-imaging via Vevo ultrasound and Cell-viZio techniques evaluated the stability and distribution of the nanolipobubbles within the cross-linked hydrogel. FITC-labeled and functionalized nanolipobubbles had particle sizes between 135 and 158 nm (PdI = 0.129 and 0.190) and a zeta potential of -34 mV. TEM and ultrasound imaging revealed the uniformity and dimensional stability of the functionalized nanolipobubbles pre- and post-embedment into the cross-linked hydrogel. Biomechanical characterization of the hydrogel by shear thinning behavior was governed by the polymer concentration and the cross-linker, glutaraldehyde. Ultrasound analysis and Cell-viZio bio-imaging were highly suitable to visualize the fluorescent image-guided nanolipobubbles and their morphology post-embedment into the hydrogel to form the NanoComposite system. Since the nanocomposite is intended for targeted treatment of neurodegenerative disorders, the distribution of the functionalized nanolipobubbles into PC12 neuronal cells was also ascertained via confocal microscopy. Results demonstrated effective release and localization of the nanolipobubbles within PC12 neuronal cells. The molecular structure of the synthetic surface peptide remained intact for an extended period to ensure potency for targeted delivery from the hydrogel ex vivo. These findings provide further insight into the properties of nanocomposite hydrogels for specialized drug delivery.

Rapid, low-cost, image analysis through video processing

International Nuclear Information System (INIS)

Levinson, R.A.; Marrs, R.W.; Grantham, D.G.

1976-01-01

Remote Sensing now provides the data necessary to solve many resource problems. However, many of the complex image processing and analysis functions used in analysis of remotely-sensed data are accomplished using sophisticated image analysis equipment. High cost of this equipment places many of these techniques beyond the means of most users. A new, more economical, video system capable of performing complex image analysis has now been developed. This report describes the functions, components, and operation of that system. Processing capability of the new video image analysis system includes many of the tasks previously accomplished with optical projectors and digital computers. Video capabilities include: color separation, color addition/subtraction, contrast stretch, dark level adjustment, density analysis, edge enhancement, scale matching, image mixing (addition and subtraction), image ratioing, and construction of false-color composite images. Rapid input of non-digital image data, instantaneous processing and display, relatively low initial cost, and low operating cost gives the video system a competitive advantage over digital equipment. Complex pre-processing, pattern recognition, and statistical analyses must still be handled through digital computer systems. The video system at the University of Wyoming has undergone extensive testing, comparison to other systems, and has been used successfully in practical applications ranging from analysis of x-rays and thin sections to production of color composite ratios of multispectral imagery. Potential applications are discussed including uranium exploration, petroleum exploration, tectonic studies, geologic mapping, hydrology sedimentology and petrography, anthropology, and studies on vegetation and wildlife habitat

Development of program for renal function study with quantification analysis of nuclear medicine image

International Nuclear Information System (INIS)

Song, Ju Young; Lee, Hyoung Koo; Suh, Tae Suk; Choe, Bo Young; Shinn, Kyung Sub; Chung, Yong An; Kim, Sung Joon; Chung, Soo Kyo

2001-01-01

In this study, we developed a new software tool for the analysis of renal scintigraphy which can be modified more easily by a user who needs to study new clinical applications, and the appropriateness of the results from our program was studied. The analysis tool was programmed with IDL5.2 and designed for use on a personal computer running Windows. For testing the developed tool and studying the appropriateness of the calculated glomerular filtration rate (GFR), 99m Tc-DTPA was adminstered to 10 adults in normal condition. In order to study the appropriateness of the calculated mean transit time (MTT). 99m Tc-DTPA and 99m Tc-MAG3 were administered to 11 adults in normal condition and 22 kidneys were analyzed. All the images were acquired with ORBITOR, the Siemens gamma camera. With the developed tool, we could show dynamic renal images and time activity curve (TAC) in each ROI and calculate clinical parameters of renal function. The results calculated by the developed tool were not different statistically from the results obtained by the Siemens application program (Tmax: p=0.68, Relative Renal Function: p=1.0 GFR: p=0.25) and the developed program proved reasonable. The MTT calculation tool proved to be reasonable by the evaluation of the influence of hydration status on MTT. We have obtained reasonable clinical parameters for the evaluation of renal function with the software tool developed in this study. The developed tool could prove more practical than conventional, commercial programs

Functional Magnetic Resonance Imaging

Science.gov (United States)

Voos, Avery; Pelphrey, Kevin

2013-01-01

Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

Functional imaging of the pelvic floor

Energy Technology Data Exchange (ETDEWEB)

Lienemann, Andreas E-mail: andreaslienemann@web.de; Fischer, Tanja

2003-08-01

Introduction/Objective: Pelvic floor dysfunction and associated pelvic organ prolapse represent a major problem in our present-day society, mostly afflicting parous women. Magnetic resonance imaging (MRI) is assuming an increasingly important role in the more accurate delineation of the extent of the problem. This article briefly reviews one of the main radiological methods for the dynamic evaluation of the pelvic floor: functional cine MRI. Methods and Material: Out of the literature the smallest common denominator for functional cine MRI can be defined as follows: high field system; patient either in supine or sitting position; fast gradient echo sequence; midsagittal slice orientation; either a stack of slices or repeated measurements at the same slice position with the patient at rest or straining; image analysis using the pubococcygeal reference line. Results: All except two publications stress the usefulness of functional cine MRI in the evaluation of patients with organ descent and prolapse. This well accepted method allows for the visualization of all relevant structures in the anterior, middle and posterior compartment. It is especially useful in the detection of enteroceles, and provides a reliable postoperative follow-up tool. Isolated urinary or stool incontinence are not an indication for functional cine MRI, as is the case in patients with equivocal clinical findings. To date it does not allow for real 3D imaging of the pelvic floor or sufficient determination of fascial defects. Discussion: Functional cine MRI of the pelvic floor is a promising new imaging method for the detection of organ descent and prolapse in patients with equivocal clinical findings. The combination of function and morphology allows for an innovative view of the pelvic floor, and thus adds to our understanding of the various interactions of the structures.

Imaging visual function of the human brain

International Nuclear Information System (INIS)

Marg, E.

1988-01-01

Imaging of human brain structure and activity with particular reference to visual function is reviewed along with methods of obtaining the data including computed tomographic (CT) scan, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET). The literature is reviewed and the potential for a new understanding of brain visual function is discussed. PET is reviewed from basic physical principles to the most recent visual brain findings with oxygen-15. It is shown that there is a potential for submillimeter localization of visual functions with sequentially different visual stimuli designed for the temporal separation of the responses. Single photon emission computed tomography (SPECT), a less expensive substitute for PET, is also discussed. MRS is covered from basic physical principles to the current state of the art of in vivo biochemical analysis. Future possible clinical applications are discussed. Improved understanding of the functional neural organization of vision and brain will open a window to maps and circuits of human brain function.119 references

Unevenness on aerosol inhalation lung images and lung function

International Nuclear Information System (INIS)

Teshima, Takeo; Isawa, Toyoharu; Hirano, Tomio; Ebina, Akio; Shiraishi, Koichiro; Konno, Kiyoshi

1985-01-01

The unevenness or inhomogeneity of aerosol deposition patterns on radioaerosol inhalation lung images has been interpreted rather qualitatively in the clinical practice. We have reported our approach to quantitatively analyze the radioactive count distribution on radioaerosol inhalation lung images in relation to the actual lung function data. We have defined multiple indexes to express the shape and the unevenness of the count distribution of the lung images. To reduce as much as possible the number of indexes to be used in the regression functions, the method of selection of variables was introduced to the multiple regression analysis. Because some variables showed greater coefficients of simple correlation, while others did not, multicollinearity of variables had to be taken into consideration. For this reason, we chose a principal components regression analysis. The multiple regression function for each item of pulmonary function data thus established from analysis of 67 subjects appeared usable as a predictor of the actual lung function: for example, % VC (vital capacity) could be estimated by using four indexes out of the multiple ones with a coefficient of multiple correlation (R) of 0.753, and FEVsub(1.0) % (forced expiratory volume in one second divided by forced expiratory volume), by 7 indexes with R = 0.921. Pulmonary function data regarding lung volumes and lung mechanics were estimated more accurately with greater R's than those for lung diffusion, but even in the latter the prediction was still statistically significant at p less than 0.01. We believe the multiple regression functions thus obtained are useful for estimating not only the overall but also the regional function of the lungs. (author)

Retinal Imaging and Image Analysis

Science.gov (United States)

Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

2011-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

Knowledge-based analysis and understanding of 3D medical images

International Nuclear Information System (INIS)

Dhawan, A.P.; Juvvadi, S.

1988-01-01

The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. The authors objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

Science.gov (United States)

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

Adaptive Analysis of Functional MRI Data

International Nuclear Information System (INIS)

Friman, Ola

2003-01-01

Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

Functional imaging of the pancreas. Image processing techniques and clinical evaluation

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Fumiko

1984-02-01

An image processing technique for functional imaging of the pancreas was developed and is here reported. In this paper, clinical efficacy of the technique for detecting pancreatic abnormality is evaluated in comparison with conventional pancreatic scintigraphy and CT. For quantitative evaluation, functional rate, i.e. the rate of normal functioning pancreatic area, was calculated from the functional image and subtraction image. Two hundred and ninety-five cases were studied using this technique. Conventional image had a sensitivity of 65% and a specificity of 78%, while the use of functional imaging improved sensitivity to 88% and specificity to 88%. The mean functional rate in patients with pancreatic disease was significantly lower (33.3 +- 24.5 in patients with chronic pancreatitis, 28.1 +- 26.9 in patients with acute pancreatitis, 43.4 +- 22.3 in patients with diabetes mellitus, 20.4 +- 23.4 in patients with pancreatic cancer) than the mean functional rate in cases without pancreatic disease (86.4 +- 14.2). It is suggested that functional image of the pancreas reflecting pancreatic exocrine function and functional rate is a useful indicator of pancreatic exocrine function.

Fourier analysis: from cloaking to imaging

Science.gov (United States)

Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping

2016-04-01

Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

Physiology for the pulmonary functional imager

Energy Technology Data Exchange (ETDEWEB)

Levin, David L., E-mail: levin.david@mayo.edu [Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 (United States); Schiebler, Mark L. [Department of Radiology, UW-Madison School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252 (United States); Hopkins, Susan R., E-mail: shopkins@ucsd.edu [Division of Physiology 0623A, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093 (United States)

2017-01-15

Highlights: • An understanding of the relevant pulmonary physiology is crucial to functional lung imaging. • Spatial resolution for pulmonary functional imaging can be substantially less than that used for anatomic/clinical imaging. • Regional deformation of the lung under the influence of gravity significantly affects the measurement of pulmonary perfusion. • Large vessels identified on perfusion imaging do not represent local blood flow. • Pulmonary diseases are typically characterized by a change in the matching of ventilation and perfusion. - Abstract: As pulmonary functional imaging moves beyond the realm of the radiologist and physicist, it is important that imagers have a common language and understanding of the relevant physiology of the lung. This review will focus on key physiological concepts and pitfalls relevant to functional lung imaging.

Physiology for the pulmonary functional imager

International Nuclear Information System (INIS)

Levin, David L.; Schiebler, Mark L.; Hopkins, Susan R.

2017-01-01

Highlights: • An understanding of the relevant pulmonary physiology is crucial to functional lung imaging. • Spatial resolution for pulmonary functional imaging can be substantially less than that used for anatomic/clinical imaging. • Regional deformation of the lung under the influence of gravity significantly affects the measurement of pulmonary perfusion. • Large vessels identified on perfusion imaging do not represent local blood flow. • Pulmonary diseases are typically characterized by a change in the matching of ventilation and perfusion. - Abstract: As pulmonary functional imaging moves beyond the realm of the radiologist and physicist, it is important that imagers have a common language and understanding of the relevant physiology of the lung. This review will focus on key physiological concepts and pitfalls relevant to functional lung imaging.

Energy functionals for medical image segmentation: choices and consequences

OpenAIRE

McIntosh, Christopher

2011-01-01

Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis. Though there exists numerous approaches for medical image segmentation, one in particular has gained increasing popularity: energy minimization-based techniques, and the large set of methods encompassed therein. With these techniques an energy function must be chosen, segmentations...

PET imaging for brain function

International Nuclear Information System (INIS)

Fukuda, Hiroshi

2003-01-01

Described are the principle of PET and its characteristics, imaging of human brain function, mapping of detailed human cerebral functions and PET imaging of nerve transmission. Following compounds labeled by positron emitters are used for PET imaging of brain functions: for blood flow and oxygen metabolism, 15 O-O 2 gas, water and carbon dioxide; for energy metabolism, 18 F-fluorodeoxyglucose; and for nerve transmission functions in receptor binding, transporter, transmitter synthesis and enzyme, 11 C- or 18 F-dopamine, serotonin and their analogues, and acetylcholine analogues. For brain mapping, examples of cognition tasks, results and their statistics are presented with images for blood flow. Nerve transmissions in schizophrenia and Alzheimer disease are imaged with labeled analogues of dopamine and acetylcholine, respectively. PET is becoming more and more important in the field of psychiatric science particularly in the coming society of increasing aged people. (N.I.)

Image analysis in x-ray cinefluorography

Energy Technology Data Exchange (ETDEWEB)

Ikuse, J; Yasuhara, H; Sugimoto, H [Toshiba Corp., Kawasaki, Kanagawa (Japan)

1979-02-01

For the cinefluorographic image in the cardiovascular diagnostic system, the image quality is evaluated by means of MTF (Modulation Transfer Function), and object contrast by introducing the concept of x-ray spectrum analysis. On the basis of these results, further investigation is made of optimum X-ray exposure factors set for cinefluorography and the cardiovascular diagnostic system.

Fourier analysis: from cloaking to imaging

International Nuclear Information System (INIS)

Wu, Kedi; Ping Wang, Guo; Cheng, Qiluan

2016-01-01

Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers. (review)

Methods for modeling and quantification in functional imaging by positron emissions tomography and magnetic resonance imaging

International Nuclear Information System (INIS)

Costes, Nicolas

2017-01-01

This report presents experiences and researches in the field of in vivo medical imaging by positron emission tomography (PET) and magnetic resonance imaging (MRI). In particular, advances in terms of reconstruction, quantification and modeling in PET are described. The validation of processing and analysis methods is supported by the creation of data by simulation of the imaging process in PET. The recent advances of combined PET/MRI clinical cameras, allowing simultaneous acquisition of molecular/metabolic PET information, and functional/structural MRI information opens the door to unique methodological innovations, exploiting spatial alignment and simultaneity of the PET and MRI signals. It will lead to an increase in accuracy and sensitivity in the measurement of biological phenomena. In this context, the developed projects address new methodological issues related to quantification, and to the respective contributions of MRI or PET information for a reciprocal improvement of the signals of the two modalities. They open perspectives for combined analysis of the two imaging techniques, allowing optimal use of synchronous, anatomical, molecular and functional information for brain imaging. These innovative concepts, as well as data correction and analysis methods, will be easily translated into other areas of investigation using combined PET/MRI. (author) [fr

Connotation and category of functional-molecular imaging

International Nuclear Information System (INIS)

Li Tianran; Tian Jiahe

2007-01-01

Function and molecular lmaging represent medical imaging' s direction. The review article introduce function and molecular's concept and category and its characteristic. Comparing with traditionary classics radiology, function and molecular imaging have many features, such as micro-mount and specificity and quantitative. There are many technology about function and molecular imaging. Function and molecular imaging is important ingredient of modern medical and play a considerable role. (authors)

Directionality analysis on functional magnetic resonance imaging during motor task using Granger causality.

Science.gov (United States)

Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Deuschl, G; Raethjen, J; Heute, U; Muthuraman, M

2012-01-01

Directionality analysis of signals originating from different parts of brain during motor tasks has gained a lot of interest. Since brain activity can be recorded over time, methods of time series analysis can be applied to medical time series as well. Granger Causality is a method to find a causal relationship between time series. Such causality can be referred to as a directional connection and is not necessarily bidirectional. The aim of this study is to differentiate between different motor tasks on the basis of activation maps and also to understand the nature of connections present between different parts of the brain. In this paper, three different motor tasks (finger tapping, simple finger sequencing, and complex finger sequencing) are analyzed. Time series for each task were extracted from functional magnetic resonance imaging (fMRI) data, which have a very good spatial resolution and can look into the sub-cortical regions of the brain. Activation maps based on fMRI images show that, in case of complex finger sequencing, most parts of the brain are active, unlike finger tapping during which only limited regions show activity. Directionality analysis on time series extracted from contralateral motor cortex (CMC), supplementary motor area (SMA), and cerebellum (CER) show bidirectional connections between these parts of the brain. In case of simple finger sequencing and complex finger sequencing, the strongest connections originate from SMA and CMC, while connections originating from CER in either direction are the weakest ones in magnitude during all paradigms.

Pre-clinical functional magnetic resonance imaging. Pt. II. The heart

Energy Technology Data Exchange (ETDEWEB)

Messner, Nadja M.; Zoellner, Frank G.; Kalayciyan, Raffi; Schad, Lothar R. [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine

2014-07-01

One third of all deaths worldwide in 2008 were caused by cardiovascular diseases (CVD), and the incidence of CVD related deaths rises ever more. Thus, improved imaging techniques and modalities are needed for the evaluation of cardiac morphology and function. Cardiac magnetic resonance imaging (CMRI) is a minimally invasive technique that is increasingly important due to its high spatial and temporal resolution, its high soft tissue contrast and its ability of functional and quantitative imaging. It is widely accepted as the gold standard of cardiac functional analysis. In the short period of small animal MRI, remarkable progress has been achieved concerning new, fast imaging schemes as well as purpose-built equipment. Dedicated small animal scanners allow for tapping the full potential of recently developed animal models of cardiac disease. In this paper, we review state-of-the-art cardiac magnetic resonance imaging techniques and applications in small animals at ultra-high fields (UHF).

Image analysis

International Nuclear Information System (INIS)

Berman, M.; Bischof, L.M.; Breen, E.J.; Peden, G.M.

1994-01-01

This paper provides an overview of modern image analysis techniques pertinent to materials science. The usual approach in image analysis contains two basic steps: first, the image is segmented into its constituent components (e.g. individual grains), and second, measurement and quantitative analysis are performed. Usually, the segmentation part of the process is the harder of the two. Consequently, much of the paper concentrates on this aspect, reviewing both fundamental segmentation tools (commonly found in commercial image analysis packages) and more advanced segmentation tools. There is also a review of the most widely used quantitative analysis methods for measuring the size, shape and spatial arrangements of objects. Many of the segmentation and analysis methods are demonstrated using complex real-world examples. Finally, there is a discussion of hardware and software issues. 42 refs., 17 figs

Brain imaging and brain function

International Nuclear Information System (INIS)

Sokoloff, L.

1985-01-01

This book is a survey of the applications of imaging studies of regional cerebral blood flow and metabolism to the investigation of neurological and psychiatric disorders. Contributors review imaging techniques and strategies for measuring regional cerebral blood flow and metabolism, for mapping functional neural systems, and for imaging normal brain functions. They then examine the applications of brain imaging techniques to the study of such neurological and psychiatric disorders as: cerebral ischemia; convulsive disorders; cerebral tumors; Huntington's disease; Alzheimer's disease; depression and other mood disorders. A state-of-the-art report on magnetic resonance imaging of the brain and central nervous system rounds out the book's coverage

Quantum computation and analysis of Wigner and Husimi functions: toward a quantum image treatment.

Science.gov (United States)

Terraneo, M; Georgeot, B; Shepelyansky, D L

2005-06-01

We study the efficiency of quantum algorithms which aim at obtaining phase-space distribution functions of quantum systems. Wigner and Husimi functions are considered. Different quantum algorithms are envisioned to build these functions, and compared with the classical computation. Different procedures to extract more efficiently information from the final wave function of these algorithms are studied, including coarse-grained measurements, amplitude amplification, and measure of wavelet-transformed wave function. The algorithms are analyzed and numerically tested on a complex quantum system showing different behavior depending on parameters: namely, the kicked rotator. The results for the Wigner function show in particular that the use of the quantum wavelet transform gives a polynomial gain over classical computation. For the Husimi distribution, the gain is much larger than for the Wigner function and is larger with the help of amplitude amplification and wavelet transforms. We discuss the generalization of these results to the simulation of other quantum systems. We also apply the same set of techniques to the analysis of real images. The results show that the use of the quantum wavelet transform allows one to lower dramatically the number of measurements needed, but at the cost of a large loss of information.

Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

Directory of Open Access Journals (Sweden)

Andre Santos Ribeiro

2015-07-01

Full Text Available Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity.Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI and positron emission tomography (PET. It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also.Results. It was observed both a high inter

Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

Directory of Open Access Journals (Sweden)

Kiuru Aaro

2003-01-01

Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

Functional connectivity of the rodent brain using optical imaging

Science.gov (United States)

Guevara Codina, Edgar

The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis

Malware analysis using visualized image matrices.

Science.gov (United States)

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Malware Analysis Using Visualized Image Matrices

Directory of Open Access Journals (Sweden)

KyoungSoo Han

2014-01-01

Full Text Available This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

Science.gov (United States)

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Trial of quantitative analysis of cardiac function by 3D reconstruction of multislice cine MR images

International Nuclear Information System (INIS)

Yamamoto, Hideki; Sei, Tetsurou; Nakagawa, Tomio; Hiraki, Yoshio.

1994-01-01

Non-invasive techniques for measuring the dynamic behavior of the left ventricle (LV) can be invaluable tool in the diagnosis of the heart disease. In this paper we present methods for quantitative analysis of cardiac function using a compact magnetic resonance image processing system. A 256 x 256 magnetic resonance transaxial image of the left ventricle in a normal case is obtained. After gray level thresholding and region segmentation, the boundary of the left ventricular chamber is extracted. Then, the boundaries of the left ventricular chamber are displayed three-dimensionally by using the Z-buffer algorithm. Thus, LV volume and ejection fraction are calculated. Here, the value of LV ejection fraction is 60%. These results agree reasonably well with the corresponding data obtained by the echocardiography. (author)

Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling

International Nuclear Information System (INIS)

Liehn, J.C.; Hannequin, P.; Valeyre, J.

1989-01-01

This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr

Functional Imaging and Migraine: New Connections?

Science.gov (United States)

Schwedt, Todd J.; Chong, Catherine D.

2015-01-01

Purpose of Review Over the last several years, a growing number of brain functional imaging studies have provided insights into mechanisms underlying migraine. This manuscript reviews the recent migraine functional neuroimaging literature and provides recommendations for future studies that will help fill knowledge gaps. Recent Findings Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have identified brain regions that might be responsible for mediating the onset of a migraine attack and those associated with migraine symptoms. Enhanced activation of brain regions that facilitate processing of sensory stimuli suggests a mechanism by which migraineurs are hypersensitive to visual, olfactory, and cutaneous stimuli. Resting state functional connectivity MRI studies have identified numerous brain regions and functional networks with atypical functional connectivity in migraineurs, suggesting that migraine is associated with aberrant brain functional organization. Summary fMRI and PET studies that have identified brain regions and brain networks that are atypical in migraine have helped to describe the neurofunctional basis for migraine symptoms. Future studies should compare functional imaging findings in migraine to other headache and pain disorders and should explore the utility of functional imaging data as biomarkers for diagnostic and treatment purposes. PMID:25887764

An application of image processing techniques in computed tomography image analysis

DEFF Research Database (Denmark)

McEvoy, Fintan

2007-01-01

number of animals and image slices, automation of the process was desirable. The open-source and free image analysis program ImageJ was used. A macro procedure was created that provided the required functionality. The macro performs a number of basic image processing procedures. These include an initial...... process designed to remove the scanning table from the image and to center the animal in the image. This is followed by placement of a vertical line segment from the mid point of the upper border of the image to the image center. Measurements are made between automatically detected outer and inner...... boundaries of subcutaneous adipose tissue along this line segment. This process was repeated as the image was rotated (with the line position remaining unchanged) so that measurements around the complete circumference were obtained. Additionally, an image was created showing all detected boundary points so...

Pulmonary functional MR imaging for COPD

International Nuclear Information System (INIS)

Ohno, Yoshiharu

2008-01-01

Chronic obstructive pulmonary disease (COPD) is a slowly progressive disease characterized by airflow limitation, cough, sputum production, and, at later stages, dyspnea. COPD is currently the fourth-leading cause of mortality and the twelfth-leading cause of disability, and by the year 2020 it is expected to be the third-leading cause of death and the fifth-leading cause of disability worldwide. The diagnosis of COPD largely relies on a history of exposure to noxious stimuli and abnormal lung function test results. Since the pathology of COPD varies and the molecular mechanisms are only slightly understood, the diagnosis and stage assessment of COPD have relied on the results of pulmonary function test. In addition, CT and nuclear medicine study are utilized for assessment of regional morphological and functional abnormalities. Recently, pulmonary functional MR imaging is suggested as a new technique for assessment of regional physiopathologic information in various pulmonary diseases including COPD, pulmonary thromboembolism, lung cancer and interstitial lung diseases. This review article covers the brief description of theory and clinical application of contrast-enhanced perfusion MR imaging; hyperpolarized noble gas MR imaging and oxygen-enhanced MR imaging in COPD subjects. We believe that further basic studies as well as clinical applications of this new technique will define the real significance of pulmonary functional MR imaging for the future of pulmonary functional imaging and its usefulness for diagnosis and patients' management in COPD. (author)

Presurgical functional magnetic resonance imaging

International Nuclear Information System (INIS)

Stippich, C.

2010-01-01

Functional magnetic resonance imaging (fMRI) is an important and novel neuroimaging modality for patients with brain tumors. By non-invasive measurement, localization and lateralization of brain activiation, most importantly of motor and speech function, fMRI facilitates the selection of the most appropriate and sparing treatment and function-preserving surgery. Prerequisites for the diagnostic use of fMRI are the application of dedicated clinical imaging protocols and standardization of the respective imaging procedures. The combination with diffusion tensor imaging (DTI) also enables tracking and visualization of important fiber bundles such as the pyramidal tract and the arcuate fascicle. These multimodal MR data can be implemented in computer systems for functional neuronavigation or radiation treatment. The practicability, accuracy and reliability of presurgical fMRI have been validated by large numbers of published data. However, fMRI cannot be considered as a fully established modality of diagnostic neuroimaging due to the lack of guidelines of the responsible medical associations as well as the lack of medical certification of important hardware and software components. This article reviews the current research in the field and provides practical information relevant for presurgical fMRI. (orig.) [de

Digital image analysis of NDT radiographs

International Nuclear Information System (INIS)

Graeme, W.A. Jr.; Eizember, A.C.; Douglass, J.

1989-01-01

Prior to the introduction of Charge Coupled Device (CCD) detectors the majority of image analysis performed on NDT radiographic images was done visually in the analog domain. While some film digitization was being performed, the process was often unable to capture all the usable information on the radiograph or was too time consuming. CCD technology now provides a method to digitize radiographic film images without losing the useful information captured in the original radiograph in a timely process. Incorporating that technology into a complete digital radiographic workstation allows analog radiographic information to be processed, providing additional information to the radiographer. Once in the digital domain, that data can be stored, and fused with radioscopic and other forms of digital data. The result is more productive analysis and management of radiographic inspection data. The principal function of the NDT Scan IV digital radiography system is the digitization, enhancement and storage of radiographic images

Functional imaging - a new tool for X-ray functional diagnostics

International Nuclear Information System (INIS)

Boehm, M.; Erbe, W.; Sonne, B.; Hoehne, K.H.; Nicolae, G.C.; Pfeiffer, G.

1978-05-01

The method of functional imaging is applied to X-ray angiograms. Functional images are generated by inserting at each point of an X-ray image a computed grey value proportional to a dynamic parameter (such as blood velocity) instead of the recorded X-ray absorption value. For this purpose a new system for angiographic image processing has been developed. First results show that the method is a tool to extract more information about the blood dynamics in organs in an easier and faster way than with the conventional angiographic technique. (orig.)

[Functional magnetic resonance imaging in psychiatry and psychotherapy].

Science.gov (United States)

Derntl, B; Habel, U; Schneider, F

2010-01-01

technical improvements, functional magnetic resonance imaging (fMRI) has become the most popular and versatile imaging method in psychiatric research. The scope of this manuscript is to briefly introduce the basics of MR physics, the blood oxygenation level-dependent (BOLD) contrast as well as the principles of MR study design and functional data analysis. The presentation of exemplary studies on emotion recognition and empathy in schizophrenia patients will highlight the importance of MR methods in psychiatry. Finally, we will demonstrate insights into new developments that will further boost MR techniques in clinical research and will help to gain more insight into dysfunctional neural networks underlying cognitive and emotional deficits in psychiatric patients. Moreover, some techniques such as neurofeedback seem promising for evaluation of therapy effects on a behavioral and neural level.

Design and validation of Segment - freely available software for cardiovascular image analysis

International Nuclear Information System (INIS)

Heiberg, Einar; Sjögren, Jane; Ugander, Martin; Carlsson, Marcus; Engblom, Henrik; Arheden, Håkan

2010-01-01

Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page (http://segment.heiberg.se). Segment

Joint analysis of three-dimensional anatomical and functional data considering the cerebral post mortem imaging in rodents

International Nuclear Information System (INIS)

Dubois, Albertine

2008-01-01

The recent development of dedicated small animal anatomical (MRI) and functional (micro-PET) scanners has opened up the possibility of performing repeated functional in vivo studies in the same animal as the longitudinal follow-up of cerebral glucose metabolism. However, these systems still suffer technical limitations including a limited sensitivity and a reduced spatial resolution. Hence, autoradiography and histological studies remain the reference and widely used techniques for biological studies in small animals. The major disadvantage of these post mortem imaging techniques is that they require brain tissue sectioning, entailing the production of large numbers (up to several hundreds) of serial sections and the inherent loss of three-dimensional (3D) spatial consistency. The first step towards improving the analysis of this post mortem information was the development of reliable, automated procedures for the 3D reconstruction of the whole brain sections. We first developed an optimized data acquisition from large numbers of post mortem data (2D sections and block-face photographs). Then, we proposed different strategies of 3D reconstruction of the corresponding volumes. We also addressed the histological to autoradiographic sections and to block-face photographs co-registration problem (the photographic volume is intrinsically spatially consistent). These developments were essential for the 3D reconstruction but also enabled the evaluation of different methods of functional data analysis, from the most straightforward (manual delineation of regions of interest) to the most automated (Statistical Parametric Mapping-like approaches for group analysis). Two biological applications were carried out: visual stimulation in rats and cerebral metabolism in a transgenic mouse model of Alzheimer's disease. One perspective of this work is to match reconstructed post mortem data with in vivo images of the same animal. (author) [fr

An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

Science.gov (United States)

Kim, Yongmin; Alexander, Thomas

1986-06-01

In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

Multidisciplinary Functional MR Imaging for Prostate Cancer

International Nuclear Information System (INIS)

Kim, Jeong Kon; Jang, Yun Jin; Cho, Gyung Goo

2009-01-01

Various functional magnetic resonance (MR) imaging techniques are used for evaluating prostate cancer including diffusion-weighted imaging, dynamic contrast- enhanced MR imaging, and MR spectroscopy. These techniques provide unique information that is helpful to differentiate prostate cancer from non-cancerous tissue and have been proven to improve the diagnostic performance of MRI not only for cancer detection, but also for staging, post-treatment monitoring, and guiding prostate biopsies. However, each functional MR imaging technique also has inherent challenges. Therefore, in order to make accurate diagnoses, it is important to comprehensively understand their advantages and limitations, histologic background related with image findings, and their clinical relevance for evaluating prostate cancer. This article will review the basic principles and clinical significance of functional MR imaging for evaluating prostate cancer

Ultrasonic image analysis and image-guided interventions.

Science.gov (United States)

Noble, J Alison; Navab, Nassir; Becher, H

2011-08-06

The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

Advantages in functional imaging of the brain.

Science.gov (United States)

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

Automatic extraction analysis of the anatomical functional area for normal brain 18F-FDG PET imaging

International Nuclear Information System (INIS)

Guo Wanhua; Jiang Xufeng; Zhang Liying; Lu Zhongwei; Li Peiyong; Zhu Chengmo; Zhang Jiange; Pan Jiapu

2003-01-01

Using self-designed automatic extraction software of brain functional area, the grey scale distribution of 18 F-FDG imaging and the relationship between the 18 F-FDG accumulation of brain anatomic function area and the 18 F-FDG injected dose, the level of glucose, the age, etc., were studied. According to the Talairach coordinate system, after rotation, drift and plastic deformation, the 18 F-FDG PET imaging was registered into the Talairach coordinate atlas, and then the average gray value scale ratios between individual brain anatomic functional area and whole brain area was calculated. Further more the statistics of the relationship between the 18 F-FDG accumulation of every brain anatomic function area and the 18 F-FDG injected dose, the level of glucose and the age were tested by using multiple stepwise regression model. After images' registration, smoothing and extraction, main cerebral cortex of the 18 F-FDG PET brain imaging can be successfully localized and extracted, such as frontal lobe, parietal lobe, occipital lobe, temporal lobe, cerebellum, brain ventricle, thalamus and hippocampus. The average ratios to the inner reference of every brain anatomic functional area were 1.01 ± 0.15. By multiple stepwise regression with the exception of thalamus and hippocampus, the grey scale of all the brain functional area was negatively correlated to the ages, but with no correlation to blood sugar and dose in all areas. To the 18 F-FDG PET imaging, the brain functional area extraction program could automatically delineate most of the cerebral cortical area, and also successfully reflect the brain blood and metabolic study, but extraction of the more detailed area needs further investigation

Body image disturbance in adults treated for cancer - a concept analysis.

Science.gov (United States)

Rhoten, Bethany A

2016-05-01

To report an analysis of the concept of body image disturbance in adults who have been treated for cancer as a phenomenon of interest to nurses. Although the concept of body image disturbance has been clearly defined in adolescents and adults with eating disorders, adults who have been treated for cancer may also experience body image disturbance. In this context, the concept of body image disturbance has not been clearly defined. Concept analysis. PubMed, Psychological Information Database and Cumulative Index of Nursing and Allied Health Literature were searched for publications from 1937 - 2015. Search terms included body image, cancer, body image disturbance, adult and concept analysis. Walker and Avant's 8-step method of concept analysis was used. The defining attributes of body image disturbance in adults who have been treated for cancer are: (1) self-perception of a change in appearance and displeasure with the change or perceived change in appearance; (2) decline in an area of function; and (3) psychological distress regarding changes in appearance and/or function. This concept analysis provides a foundation for the development of multidimensional assessment tools and interventions to alleviate body image disturbance in this population. A better understanding of body image disturbance in adults treated for cancer will assist nurses and other clinicians in identifying this phenomenon and nurse scientists in developing instruments that accurately measure this condition, along with interventions that will promote a better quality of life for survivors. © 2016 John Wiley & Sons Ltd.

Functional cardiac imaging: positron emission tomography

International Nuclear Information System (INIS)

Mullani, N.A.; Gould, K.L.

1984-01-01

Dynamic cardiovascular imaging plays a vital role in the diagnosis and treatment of cardiac disease by providing information about the function of the heart. During the past 30 years, cardiovascular imaging has evolved from the simple chest x-ray and fluoroscopy to such sophisticated techniques as invasive cardiac angiography and cinearteriography and, more recently, to noninvasive cardiac CT scanning, nuclear magnetic resonance, and positron emission tomography, which reflect more complex physiologic functions. As research tools, CT, NMR, and PET provide quantitative information on global as well as regional ventricular function, coronary artery stenosis, myocardial perfusion, glucose and fatty acid metabolism, or oxygen utilization, with little discomfort or risk to the patient. As imaging modalities become more sophisticated and more oriented toward clinical application, the prospect of routinely obtaining such functional information about the heart is becoming realistic. However, these advances are double-edged in that the interpretation of functional data is more complex than that of the anatomic imaging familiar to most physicians. They will require an enhanced understanding of the physiologic and biochemical processes, as well as of the instrumentation and techniques for analyzing the data. Of the new imaging modalities that provide functional information about the heart, PET is the most useful because it quantitates the regional distribution of radionuclides in vivo. Clinical applications, interpretation of data, and the impact of PET on our understanding of cardiac pathophysiology are discussed. 5 figures

Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

Science.gov (United States)

Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

2017-12-01

Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

Acquisition and analysis strategies in functional MRI at high fields

International Nuclear Information System (INIS)

Windischberger, C.

2001-08-01

Functional magnetic resonance imaging represents a non-invasive technique to examine neuronal activity in the brain. It applies radio waves to excite nuclear spins, using the emitted signal during relaxation for image generation. Signal modulations from local blood flow and oxygenation level changes caused by neuronal activity are the basis for calculating functional brain maps with high spatial resolution. The present work discusses concepts for improving the spatial and temporal resolution, as well as sophisticated analysis approaches. Besides an exhaustive description of image reconstruction algorithms, computational simulations on echo-shifting in echo-planar imaging are presented and effects on spatial resolution are quantified. The results demonstrate that echo-shifting causes only minimal resolution losses for high signal-to-noise data, but leads to severe resolution degradation (up to 30 %) in images with low signal-to-noise ratios. After an overview of the mechanisms that cause fMRI signal changes subsequent to neuronal activity, explorative analysis algorithms like Fuzzy Cluster Analysis, as well as parametric approaches are described and discussed. In the context of fMRI artifacts, effects of respiratory motion are examined. For the first time, well-defined breathing patterns are used to quantify the influences on fMRI signal intensity. Also, the variability of fMRI activation in a mental rotation paradigm are investigated, using single-trial analysis. Such, intra-subject activation consistency was determined successfully. Finally, in a second study on mental rotation explorative data analysis was applied to retrieve neuro-functional hypotheses. (author)

Theoretical analysis of radiographic images by nonstationary Poisson processes

International Nuclear Information System (INIS)

Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.

1980-01-01

This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process. (author)

Functional analysis in MR urography - made simple

Energy Technology Data Exchange (ETDEWEB)

Khrichenko, Dmitry; Darge, Kassa [Children' s Hospital of Philadelphia, Department of Radiology, Philadelphia, PA (United States)

2010-02-15

MR urography (MRU) has proved to be a most advantageous imaging modality of the urinary tract in children, providing one-stop comprehensive morphological and functional information, without the utilization of ionizing radiation. The functional analysis of the MRU scan still requires external post-processing using relatively complex software. This has proved to be a limiting factor in widespread routine implementation of MRU functional analysis and use of MRU functional parameters similar to nuclear medicine. We present software, developed in a pediatric radiology department, that not only enables comprehensive automated functional analysis, but is also very user-friendly, fast, easily operated by the average radiologist or MR technician and freely downloadable Virtual Machine is required for the installation, which is obtained at no charge. The analysis software, known as ''CHOP-fMRU,'' has the potential to help overcome the obstacles to widespread use of functional MRU in children. (orig.)

Integration of structural and functional magnetic resonance imaging in amyotrophic lateral sclerosis.

Science.gov (United States)

Douaud, Gwenaëlle; Filippini, Nicola; Knight, Steven; Talbot, Kevin; Turner, Martin R

2011-12-01

Amyotrophic lateral sclerosis as a system failure is a concept supported by the finding of consistent extramotor as well as motor cerebral pathology. The functional correlates of the structural changes detected using advanced magnetic resonance imaging techniques such as diffusion tensor imaging and voxel-based morphometry have not been extensively studied. A group of 25 patients with amyotrophic lateral sclerosis was compared to healthy control subjects using a multi-modal neuroimaging approach comprising T(1)-weighted, diffusion-weighted and resting-state functional magnetic resonance imaging. Using probabilistic tractography, a grey matter connection network was defined based upon the prominent corticospinal tract and corpus callosum involvement demonstrated by white matter tract-based spatial statistics. This 'amyotrophic lateral sclerosis-specific' network included motor, premotor and supplementary motor cortices, pars opercularis and motor-related thalamic nuclei. A novel analysis protocol, using this disease-specific grey matter network as an input for a dual-regression analysis, was then used to assess changes in functional connectivity directly associated with this network. A spatial pattern of increased functional connectivity spanning sensorimotor, premotor, prefrontal and thalamic regions was found. A composite of structural and functional magnetic resonance imaging measures also allowed the qualitative discrimination of patients from controls. An integrated structural and functional connectivity approach therefore identified apparently dichotomous processes characterizing the amyotrophic lateral sclerosis cerebral network failure, in which there was increased functional connectivity within regions of decreased structural connectivity. Patients with slower rates of disease progression showed connectivity measures with values closer to healthy controls, raising the possibility that functional connectivity increases might not simply represent a

A functional magnetic resonance imaging study

Indian Academy of Sciences (India)

MADU

systems and ultra fast imaging techniques, such as echo planar imaging (EPI ) ... is used to understand brain organization, assessing of neurological status, and ..... J C 1998 Functional MRI studies of motor recovery after stroke;. NeuroImage 7 ...

Development of Image Analysis Software of MAXI

Science.gov (United States)

Eguchi, S.; Ueda, Y.; Hiroi, K.; Isobe, N.; Sugizaki, M.; Suzuki, M.; Tomida, H.; Maxi Team

2010-12-01

Monitor of All-sky X-ray Image (MAXI) is an X-ray all-sky monitor, attached to the Japanese experiment module Kibo on the International Space Station. The main scientific goals of the MAXI mission include the discovery of X-ray novae followed by prompt alerts to the community (Negoro et al., in this conference), and production of X-ray all-sky maps and new source catalogs with unprecedented sensitivities. To extract the best capabilities of the MAXI mission, we are working on the development of detailed image analysis tools. We utilize maximum likelihood fitting to a projected sky image, where we take account of the complicated detector responses, such as the background and point spread functions (PSFs). The modeling of PSFs, which strongly depend on the orbit and attitude of MAXI, is a key element in the image analysis. In this paper, we present the status of our software development.

Estimation of physiological parameters using knowledge-based factor analysis of dynamic nuclear medicine image sequences

International Nuclear Information System (INIS)

Yap, J.T.; Chen, C.T.; Cooper, M.

1995-01-01

The authors have previously developed a knowledge-based method of factor analysis to analyze dynamic nuclear medicine image sequences. In this paper, the authors analyze dynamic PET cerebral glucose metabolism and neuroreceptor binding studies. These methods have shown the ability to reduce the dimensionality of the data, enhance the image quality of the sequence, and generate meaningful functional images and their corresponding physiological time functions. The new information produced by the factor analysis has now been used to improve the estimation of various physiological parameters. A principal component analysis (PCA) is first performed to identify statistically significant temporal variations and remove the uncorrelated variations (noise) due to Poisson counting statistics. The statistically significant principal components are then used to reconstruct a noise-reduced image sequence as well as provide an initial solution for the factor analysis. Prior knowledge such as the compartmental models or the requirement of positivity and simple structure can be used to constrain the analysis. These constraints are used to rotate the factors to the most physically and physiologically realistic solution. The final result is a small number of time functions (factors) representing the underlying physiological processes and their associated weighting images representing the spatial localization of these functions. Estimation of physiological parameters can then be performed using the noise-reduced image sequence generated from the statistically significant PCs and/or the final factor images and time functions. These results are compared to the parameter estimation using standard methods and the original raw image sequences. Graphical analysis was performed at the pixel level to generate comparable parametric images of the slope and intercept (influx constant and distribution volume)

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

Science.gov (United States)

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Image formation and image analysis in electron microscopy

International Nuclear Information System (INIS)

Heel, M. van.

1981-01-01

This thesis covers various aspects of image formation and image analysis in electron microscopy. The imaging of relatively strong objects in partially coherent illumination, the coherence properties of thermionic emission sources and the detection of objects in quantum noise limited images are considered. IMAGIC, a fast, flexible and friendly image analysis software package is described. Intelligent averaging of molecular images is discussed. (C.F.)

A NEW TOOL FOR IMAGE ANALYSIS BASED ON CHEBYSHEV RATIONAL FUNCTIONS: CHEF FUNCTIONS

International Nuclear Information System (INIS)

Jiménez-Teja, Y.; Benítez, N.

2012-01-01

We introduce a new approach to the modeling of the light distribution of galaxies, an orthonormal polar basis formed by a combination of Chebyshev rational functions and Fourier polynomials that we call CHEF functions, or CHEFs. We have developed an orthonormalization process to apply this basis to pixelized images, and implemented the method as a Python pipeline. The new basis displays remarkable flexibility, being able to accurately fit all kinds of galaxy shapes, including irregulars, spirals, ellipticals, highly compact, and highly elongated galaxies. It does this while using fewer components than similar methods, as shapelets, and without producing artifacts, due to the efficiency of the rational Chebyshev polynomials to fit quickly decaying functions like galaxy profiles. The method is linear and very stable, and therefore is capable of processing large numbers of galaxies in a fast and automated way. Due to the high quality of the fits in the central parts of the galaxies, and the efficiency of the CHEF basis modeling galaxy profiles up to very large distances, the method provides highly accurate estimates of total galaxy fluxes and ellipticities. Future papers will explore in more detail the application of the method to perform multiband photometry, morphological classification, and weak shear measurements.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

Science.gov (United States)

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

IQM: an extensible and portable open source application for image and signal analysis in Java.

Science.gov (United States)

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

Science.gov (United States)

Driscoll, Brandon; Jaffray, David; Coolens, Catherine

2014-03-01

Purpose: To provide clinicians & researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

International Nuclear Information System (INIS)

Driscoll, Brandon; Jaffray, David; Coolens, Catherine

2014-01-01

Purpose: To provide clinicians and researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

Functional and perfusion magnetic resonance imaging at 3 tesla

International Nuclear Information System (INIS)

Klarhoefer, M.

2001-03-01

This thesis deals with the development and optimization of fast magnetic resonance imaging (MRI) methods for non-invasive functional studies of the human brain and perfusion imaging on a 3 Tesla (T) whole body NMR system. The functional MRI (fMRI) experiments performed showed that single-shot multi-echo EPI and spiral imaging techniques provide fast tools to obtain information about T2* distributions during functional activation in the human brain. Both sequences were found to be useful in the separation of different sources contributing to the functional MR signal like inflow or susceptibility effects in the various vascular environments. An fMRI study dealing with the involvement of prefrontal brain regions in movement preparation lead to inconsistent results. It could not be clarified if these were caused by problems during a spatial normalization process of the individual brains or if the functional paradigm, using very short inter-stimulus intervals, was not suited for the problem investigated. Blood flow velocity measurements in the human finger showed that the use of a strong, small-bore gradient system permits short echo times that reduce flow artefacts and allows high spatial resolution in order to keep systematic errors due to partial volume effects small. With regard to the perfusion investigations an inversion recovery snapshot-FLASH sequence was implemented, which allowed the acquisition of T1 parameter maps of the human brain within a few seconds. The accuracy of this method was demonstrated in test objects. The perfusion investigations with FAIR showed good qualitative results, whereas the quantitative analysis did not yield reproducible findings. A reason for the poor results could be the low signal-to-noise ratio (SNR) of the FAIR images or an incomplete global inversion of the magnetization due to the transmission characteristics of the radio-frequency coil. The BASE sequence that did not require a global inversion yielded quantitative perfusion

OpenComet: An automated tool for comet assay image analysis

Directory of Open Access Journals (Sweden)

Benjamin M. Gyori

2014-01-01

Full Text Available Reactive species such as free radicals are constantly generated in vivo and DNA is the most important target of oxidative stress. Oxidative DNA damage is used as a predictive biomarker to monitor the risk of development of many diseases. The comet assay is widely used for measuring oxidative DNA damage at a single cell level. The analysis of comet assay output images, however, poses considerable challenges. Commercial software is costly and restrictive, while free software generally requires laborious manual tagging of cells. This paper presents OpenComet, an open-source software tool providing automated analysis of comet assay images. It uses a novel and robust method for finding comets based on geometric shape attributes and segmenting the comet heads through image intensity profile analysis. Due to automation, OpenComet is more accurate, less prone to human bias, and faster than manual analysis. A live analysis functionality also allows users to analyze images captured directly from a microscope. We have validated OpenComet on both alkaline and neutral comet assay images as well as sample images from existing software packages. Our results show that OpenComet achieves high accuracy with significantly reduced analysis time.

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

Science.gov (United States)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Spinal imaging and image analysis

CERN Document Server

Yao, Jianhua

2015-01-01

This book is instrumental to building a bridge between scientists and clinicians in the field of spine imaging by introducing state-of-the-art computational methods in the context of clinical applications.  Spine imaging via computed tomography, magnetic resonance imaging, and other radiologic imaging modalities, is essential for noninvasively visualizing and assessing spinal pathology. Computational methods support and enhance the physician’s ability to utilize these imaging techniques for diagnosis, non-invasive treatment, and intervention in clinical practice. Chapters cover a broad range of topics encompassing radiological imaging modalities, clinical imaging applications for common spine diseases, image processing, computer-aided diagnosis, quantitative analysis, data reconstruction and visualization, statistical modeling, image-guided spine intervention, and robotic surgery. This volume serves a broad audience as  contributions were written by both clinicians and researchers, which reflects the inte...

Physiological basis and image processing in functional magnetic resonance imaging: Neuronal and motor activity in brain

Directory of Open Access Journals (Sweden)

Sharma Rakesh

2004-05-01

Full Text Available Abstract Functional magnetic resonance imaging (fMRI is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities.

Image Analysis for X-ray Imaging of Food

DEFF Research Database (Denmark)

Einarsdottir, Hildur

for quality and safety evaluation of food products. In this effort the fields of statistics, image analysis and statistical learning are combined, to provide analytical tools for determining the aforementioned food traits. The work demonstrated includes a quantitative analysis of heat induced changes......X-ray imaging systems are increasingly used for quality and safety evaluation both within food science and production. They offer non-invasive and nondestructive penetration capabilities to image the inside of food. This thesis presents applications of a novel grating-based X-ray imaging technique...... and defect detection in food. Compared to the complex three dimensional analysis of microstructure, here two dimensional images are considered, making the method applicable for an industrial setting. The advantages obtained by grating-based imaging are compared to conventional X-ray imaging, for both foreign...

Brain atlas for functional imaging. Clinical and research applications

International Nuclear Information System (INIS)

Nowinski, W.L.; Thirunavuukarasuu, A.; Kennedy, D.N

2001-01-01

This CD-ROM: Allows anatomical and functional images to be loaded and registered. Enables interactive placement of the Talairach landmarks in 3D Space. Provides automatic data-to-atlas warping based on the Talairaich proportional gridsystem transformation. Real-time interactive warping for fine tuning is also available. Allows the user to place marks on the activation loci in the warped functional images, display these marks with the atlas, and edit them in three planes. Mark placement is assisted by image thresholding. Provides simultaneous display of the atlas, anatomical image and functional image within one interactively blended image. Atlas-data blending and anatomical-functional image blending are controlled independently. Labels the data by means of the atlas. The atlas can be flipped left/right so that Brodmann's areas and gyri can be labeled on both hemispheres. Provides additional functions such as friendly navigation, cross-referenced display, readout of the Talairach coordinates and intensities, load coordinates, save, on-line help. (orig.)

Brain atlas for functional imaging. Clinical and research applications

Energy Technology Data Exchange (ETDEWEB)

Nowinski, W.L.; Thirunavuukarasuu, A.; Kennedy, D.N

2001-07-01

This CD-ROM: Allows anatomical and functional images to be loaded and registered. Enables interactive placement of the Talairach landmarks in 3D Space. Provides automatic data-to-atlas warping based on the Talairaich proportional gridsystem transformation. Real-time interactive warping for fine tuning is also available. Allows the user to place marks on the activation loci in the warped functional images, display these marks with the atlas, and edit them in three planes. Mark placement is assisted by image thresholding. Provides simultaneous display of the atlas, anatomical image and functional image within one interactively blended image. Atlas-data blending and anatomical-functional image blending are controlled independently. Labels the data by means of the atlas. The atlas can be flipped left/right so that Brodmann's areas and gyri can be labeled on both hemispheres. Provides additional functions such as friendly navigation, cross-referenced display, readout of the Talairach coordinates and intensities, load coordinates, save, on-line help. (orig.)

Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

Science.gov (United States)

de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

2008-01-01

Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications.

The brain, a choice subject for radioisotopic functional imaging

International Nuclear Information System (INIS)

Maziere, B.

1996-01-01

Progresses realized in the use of radioisotopes and in tomographic imaging techniques have permitted to access to the visualization of the human body functions. The application of this radioisotopic functional imaging (or emission tomography functional imaging) has been particularly fruitful in the study of brain functioning. This method is the only exploratory method for the biochemical aspects of the cerebral functioning and is used both by the physiologist and the therapist. (J.S.)

An approach for quantitative image quality analysis for CT

Science.gov (United States)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Endoscopic device for functional imaging of the retina

Science.gov (United States)

Barriga, Simon; Lohani, Sweyta; Martell, Bret; Soliz, Peter; Ts'o, Dan

2011-03-01

Non-invasive imaging of retinal function based on the recording of spatially distributed reflectance changes evoked by visual stimuli has to-date been performed primarily using modified commercial fundus cameras. We have constructed a prototype retinal functional imager, using a commercial endoscope (Storz) for the frontend optics, and a low-cost back-end that includes the needed dichroic beam splitter to separate the stimulus path from the imaging path. This device has been tested to demonstrate its performance for the delivery of adequate near infrared (NIR) illumination, intensity of the visual stimulus and reflectance return in the imaging path. The current device was found to be capable of imaging reflectance changes of 0.1%, similar to that observable using the modified commercial fundus camera approach. The visual stimulus (a 505nm spot of 0.5secs) was used with an interrogation illumination of 780nm, and a sequence of imaged captured. At each pixel, the imaged signal was subtracted and normalized by the baseline reflectance, so that the measurement was ΔR/R. The typical retinal activity signal observed had a ΔR/R of 0.3-1.0%. The noise levels were measured when no stimulus was applied and found to vary between +/- 0.05%. Functional imaging has been suggested as a means to provide objective information on retina function that may be a preclinical indicator of ocular diseases, such as age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy. The endoscopic approach promises to yield a significantly more economical retinal functional imaging device that would be clinically important.

Functional mesoporous silica nanoparticles for bio-imaging applications.

Science.gov (United States)

Cha, Bong Geun; Kim, Jaeyun

2018-03-22

Biomedical investigations using mesoporous silica nanoparticles (MSNs) have received significant attention because of their unique properties including controllable mesoporous structure, high specific surface area, large pore volume, and tunable particle size. These unique features make MSNs suitable for simultaneous diagnosis and therapy with unique advantages to encapsulate and load a variety of therapeutic agents, deliver these agents to the desired location, and release the drugs in a controlled manner. Among various clinical areas, nanomaterials-based bio-imaging techniques have advanced rapidly with the development of diverse functional nanoparticles. Due to the unique features of MSNs, an imaging agent supported by MSNs can be a promising system for developing targeted bio-imaging contrast agents with high structural stability and enhanced functionality that enable imaging of various modalities. Here, we review the recent achievements on the development of functional MSNs for bio-imaging applications, including optical imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), ultrasound imaging, and multimodal imaging for early diagnosis. With further improvement in noninvasive bio-imaging techniques, the MSN-supported imaging agent systems are expected to contribute to clinical applications in the future. This article is categorized under: Diagnostic Tools > In vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology. © 2018 Wiley Periodicals, Inc.

FGWAS: Functional genome wide association analysis.

Science.gov (United States)

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Retinal imaging and image analysis

NARCIS (Netherlands)

Abramoff, M.D.; Garvin, Mona K.; Sonka, Milan

2010-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of

MR imaging of non-functioning endocrine tumors of the pancreas

International Nuclear Information System (INIS)

Irie, Hiroyuki; Honda, Hiroshi; Kuroiwa, Toshiro

2002-01-01

The purpose of this study was to clarify the MR imaging characteristics of patients with non-functioning endocrine tumors of the pancreas. Fourteen patients with these tumors underwent MR imaging. The signal characteristics of the tumor on T 1 -, T 2 -, and contrast-enhanced T 1 -weighted images were evaluated. The enhancement pattern of the tumor on dynamic study was also examined. The degree of stromal fibrosis was evaluated on the pathologic specimen, and was then classified as mild, moderate, or marked fibrosis. On T 1 -weighted images, the tumors were hypointense in 12 of 14 cases. The signals of the tumors on T 2 -weighted images were varied. The tumors were hypointense in 1 case, isointense in 2 cases, hyperintense in 6 cases, and very hyperintense in the other 5 cases. On contrast-enhanced T 1 -weighted images, the tumors were hyperintense in 8 cases and very hyperintense in 5 cases. On T 2 - and contrast-enhanced T 1 -weighted images, 4 of 5 malignant tumors were very hyperintense. Dynamic study revealed prolonged enhancement in 10 of 11 cases. Pathologic analysis revealed moderate or marked fibrosis in 10 of 14 cases, and prolonged enhancement was considered to be related stromal fibrosis. In conclusion, MR imaging findings of non-functioning endocrine tumors of the pancreas vary in relation to pathological variety. Prolonged enhancement of the tumor on dynamic study is considered to be one of the characteristic MR imaging findings that corresponds to stromal fibrosis of the tumor. (author)

Chronic kidney disease: Pathological and functional evaluation with intravoxel incoherent motion diffusion-weighted imaging.

Science.gov (United States)

Mao, Wei; Zhou, Jianjun; Zeng, Mengsu; Ding, Yuqin; Qu, Lijie; Chen, Caizhong; Ding, Xiaoqiang; Wang, Yaqiong; Fu, Caixia

2018-05-01

Because chronic kidney disease (CKD) is a worldwide problem, accurate pathological and functional evaluation is required for planning treatment and follow-up. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can assess both capillary perfusion and tissue diffusion and may be helpful in evaluating renal function and pathology. To evaluate functional and pathological alterations in CKD by applying IVIM-DWI. Prospective study. In all, 72 CKD patients who required renal biopsy and 20 healthy volunteers. 1.5T. All subjects underwent IVIM-DWI of the kidneys, and image analysis was performed by two radiologists. The mean values of true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were acquired from renal parenchyma. Correlation between IVIM-DWI parameters and estimated glomerular filtration rate (eGFR), as well as pathological damage, were assessed. One-way analysis of variance (ANOVA), paired sample t-test and Spearman correlation analysis. The paired sample t-test revealed that IVIM-DWI parameters were significantly lower in medulla than cortex for both patients and controls (P Imaging 2018;47:1251-1259. © 2017 International Society for Magnetic Resonance in Medicine.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

Science.gov (United States)

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

Correlation analysis between pulmonary function test parameters and CT image parameters of emphysema

Science.gov (United States)

Liu, Cheng-Pei; Li, Chia-Chen; Yu, Chong-Jen; Chang, Yeun-Chung; Wang, Cheng-Yi; Yu, Wen-Kuang; Chen, Chung-Ming

2016-03-01

Conventionally, diagnosis and severity classification of Chronic Obstructive Pulmonary Disease (COPD) are usually based on the pulmonary function tests (PFTs). To reduce the need of PFT for the diagnosis of COPD, this paper proposes a correlation model between the lung CT images and the crucial index of the PFT, FEV1/FVC, a severity index of COPD distinguishing a normal subject from a COPD patient. A new lung CT image index, Mirage Index (MI), has been developed to describe the severity of COPD primarily with emphysema disease. Unlike conventional Pixel Index (PI) which takes into account all voxels with HU values less than -950, the proposed approach modeled these voxels by different sizes of bullae balls and defines MI as a weighted sum of the percentages of the bullae balls of different size classes and locations in a lung. For evaluation of the efficacy of the proposed model, 45 emphysema subjects of different severity were involved in this study. In comparison with the conventional index, PI, the correlation between MI and FEV1/FVC is -0.75+/-0.08, which substantially outperforms the correlation between PI and FEV1/FVC, i.e., -0.63+/-0.11. Moreover, we have shown that the emphysematous lesion areas constituted by small bullae balls are basically irrelevant to FEV1/FVC. The statistical analysis and special case study results show that MI can offer better assessment in different analyses.

Magnetic resonance imaging of hypertrophic cardiomyopathy. Evaluation of diastolic function

International Nuclear Information System (INIS)

Schwarz, F.; Reiser, M.F.; Theisen, D.; Schwab, F.; Beckmann, B.M.; Schuessler, F.; Kaeaeb, S.; Zinsser, D.; Goelz, T.

2013-01-01

Hypertrophic cardiomyopathy (HCM) has a prevalence of approximately 0.2% and is clinically asymptomatic in many patients or presents with unspecific symptoms. This explains the importance of imaging for the diagnosis of HCM as well as for the assessment of the clinical course. The definitive finding in HCM is myocardial hypertrophy with thickening of the ventricular wall ≥ 15 mm. While echocardiography is an excellent screening tool magnetic resonance imaging (MRI) allows a comprehensive analysis of the heart in HCM. This includes a detailed analysis of the distribution and extent of myocardial hypertrophy, a thorough evaluation of systolic and diastolic cardiac function, the assessment of the presence and extent of dynamic outflow tract obstruction as well as the description of the systolic anterior motion (SAM) phenomenon of the mitral valve with secondary mitral insufficiency. When contrast material is administered, additional information about myocardial perfusion as well as the presence and extent of myocardial fibrosis can be obtained. This study compared systolic functional parameters as well as end systolic and end diastolic wall thickness of patients with and without diastolic dysfunction. (orig.) [de

Hyperspectral image analysis. A tutorial

International Nuclear Information System (INIS)

Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

2015-01-01

This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

Science.gov (United States)

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

Resting functional imaging tools (MRS, SPECT, PET and PCT)

NARCIS (Netherlands)

van der Naalt, Joukje; Grafman, Jordan; Salazar, Andres M

2015-01-01

Functional imaging includes imaging techniques that provide information about the metabolic and hemodynamic status of the brain. Most commonly applied functional imaging techniques in patients with traumatic brain injury (TBI) include magnetic resonance spectroscopy (MRS), single photon emission

Medical image registration for analysis

International Nuclear Information System (INIS)

Petrovic, V.

2006-01-01

Full text: Image registration techniques represent a rich family of image processing and analysis tools that aim to provide spatial correspondences across sets of medical images of similar and disparate anatomies and modalities. Image registration is a fundamental and usually the first step in medical image analysis and this paper presents a number of advanced techniques as well as demonstrates some of the advanced medical image analysis techniques they make possible. A number of both rigid and non-rigid medical image alignment algorithms of equivalent and merely consistent anatomical structures respectively are presented. The algorithms are compared in terms of their practical aims, inputs, computational complexity and level of operator (e.g. diagnostician) interaction. In particular, the focus of the methods discussion is placed on the applications and practical benefits of medical image registration. Results of medical image registration on a number of different imaging modalities and anatomies are presented demonstrating the accuracy and robustness of their application. Medical image registration is quickly becoming ubiquitous in medical imaging departments with the results of such algorithms increasingly used in complex medical image analysis and diagnostics. This paper aims to demonstrate at least part of the reason why

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology.

Science.gov (United States)

Markiewicz, Tomasz

2011-03-30

The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server

Evaluation of cardiac function using multi-shot echo planar imaging

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Tadashi; Tanitame, Nobuko; Hata, Ryoichiro; Hirai, Nobuhiko; Ikeda, Midori; Ono, Chiaki; Fukuoka, Haruhito; Ito, Katsuhide [Hiroshima Univ. (Japan). School of Medicine

1998-01-01

In this study, we performed multi-shot echo planar imaging (8 shot, TR/TE/FL=55 ms/18 ms/60 degrees) and k-space segmented fast gradient echo sequence (8 views per segment, TR/TE/FL=9.9 ms/1.8 ms/30 degrees) to assess cardiac function in healthy volunteers. Transaxial sections of the entire heart were obtained with both sequences in ECG triggered, breath hold, and with a 256 x 128 matrix. Resulting temporal resolution was 55 ms for echo planar imaging, and 71 ms for k-space segmented fast gradient echo sequence, respectively. Ventricular volume and ejection fraction of both ventricles and left ventricular mass obtained with multi-shot echo planar imaging were assessed in comparison with k-space segmented fast gradient echo sequence. Measurements of left ventricular volume, ejection fraction and mass obtained with multi-shot echo planar imaging demonstrated close correlation with those obtained with k-space segmented fast gradient echo sequence. Right ventricular volumes obtained with echo planar imaging were significantly higher than those obtained with k-space segmented fast gradient echo sequence. This tendency is considered to be due to differing contrast between right ventricular myocardium and fat tissue observed with echo planar imaging relative to that observed with fast gradient echo sequence, because fat suppression is always performed in echo planar images. Multi-shot echo planar imaging can be a reliable tool for measurement of cardiac functional parameters, although wall motion analysis of the left ventricle requires higher temporal resolution and a short axial section. (K.H.)

The Digital Image Processing And Quantitative Analysis In Microscopic Image Characterization

International Nuclear Information System (INIS)

Ardisasmita, M. Syamsa

2000-01-01

Many electron microscopes although have produced digital images, but not all of them are equipped with a supporting unit to process and analyse image data quantitatively. Generally the analysis of image has to be made visually and the measurement is realized manually. The development of mathematical method for geometric analysis and pattern recognition, allows automatic microscopic image analysis with computer. Image processing program can be used for image texture and structure periodic analysis by the application of Fourier transform. Because the development of composite materials. Fourier analysis in frequency domain become important for measure the crystallography orientation. The periodic structure analysis and crystal orientation are the key to understand many material properties like mechanical strength. stress, heat conductivity, resistance, capacitance and other material electric and magnetic properties. In this paper will be shown the application of digital image processing in microscopic image characterization and analysis in microscopic image

SIMA: Python software for analysis of dynamic fluorescence imaging data

Directory of Open Access Journals (Sweden)

Patrick eKaifosh

2014-09-01

Full Text Available Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs, and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/.

Dynamic chest radiography: flat-panel detector (FPD) based functional X-ray imaging.

Science.gov (United States)

Tanaka, Rie

2016-07-01

Dynamic chest radiography is a flat-panel detector (FPD)-based functional X-ray imaging, which is performed as an additional examination in chest radiography. The large field of view (FOV) of FPDs permits real-time observation of the entire lungs and simultaneous right-and-left evaluation of diaphragm kinetics. Most importantly, dynamic chest radiography provides pulmonary ventilation and circulation findings as slight changes in pixel value even without the use of contrast media; the interpretation is challenging and crucial for a better understanding of pulmonary function. The basic concept was proposed in the 1980s; however, it was not realized until the 2010s because of technical limitations. Dynamic FPDs and advanced digital image processing played a key role for clinical application of dynamic chest radiography. Pulmonary ventilation and circulation can be quantified and visualized for the diagnosis of pulmonary diseases. Dynamic chest radiography can be deployed as a simple and rapid means of functional imaging in both routine and emergency medicine. Here, we focus on the evaluation of pulmonary ventilation and circulation. This review article describes the basic mechanism of imaging findings according to pulmonary/circulation physiology, followed by imaging procedures, analysis method, and diagnostic performance of dynamic chest radiography.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

Science.gov (United States)

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Evaluation of coronary artery disease by functional imaging from equilibrium radionuclide ventriculography

International Nuclear Information System (INIS)

He Zuoxiang

1992-01-01

Functional imagings were performed in 10 normals, 9 subjects with Non coronary Artery disease (NCAD), 33 CAD patients with documented MI (CAD-WMI) and 20 without MI (CAD-NMI). The sensitivity of LVGEF, LVREF and phase analysis at rest for detecting CAD-WMI was 66.7%, 78.8%, 93.9% respectively. LVGEF, LVREF during exercise for assessing CAD-NMI had the sensitivity of 90%, 80%, respectively, while specificity 90%. Early LVEF decrease, > 10% LVEF decrease and abnormal response at > 7 sectors during exercise were observed in 2 patients with 3 vessel. In conclusion, functional imaging were very useful for detecting CAD and evaluating its extent

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

Science.gov (United States)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Ventilation/perfusion SPECT or SPECT/CT for lung function imaging in patients with pulmonary emphysema?

Science.gov (United States)

Froeling, Vera; Heimann, Uwe; Huebner, Ralf-Harto; Kroencke, Thomas J; Maurer, Martin H; Doellinger, Felix; Geisel, Dominik; Hamm, Bernd; Brenner, Winfried; Schreiter, Nils F

2015-07-01

To evaluate the utility of attenuation correction (AC) of V/P SPECT images for patients with pulmonary emphysema. Twenty-one patients (mean age 67.6 years) with pulmonary emphysema who underwent V/P SPECT/CT were included. AC/non-AC V/P SPECT images were compared visually and semiquantitatively. Visual comparison of AC/non-AC images was based on a 5-point likert scale. Semiquantitative comparison assessed absolute counts per lung (aCpLu) and lung lobe (aCpLo) for AC/non-AC images using software-based analysis; percentage counts (PC = (aCpLo/aCpLu) × 100) were calculated. Correlation between AC/non-AC V/P SPECT images was analyzed using Spearman's rho correlation coefficient; differences were tested for significance with the Wilcoxon rank sum test. Visual analysis revealed high conformity for AC and non-AC V/P SPECT images. Semiquantitative analysis of PC in AC/non-AC images had an excellent correlation and showed no significant differences in perfusion (ρ = 0.986) or ventilation (ρ = 0.979, p = 0.809) SPECT/CT images. AC of V/P SPECT images for lung lobe-based function imaging in patients with pulmonary emphysema do not improve visual or semiquantitative image analysis.

Functional Near Infrared Spectroscopy: Enabling Routine Functional Brain Imaging.

Science.gov (United States)

Yücel, Meryem A; Selb, Juliette J; Huppert, Theodore J; Franceschini, Maria Angela; Boas, David A

2017-12-01

Functional Near-Infrared Spectroscopy (fNIRS) maps human brain function by measuring and imaging local changes in hemoglobin concentrations in the brain that arise from the modulation of cerebral blood flow and oxygen metabolism by neural activity. Since its advent over 20 years ago, researchers have exploited and continuously advanced the ability of near infrared light to penetrate through the scalp and skull in order to non-invasively monitor changes in cerebral hemoglobin concentrations that reflect brain activity. We review recent advances in signal processing and hardware that significantly improve the capabilities of fNIRS by reducing the impact of confounding signals to improve statistical robustness of the brain signals and by enhancing the density, spatial coverage, and wearability of measuring devices respectively. We then summarize the application areas that are experiencing rapid growth as fNIRS begins to enable routine functional brain imaging.

Electrophoresis gel image processing and analysis using the KODAK 1D software.

Science.gov (United States)

Pizzonia, J

2001-06-01

The present article reports on the performance of the KODAK 1D Image Analysis Software for the acquisition of information from electrophoresis experiments and highlights the utility of several mathematical functions for subsequent image processing, analysis, and presentation. Digital images of Coomassie-stained polyacrylamide protein gels containing molecular weight standards and ethidium bromide stained agarose gels containing DNA mass standards are acquired using the KODAK Electrophoresis Documentation and Analysis System 290 (EDAS 290). The KODAK 1D software is used to optimize lane and band identification using features such as isomolecular weight lines. Mathematical functions for mass standard representation are presented, and two methods for estimation of unknown band mass are compared. Given the progressive transition of electrophoresis data acquisition and daily reporting in peer-reviewed journals to digital formats ranging from 8-bit systems such as EDAS 290 to more expensive 16-bit systems, the utility of algorithms such as Gaussian modeling, which can correct geometric aberrations such as clipping due to signal saturation common at lower bit depth levels, is discussed. Finally, image-processing tools that can facilitate image preparation for presentation are demonstrated.

Oncological image analysis.

Science.gov (United States)

Brady, Sir Michael; Highnam, Ralph; Irving, Benjamin; Schnabel, Julia A

2016-10-01

Cancer is one of the world's major healthcare challenges and, as such, an important application of medical image analysis. After a brief introduction to cancer, we summarise some of the major developments in oncological image analysis over the past 20 years, but concentrating those in the authors' laboratories, and then outline opportunities and challenges for the next decade. Copyright © 2016 Elsevier B.V. All rights reserved.

Artificial intelligence and medical imaging. Expert systems and image analysis

International Nuclear Information System (INIS)

Wackenheim, A.; Zoellner, G.; Horviller, S.; Jacqmain, T.

1987-01-01

This paper gives an overview on the existing systems for automated image analysis and interpretation in medical imaging, especially in radiology. The example of ORFEVRE, the system for the analysis of CAT-scan images of the cervical triplet (c3-c5) by image analysis and subsequent expert-system is given and discussed in detail. Possible extensions are described [fr

Multidimensional digital image representations using generalized Kaiser-Bessel window functions.

Science.gov (United States)

Lewitt, R M

1990-10-01

Inverse problems that require the solution of integral equations are inherent in a number of indirect imaging applications, such as computerized tomography. Numerical solutions based on discretization of the mathematical model of the imaging process, or on discretization of analytic formulas for iterative inversion of the integral equations, require a discrete representation of an underlying continuous image. This paper describes discrete image representations, in n-dimensional space, that are constructed by the superposition of shifted copies of a rotationally symmetric basis function. The basis function is constructed using a generalization of the Kaiser-Bessel window function of digital signal processing. The generalization of the window function involves going from one dimension to a rotationally symmetric function in n dimensions and going from the zero-order modified Bessel function of the standard window to a function involving the modified Bessel function of order m. Three methods are given for the construction, in n-dimensional space, of basis functions having a specified (finite) number of continuous derivatives, and formulas are derived for the Fourier transform, the x-ray transform, the gradient, and the Laplacian of these basis functions. Properties of the new image representations using these basis functions are discussed, primarily in the context of two-dimensional and three-dimensional image reconstruction from line-integral data by iterative inversion of the x-ray transform. Potential applications to three-dimensional image display are also mentioned.

Studying Axon-Astrocyte Functional Interactions by 3D Two-Photon Ca2+ Imaging: A Practical Guide to Experiments and "Big Data" Analysis.

Science.gov (United States)

Savtchouk, Iaroslav; Carriero, Giovanni; Volterra, Andrea

2018-01-01

Recent advances in fast volumetric imaging have enabled rapid generation of large amounts of multi-dimensional functional data. While many computer frameworks exist for data storage and analysis of the multi-gigabyte Ca 2+ imaging experiments in neurons, they are less useful for analyzing Ca 2+ dynamics in astrocytes, where transients do not follow a predictable spatio-temporal distribution pattern. In this manuscript, we provide a detailed protocol and commentary for recording and analyzing three-dimensional (3D) Ca 2+ transients through time in GCaMP6f-expressing astrocytes of adult brain slices in response to axonal stimulation, using our recently developed tools to perform interactive exploration, filtering, and time-correlation analysis of the transients. In addition to the protocol, we release our in-house software tools and discuss parameters pertinent to conducting axonal stimulation/response experiments across various brain regions and conditions. Our software tools are available from the Volterra Lab webpage at https://wwwfbm.unil.ch/dnf/group/glia-an-active-synaptic-partner/member/volterra-andrea-volterra in the form of software plugins for Image J (NIH)-a de facto standard in scientific image analysis. Three programs are available: MultiROI_TZ_profiler for interactive graphing of several movable ROIs simultaneously, Gaussian_Filter5D for Gaussian filtering in several dimensions, and Correlation_Calculator for computing various cross-correlation parameters on voxel collections through time.

Imaging of the Eustachian tube and its function: a systematic review

Energy Technology Data Exchange (ETDEWEB)

Smith, M.E.; Tysome, J.R. [Cambridge University Hospitals NHS Foundation Trust, Department of ENT Surgery, Addenbrooke' s Hospital, Cambridge (United Kingdom); Scoffings, D.J. [Cambridge University Hospitals NHS Foundation Trust, Department of Radiology, Addenbrooke' s Hospital, Cambridge (United Kingdom)

2016-06-15

The Eustachian tube is a complex and inaccessible structure, which maintains middle ear ventilation to facilitate transmission of sound from the tympanic membrane to the cochlea. A renewed interest in treatments for eustachian tube dysfunction has led to a demand for methods of imaging the Eustachian tube, and assessing tube opening non-invasively. This review aims to summarise the use of imaging in the anatomical assessment of the Eustachian tube, and to explore how radiological techniques can be used to assess tube function. A systematic review of the literature was performed with narrative data analysis. With high-resolution images, the soft and bony anatomy of the Eustachian tube can be assessed in detail. CT and MRI are best suited to identifying features associated with obstructive or patulous Eustachian tube dysfunction, though true assessments of function have only been achieved with contrast enhanced radiographs and scintigraphy. A single modality has yet to provide a complete assessment. No test has entered routine clinical use, but further development and research is underway. Significant information can be gained from imaging the Eustachian tube, and as faster acquisition techniques are developed, it is possible that dynamic imaging of tubal opening could play an important role in the assessment of patients with ET dysfunction. (orig.)

Microscopy image segmentation tool: Robust image data analysis

Energy Technology Data Exchange (ETDEWEB)

Valmianski, Ilya, E-mail: ivalmian@ucsd.edu; Monton, Carlos; Schuller, Ivan K. [Department of Physics and Center for Advanced Nanoscience, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093 (United States)

2014-03-15

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

Microscopy image segmentation tool: Robust image data analysis

Science.gov (United States)

Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

2014-03-01

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

Microscopy image segmentation tool: Robust image data analysis

International Nuclear Information System (INIS)

Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K.

2014-01-01

We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy

Resting-State Functional MR Imaging for Determining Language Laterality in Intractable Epilepsy.

Science.gov (United States)

DeSalvo, Matthew N; Tanaka, Naoaki; Douw, Linda; Leveroni, Catherine L; Buchbinder, Bradley R; Greve, Douglas N; Stufflebeam, Steven M

2016-10-01

Purpose To measure the accuracy of resting-state functional magnetic resonance (MR) imaging in determining hemispheric language dominance in patients with medically intractable focal epilepsies against the results of an intracarotid amobarbital procedure (IAP). Materials and Methods This study was approved by the institutional review board, and all subjects gave signed informed consent. Data in 23 patients with medically intractable focal epilepsy were retrospectively analyzed. All 23 patients were candidates for epilepsy surgery and underwent both IAP and resting-state functional MR imaging as part of presurgical evaluation. Language dominance was determined from functional MR imaging data by calculating a laterality index (LI) after using independent component analysis. The accuracy of this method was assessed against that of IAP by using a variety of thresholds. Sensitivity and specificity were calculated by using leave-one-out cross validation. Spatial maps of language components were qualitatively compared among each hemispheric language dominance group. Results Measurement of hemispheric language dominance with resting-state functional MR imaging was highly concordant with IAP results, with up to 96% (22 of 23) accuracy, 96% (22 of 23) sensitivity, and 96% (22 of 23) specificity. Composite language component maps in patients with typical language laterality consistently included classic language areas such as the inferior frontal gyrus, the posterior superior temporal gyrus, and the inferior parietal lobule, while those of patients with atypical language laterality also included non-classical language areas such as the superior and middle frontal gyri, the insula, and the occipital cortex. Conclusion Resting-state functional MR imaging can be used to measure language laterality in patients with medically intractable focal epilepsy. (©) RSNA, 2016 Online supplemental material is available for this article.

Visceral Afferent Pathways and Functional Brain Imaging

Directory of Open Access Journals (Sweden)

Stuart W.G. Derbyshire

2003-01-01

Full Text Available The application of functional imaging to study painful sensations has generated considerable interest regarding insight into brain dysfunction that may be responsible for functional pain such as that suffered in patients with irritable bowel syndrome (IBS. This review provides a brief introduction to the development of brain science as it relates to pain processing and a snapshot of recent functional imaging results with somatic and visceral pain. Particular emphasis is placed on current hypotheses regarding dysfunction of the brain-gut axis in IBS patients. There are clear and interpretable differences in brain activation following somatic as compared with visceral noxious sensation. Noxious visceral distension, particularly of the lower gastrointestinal tract, activates regions associated with unpleasant affect and autonomic responses. Noxious somatic sensation, in contrast, activates regions associated with cognition and skeletomotor responses. Differences between IBS patients and control subjects, however, were far less clear and interpretable. While this is in part due to the newness of this field, it also reflects weaknesses inherent within the current understanding of IBS. Future use of functional imaging to examine IBS and other functional disorders will be more likely to succeed by describing clear theoretical and clinical endpoints.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

Science.gov (United States)

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the

Bench to bedside molecular functional imaging in translational cancer medicine: to image or to imagine?

International Nuclear Information System (INIS)

Mahajan, A.; Goh, V.; Basu, S.; Vaish, R.; Weeks, A.J.; Thakur, M.H.; Cook, G.J.

2015-01-01

Ongoing research on malignant and normal cell biology has substantially enhanced the understanding of the biology of cancer and carcinogenesis. This has led to the development of methods to image the evolution of cancer, target specific biological molecules, and study the anti-tumour effects of novel therapeutic agents. At the same time, there has been a paradigm shift in the field of oncological imaging from purely structural or functional imaging to combined multimodal structure–function approaches that enable the assessment of malignancy from all aspects (including molecular and functional level) in a single examination. The evolving molecular functional imaging using specific molecular targets (especially with combined positron-emission tomography [PET] computed tomography [CT] using 2- [ 18 F]-fluoro-2-deoxy-D-glucose [FDG] and other novel PET tracers) has great potential in translational research, giving specific quantitative information with regard to tumour activity, and has been of pivotal importance in diagnoses and therapy tailoring. Furthermore, molecular functional imaging has taken a key place in the present era of translational cancer research, producing an important tool to study and evolve newer receptor-targeted therapies, gene therapies, and in cancer stem cell research, which could form the basis to translate these agents into clinical practice, popularly termed “theranostics”. Targeted molecular imaging needs to be developed in close association with biotechnology, information technology, and basic translational scientists for its best utility. This article reviews the current role of molecular functional imaging as one of the main pillars of translational research. -- Highlights: •Molecular functional imaging (MFI) gives insight into the tumor biology and intratumoral heterogeneity. •It has potential role in identifying radiomic signatures associated with underlying gene-expression. •Radiomics can be used to create a road map

Hyperspectral image analysis. A tutorial

DEFF Research Database (Denmark)

Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa

2015-01-01

This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processi...... to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case....... will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology...

Exploring brain function with magnetic resonance imaging

International Nuclear Information System (INIS)

Di Salle, F.; Formisano, E.; Linden, D.E.J.; Goebel, R.; Bonavita, S.; Pepino, A.; Smaltino, F.; Tedeschi, G.

1999-01-01

Since its invention in the early 1990s, functional magnetic resonance imaging (fMRI) has rapidly assumed a leading role among the techniques used to localize brain activity. The spatial and temporal resolution provided by state-of-the-art MR technology and its non-invasive character, which allows multiple studies of the same subject, are some of the main advantages of fMRI over the other functional neuroimaging modalities that are based on changes in blood flow and cortical metabolism. This paper describes the basic principles and methodology of fMRI and some aspects of its application to functional activation studies. Attention is focused on the physiology of the blood oxygenation level-dependent (BOLD) contrast mechanism and on the acquisition of functional time-series with echo planar imaging (EPI). We also provide an introduction to the current strategies for the correction of signal artefacts and other image processing techniques. In order to convey an idea of the numerous applications of fMRI, we will review some of the recent results in the fields of cognitive and sensorimotor psychology and physiology

Exploring brain function with magnetic resonance imaging

Energy Technology Data Exchange (ETDEWEB)

Di Salle, F.; Formisano, E.; Linden, D.E.J.; Goebel, R.; Bonavita, S.; Pepino, A.; Smaltino, F.; Tedeschi, G

1999-05-01

Since its invention in the early 1990s, functional magnetic resonance imaging (fMRI) has rapidly assumed a leading role among the techniques used to localize brain activity. The spatial and temporal resolution provided by state-of-the-art MR technology and its non-invasive character, which allows multiple studies of the same subject, are some of the main advantages of fMRI over the other functional neuroimaging modalities that are based on changes in blood flow and cortical metabolism. This paper describes the basic principles and methodology of fMRI and some aspects of its application to functional activation studies. Attention is focused on the physiology of the blood oxygenation level-dependent (BOLD) contrast mechanism and on the acquisition of functional time-series with echo planar imaging (EPI). We also provide an introduction to the current strategies for the correction of signal artefacts and other image processing techniques. In order to convey an idea of the numerous applications of fMRI, we will review some of the recent results in the fields of cognitive and sensorimotor psychology and physiology.

Imaging mass spectrometry statistical analysis.

Science.gov (United States)

Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

2012-08-30

Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

Operational parameters analysis of the radiographic technique through the modulation transfer function

International Nuclear Information System (INIS)

Motta, Mauricio Saldanha; Guimaraes, Ari Sauer

1995-01-01

The influence of the focal size and image magnification variations on the radiographic final image is studied. The analysis used the modulation transfer function for evaluating the ratio of the radiographic image amplitude and that of the inspected object. it was concluded that the increase of the focal size and of the magnifications are not good for the image quality. 3 refs., 4 figs., 1 tab

Automatic selection of resting-state networks with functional magnetic resonance imaging

Directory of Open Access Journals (Sweden)

Silvia Francesca eStorti

2013-05-01

Full Text Available Functional magnetic resonance imaging (fMRI during a resting-state condition can reveal the co-activation of specific brain regions in distributed networks, called resting-state networks, which are selected by independent component analysis (ICA of the fMRI data. One of the major difficulties with component analysis is the automatic selection of the ICA features related to brain activity. In this study we describe a method designed to automatically select networks of potential functional relevance, specifically, those regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. To do this, image analysis was based on probabilistic ICA as implemented in FSL software. After decomposition, the optimal number of components was selected by applying a novel algorithm which takes into account, for each component, Pearson's median coefficient of skewness of the spatial maps generated by FSL, followed by clustering, segmentation, and spectral analysis. To evaluate the performance of the approach, we investigated the resting-state networks in 25 subjects. For each subject, three resting-state scans were obtained with a Siemens Allegra 3 T scanner (NYU data set. Comparison of the visually and the automatically identified neuronal networks showed that the algorithm had high accuracy (first scan: 95%, second scan: 95%, third scan: 93% and precision (90%, 90%, 84%. The reproducibility of the networks for visual and automatic selection was very close: it was highly consistent in each subject for the default-mode network (≥ 92% and the occipital network, which includes the medial visual cortical areas (≥ 94%, and consistent for the attention network (≥ 80%, the right and/or left lateralized frontoparietal attention networks, and the temporal-motor network (≥ 80%. The automatic selection method may be used to detect neural networks and reduce subjectivity in ICA

Functional analysis

CERN Document Server

Kantorovich, L V

1982-01-01

Functional Analysis examines trends in functional analysis as a mathematical discipline and the ever-increasing role played by its techniques in applications. The theory of topological vector spaces is emphasized, along with the applications of functional analysis to applied analysis. Some topics of functional analysis connected with applications to mathematical economics and control theory are also discussed. Comprised of 18 chapters, this book begins with an introduction to the elements of the theory of topological spaces, the theory of metric spaces, and the theory of abstract measure space

Developing a Korean standard brain atlas on the basis of statistical and probabilistic approach and visualization tool for functional image analysis

Energy Technology Data Exchange (ETDEWEB)

Koo, B. B.; Lee, J. M.; Kim, J. S.; Kim, I. Y.; Kim, S. I. [Hanyang University, Seoul (Korea, Republic of); Lee, J. S.; Lee, D. S.; Kwon, J. S. [Seoul National University College of Medicine, Seoul (Korea, Republic of); Kim, J. J. [Yonsei University College of Medicine, Seoul (Korea, Republic of)

2003-06-01

The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated region because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 brains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeled with the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each region is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease.

Developing a Korean standard brain atlas on the basis of statistical and probabilistic approach and visualization tool for functional image analysis

International Nuclear Information System (INIS)

Koo, B. B.; Lee, J. M.; Kim, J. S.; Kim, I. Y.; Kim, S. I.; Lee, J. S.; Lee, D. S.; Kwon, J. S.; Kim, J. J.

2003-01-01

The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated region because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 brains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeled with the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each region is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease

Self-calibrated correlation imaging with k-space variant correlation functions.

Science.gov (United States)

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Low-level processing for real-time image analysis

Science.gov (United States)

Eskenazi, R.; Wilf, J. M.

1979-01-01

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Structural and functional imaging: Particularities in children

International Nuclear Information System (INIS)

Chiron, C.; Hertz-Pannier, L.; Chiron, C.; Hertz-Pannier, L.; Chiron, C.; Hertz-Pannier, L.

2008-01-01

Surgery of partial epilepsies in childhood has largely benefited from the recent advances of imaging techniques, which carry a triple goal: (1) to contribute to the localization of the epilepsy onset zone, (2) to detect and delineate an underlying lesion, and (3) to study the spatial relationship between the epileptogenic zone and the neighboring functional cortex, in order to select patients and plan the resection. This noninvasive pre-surgical imaging workup must be compared to clinical and electrical data to estimate the postoperative prognosis, while invasive techniques such as SEEG, cortical stimulations, and IAT often remain indispensable in difficult cases, i.e., in cryptogenic epilepsies. As in adults, advances in MRI allow us to detect more and more subtle underlying lesions, but this requires repeating MR studies during early childhood and using adapted sequence parameters to account for ongoing myelination. Ictal SPECT and PET imaging prove especially useful in planning depth electrode placement when video-EEG is not contributive, when MRI looks normal or shows multiple abnormalities, or in cases of discrepant findings. Multimodal imaging greatly enhances the sensitivity of all of these techniques. Finally, functional MRI of motor and language functions provide noninvasive cortical mapping of essential functions, using age-adapted paradigms, in cooperating children from age five to six and from IQs around 60. (authors)

Structural and functional imaging: Particularities in children

Energy Technology Data Exchange (ETDEWEB)

Chiron, C.; Hertz-Pannier, L. [Hop Necker Enfants Malad, INSERM, Serv Neuropediat, U663, F-75015 Paris (France); Chiron, C.; Hertz-Pannier, L. [UnivParis 05, F-75005 Paris (France); Chiron, C.; Hertz-Pannier, L. [CEA, I2BM, Neurospin, SHFJ, F-91191 Orsay (France)

2008-07-01

Surgery of partial epilepsies in childhood has largely benefited from the recent advances of imaging techniques, which carry a triple goal: (1) to contribute to the localization of the epilepsy onset zone, (2) to detect and delineate an underlying lesion, and (3) to study the spatial relationship between the epileptogenic zone and the neighboring functional cortex, in order to select patients and plan the resection. This noninvasive pre-surgical imaging workup must be compared to clinical and electrical data to estimate the postoperative prognosis, while invasive techniques such as SEEG, cortical stimulations, and IAT often remain indispensable in difficult cases, i.e., in cryptogenic epilepsies. As in adults, advances in MRI allow us to detect more and more subtle underlying lesions, but this requires repeating MR studies during early childhood and using adapted sequence parameters to account for ongoing myelination. Ictal SPECT and PET imaging prove especially useful in planning depth electrode placement when video-EEG is not contributive, when MRI looks normal or shows multiple abnormalities, or in cases of discrepant findings. Multimodal imaging greatly enhances the sensitivity of all of these techniques. Finally, functional MRI of motor and language functions provide noninvasive cortical mapping of essential functions, using age-adapted paradigms, in cooperating children from age five to six and from IQs around 60. (authors)

Multi-Resolution Wavelet-Transformed Image Analysis of Histological Sections of Breast Carcinomas

Directory of Open Access Journals (Sweden)

Hae-Gil Hwang

2005-01-01

Full Text Available Multi-resolution images of histological sections of breast cancer tissue were analyzed using texture features of Haar- and Daubechies transform wavelets. Tissue samples analyzed were from ductal regions of the breast and included benign ductal hyperplasia, ductal carcinoma in situ (DCIS, and invasive ductal carcinoma (CA. To assess the correlation between computerized image analysis and visual analysis by a pathologist, we created a two-step classification system based on feature extraction and classification. In the feature extraction step, we extracted texture features from wavelet-transformed images at 10× magnification. In the classification step, we applied two types of classifiers to the extracted features, namely a statistics-based multivariate (discriminant analysis and a neural network. Using features from second-level Haar transform wavelet images in combination with discriminant analysis, we obtained classification accuracies of 96.67 and 87.78% for the training and testing set (90 images each, respectively. We conclude that the best classifier of carcinomas in histological sections of breast tissue are the texture features from the second-level Haar transform wavelet images used in a discriminant function.

Image analysis and modeling in medical image computing. Recent developments and advances.

Science.gov (United States)

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

Functional magnetic resonance imaging (FMRI) and expert testimony.

Science.gov (United States)

Kulich, Ronald; Maciewicz, Raymond; Scrivani, Steven J

2009-03-01

Medical experts frequently use imaging studies to illustrate points in their court testimony. This article reviews how these studies impact the credibility of expert testimony with judges and juries. The apparent "objective" evidence provided by such imaging studies can lend strong credence to a judge's or jury's appraisal of medical expert's testimony. However, as the court usually has no specialized scientific expertise, the use of complex images as part of courtroom testimony also has the potential to mislead or at least inappropriately bias the weight given to expert evidence. Recent advances in brain imaging may profoundly impact forensic expert testimony. Functional magnetic resonance imaging and other physiologic imaging techniques currently allow visualization of the activation pattern of brain regions associated with a wide variety of cognitive and behavioral tasks, and more recently, pain. While functional imaging technology has a valuable role in brain research and clinical investigation, it is important to emphasize that the use of imaging studies in forensic matters requires a careful scientific foundation and a rigorous legal assessment.

Quantitative image analysis of synovial tissue

NARCIS (Netherlands)

van der Hall, Pascal O.; Kraan, Maarten C.; Tak, Paul Peter

2007-01-01

Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the

An analysis of 'obstructive type' renography cases in 99mTc-DTPA renal dynamic imaging

International Nuclear Information System (INIS)

Wang Xinhui

1991-01-01

99m Tc-DTPA renal dynamic imaging and computed renography were performed in 61 cases. Renal blood perfusion imaging was also performed in some cases. Renography curves, which did not decrease in 20 min on all 61 cases (90 kidneys), are analysed in combination with renal dynamic imaging and renal perfusion imaging. 11 cases (12 kidneys) are only obstructive. 24 cases (32 kidneys) are obstructive and renal function impaired. Other 26 cases (46 kidneys) are renal function impaired or blood perfusion insufficient, but are not obstructive. The result demonstrated that the obstructive type renography may be obstructive or may be renal function impaired or blood supply insufficient. An analysis of renography in combination with renal dynamic imaging and blood perfusion imaging is more accurate than renography alone

Supplementary value of functional imaging in forensic medicine.

Science.gov (United States)

Mirzaei, Siroos; Sonneck-Koenne, Charlotte; Bruecke, Thomas; Aryana, Kamran; Knoll, Peter; Zakavi, Rasoul

2012-01-01

The aim of this study is to evaluate the role of functional imaging for forensic purposes. We reviewed a few outpatient cases that were sent to our department for examination after traumatic events and one case with neuropsychic disturbances. Functional imaging showed signs of traumatic lesions in the skeletal system, of brain metabolism and of renal failure. Functional disturbances following traumatic events are in some cases more important than morphological abnormalities. Targeted scintigraphic examinations could be applied for visualisation of traumatic lesions or evaluation of functional disturbances caused by traumatic events. These examinations can be used as evidence in the courtroom.

Functional imaging in oncology. Clinical applications. Vol. 2

Energy Technology Data Exchange (ETDEWEB)

Luna, Antonio [Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Radiology; MRI Health Time Group, Jaen (Spain); Vilanova, Joan C. [Girona Univ. (Spain). Clinica Girona - Hospital Sta. Caterina; Hygino da Cruz, L. Celso Jr. (ed.) [CDPI and IRM, Rio de Janeiro (Brazil). Dept. of Radiology; Rossi, Santiago E. [Centro de Diagnostico, Buenos Aires (Argentina)

2014-06-01

Easy-to-read manual on new functional imaging techniques in oncology. Explains current clinical applications and outlines future avenues. Includes numerous high-quality illustrations to highlight the major teaching points. In the new era of functional and molecular imaging, both currently available imaging biomarkers and biomarkers under development are expected to lead to major changes in the management of oncological patients. This two-volume book is a practical manual on the various imaging techniques capable of delivering functional information on cancer, including diffusion MRI, perfusion CT and MRI, dual-energy CT, spectroscopy, dynamic contrast-enhanced ultrasonography, PET, and hybrid modalities. This second volume considers the applications and benefits of these techniques in a wide range of tumor types, including their role in diagnosis, prediction of treatment outcome, and early evaluation of treatment response. Each chapter addresses a specific malignancy and is written by one or more acclaimed experts. The lucid text is complemented by numerous high-quality illustrations that highlight key features and major teaching points.

Functional imaging in oncology. Clinical applications. Vol. 2

International Nuclear Information System (INIS)

Luna, Antonio; Vilanova, Joan C.

2014-01-01

Easy-to-read manual on new functional imaging techniques in oncology. Explains current clinical applications and outlines future avenues. Includes numerous high-quality illustrations to highlight the major teaching points. In the new era of functional and molecular imaging, both currently available imaging biomarkers and biomarkers under development are expected to lead to major changes in the management of oncological patients. This two-volume book is a practical manual on the various imaging techniques capable of delivering functional information on cancer, including diffusion MRI, perfusion CT and MRI, dual-energy CT, spectroscopy, dynamic contrast-enhanced ultrasonography, PET, and hybrid modalities. This second volume considers the applications and benefits of these techniques in a wide range of tumor types, including their role in diagnosis, prediction of treatment outcome, and early evaluation of treatment response. Each chapter addresses a specific malignancy and is written by one or more acclaimed experts. The lucid text is complemented by numerous high-quality illustrations that highlight key features and major teaching points.

Image based rendering of iterated function systems

NARCIS (Netherlands)

Wijk, van J.J.; Saupe, D.

2004-01-01

A fast method to generate fractal imagery is presented. Iterated function systems (IFS) are based on repeatedly copying transformed images. We show that this can be directly translated into standard graphics operations: Each image is generated by texture mapping and blending copies of the previous

Functional imaging in oncology. Biophysical basis and technical approaches. Vol. 1

Energy Technology Data Exchange (ETDEWEB)

Luna, Antonio [Health Time Group, Jaen (Spain); University Hospitals, Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Radiology; Vilanova, Joan C. [Clinica Girona - Hospital Sta. Caterina, Girona (Spain); Hygino da Cruz, L. Celso Jr. [CDPI and IRM, Rio de Janeiro, RJ (Brazil). Dept. of Radiology; Rossi, Santiago E. (ed.) [Centro de Diagnostico, Buenos Aires (Argentina)

2014-07-01

Easy-to-read manual on new functional imaging techniques in oncology. Explains current clinical applications and outlines future avenues. Includes numerous high-quality illustrations to highlight the major teaching points. In the new era of functional and molecular imaging, both currently available imaging biomarkers and biomarkers under development are expected to lead to major changes in the management of oncological patients. This well-illustrated two-volume book is a practical manual on the various imaging techniques capable of delivering functional information on cancer, including preclinical and clinical imaging techniques, based on US, CT, MRI, PET and hybrid modalities. This first volume explains the biophysical basis for these functional imaging techniques and describes the techniques themselves. Detailed information is provided on the imaging of cancer hallmarks, including angiogenesis, tumor metabolism, and hypoxia. The techniques and their roles are then discussed individually, covering the full range of modalities in clinical use as well as new molecular and functional techniques. The value of a multiparametric approach is also carefully considered.

Functional imaging in oncology. Biophysical basis and technical approaches. Vol. 1

International Nuclear Information System (INIS)

Luna, Antonio; Hygino da Cruz, L. Celso Jr.

2014-01-01

Easy-to-read manual on new functional imaging techniques in oncology. Explains current clinical applications and outlines future avenues. Includes numerous high-quality illustrations to highlight the major teaching points. In the new era of functional and molecular imaging, both currently available imaging biomarkers and biomarkers under development are expected to lead to major changes in the management of oncological patients. This well-illustrated two-volume book is a practical manual on the various imaging techniques capable of delivering functional information on cancer, including preclinical and clinical imaging techniques, based on US, CT, MRI, PET and hybrid modalities. This first volume explains the biophysical basis for these functional imaging techniques and describes the techniques themselves. Detailed information is provided on the imaging of cancer hallmarks, including angiogenesis, tumor metabolism, and hypoxia. The techniques and their roles are then discussed individually, covering the full range of modalities in clinical use as well as new molecular and functional techniques. The value of a multiparametric approach is also carefully considered.

Form or function: Does focusing on body functionality protect women from body dissatisfaction when viewing media images?

Science.gov (United States)

Mulgrew, Kate E; Tiggemann, Marika

2018-01-01

We examined whether shifting young women's ( N =322) attention toward functionality components of media-portrayed idealized images would protect against body dissatisfaction. Image type was manipulated via images of models in either an objectified body-as-object form or active body-as-process form; viewing focus was manipulated via questions about the appearance or functionality of the models. Social comparison was examined as a moderator. Negative outcomes were most pronounced within the process-related conditions (body-as-process images or functionality viewing focus) and for women who reported greater functionality comparison. Results suggest that functionality-based depictions, reflections, and comparisons may actually produce worse outcomes than those based on appearance.

Imaging and chemical surface analysis of biomolecular functionalization of monolithically integrated on silicon Mach-Zehnder interferometric immunosensors

International Nuclear Information System (INIS)

Gajos, Katarzyna; Angelopoulou, Michailia; Petrou, Panagiota; Awsiuk, Kamil; Kakabakos, Sotirios; Haasnoot, Willem; Bernasik, Andrzej; Rysz, Jakub; Marzec, Mateusz M.; Misiakos, Konstantinos; Raptis, Ioannis; Budkowski, Andrzej

2016-01-01

Highlights: • Optimization of probe immobilization with robotic spotter printing overlapping spots. • In-situ inspection of microstructured surfaces of biosensors integrated on silicon. • Imaging and chemical analysis of immobilization, surface blocking and immunoreaction. • Insight with molecular discrimination into step-by-step sensor surface modifications. • Optimized biofunctionalization improves sensor sensitivity and response repeatability. - Abstract: Time-of-flight secondary ion mass spectrometry (imaging, micro-analysis) has been employed to evaluate biofunctionalization of the sensing arm areas of Mach-Zehnder interferometers monolithically integrated on silicon chips for the immunochemical (competitive) detection of bovine κ-casein in goat milk. Biosensor surfaces are examined after: modification with (3-aminopropyl)triethoxysilane, application of multiple overlapping spots of κ-casein solutions, blocking with 100-times diluted goat milk, and reaction with monoclonal mouse anti-κ-casein antibodies in blocking solution. The areas spotted with κ-casein solutions of different concentrations are examined and optimum concentration providing homogeneous coverage is determined. Coverage of biosensor surfaces with biomolecules after each of the sequential steps employed in immunodetection is also evaluated with TOF-SIMS, supplemented by Atomic force microscopy and X-ray photoelectron spectroscopy. Uniform molecular distributions are observed on the sensing arm areas after spotting with optimum κ-casein concentration, blocking and immunoreaction. The corresponding biomolecular compositions are determined with a Principal Component Analysis that distinguished between protein amino acids and milk glycerides, as well as between amino acids characteristic for Mabs and κ-casein, respectively. Use of the optimum conditions (κ-casein concentration) for functionalization of chips with arrays of ten Mach-Zehnder interferometers provided on-chips assays

Imaging and chemical surface analysis of biomolecular functionalization of monolithically integrated on silicon Mach-Zehnder interferometric immunosensors

Energy Technology Data Exchange (ETDEWEB)

Gajos, Katarzyna, E-mail: kasia.fornal@uj.edu.pl [M. Smoluchowski Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków (Poland); Angelopoulou, Michailia; Petrou, Panagiota [Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, NCSR Demokritos, P. Grigoriou & Neapoleos St, Aghia Paraksevi 15310, Athens (Greece); Awsiuk, Kamil [M. Smoluchowski Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków (Poland); Kakabakos, Sotirios [Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, NCSR Demokritos, P. Grigoriou & Neapoleos St, Aghia Paraksevi 15310, Athens (Greece); Haasnoot, Willem [RIKILT Wageningen UR, Akkermaalsbos 2, 6708 WB Wageningen (Netherlands); Bernasik, Andrzej [Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków (Poland); Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków (Poland); Rysz, Jakub [M. Smoluchowski Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków (Poland); Marzec, Mateusz M. [Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków (Poland); Misiakos, Konstantinos; Raptis, Ioannis [Department of Microelectronics, Institute of Nanoscience and Nanotechnology, NCSR Demokritos, P. Grigoriou & Neapoleos St, Aghia Paraksevi 15310, Athens (Greece); Budkowski, Andrzej [M. Smoluchowski Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków (Poland)

2016-11-01

Highlights: • Optimization of probe immobilization with robotic spotter printing overlapping spots. • In-situ inspection of microstructured surfaces of biosensors integrated on silicon. • Imaging and chemical analysis of immobilization, surface blocking and immunoreaction. • Insight with molecular discrimination into step-by-step sensor surface modifications. • Optimized biofunctionalization improves sensor sensitivity and response repeatability. - Abstract: Time-of-flight secondary ion mass spectrometry (imaging, micro-analysis) has been employed to evaluate biofunctionalization of the sensing arm areas of Mach-Zehnder interferometers monolithically integrated on silicon chips for the immunochemical (competitive) detection of bovine κ-casein in goat milk. Biosensor surfaces are examined after: modification with (3-aminopropyl)triethoxysilane, application of multiple overlapping spots of κ-casein solutions, blocking with 100-times diluted goat milk, and reaction with monoclonal mouse anti-κ-casein antibodies in blocking solution. The areas spotted with κ-casein solutions of different concentrations are examined and optimum concentration providing homogeneous coverage is determined. Coverage of biosensor surfaces with biomolecules after each of the sequential steps employed in immunodetection is also evaluated with TOF-SIMS, supplemented by Atomic force microscopy and X-ray photoelectron spectroscopy. Uniform molecular distributions are observed on the sensing arm areas after spotting with optimum κ-casein concentration, blocking and immunoreaction. The corresponding biomolecular compositions are determined with a Principal Component Analysis that distinguished between protein amino acids and milk glycerides, as well as between amino acids characteristic for Mabs and κ-casein, respectively. Use of the optimum conditions (κ-casein concentration) for functionalization of chips with arrays of ten Mach-Zehnder interferometers provided on-chips assays

METHODS OF DISTANCE MEASUREMENT’S ACCURACY INCREASING BASED ON THE CORRELATION ANALYSIS OF STEREO IMAGES

Directory of Open Access Journals (Sweden)

V. L. Kozlov

2018-01-01

Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.

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

Assessment of renal function with 99Tcm-DTPA renal dynamic imaging in neonatal hydronephrosis

International Nuclear Information System (INIS)

Jiang Lixin; Guo Zongyuan; Wu Rongde; Yu Qihai; Liu Zhanfeng

2004-01-01

Objective: To assess the renal function in neonatal hydronephrosis with 99 Tc m -DTPA renal imaging. Methods: Eighteen unilateral hydronephrotic kidneys and 12 normal kidneys were studied by 99 Tc m -DTPA renal dynamic imaging , and glomerular filtration rate (GFR) quantitative analysis was also performed. Blood urea nitrogen (BUN), serum creatinine (SCr) and hemoglobin (Hb) were determined simultaneously and the correlations between GFR and each of these parameters were analyzed. Results: Positive correlation was discovered between GFR and Hb in neonates with moderate or severe hydronephrosis (r=0.414, 0.667, P 0.05). The renal function was decreased significantly in moderate and severe neonatal hydronephrosis (P 99 Tc m -DTPA renal dynamic imaging GFR is an ideal marker for estimating renal function in neonatal hydronephrosis; SCr could be a marker for renal damage especially in moderate and severe neonatal hydronephrosis; BUN could not be a marker for evaluating renal function in neonatal hydronephrosis. Neonates with hydronephrosis should be referred for surgical procedures as soon as possible in the early stage

Gradient field echo imaging and Gd-DTPA for the assessment of renal function in humans

International Nuclear Information System (INIS)

Von Schulthess, G.K.; Kikinis, R.; Durr, R.; Bino, M.; Jager, P.; Kubler, O.

1986-01-01

To evaluate renal parenchymal function, 1.5 T gradient field echo imaging using a sequence of repetitive 10-second scans was performed in apneic patients after injection of Gd-DTPA (0.1 mmol/kg body weight). During the 10-second pauses the patients were allowed to breathe. Angled coronal images (TR=40 msec, TE =20 msec, flip angle = 40 0 ) were obtained in four volunteers and four patients with hydronephrosis. Image quality was excellent, suggesting unprecedented spatial resolution for renal function studies. Initially, cortical perfusion was observed. Then the papilae became isointense; after 70 seconds they became hypointense; and finally the renal pelvic signal dropped. No papillary signal drop was seen in hydronephrosis, as confirmed by region-of-interest analysis. These results strongly suggest that in MR renal ''function'' studies with Gd-DTPA, T1 and T2 paramagnetic effects are operative

Stochastic geometry for image analysis

CERN Document Server

Descombes, Xavier

2013-01-01

This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are  described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed.  Numerous applications, covering remote sensing images, biological and medical imaging, are detailed.  This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.

Image processing and analysis using neural networks for optometry area

Science.gov (United States)

Netto, Antonio V.; Ferreira de Oliveira, Maria C.

2002-11-01

In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

Live imaging of muscles in Drosophila metamorphosis: Towards high-throughput gene identification and function analysis.

Science.gov (United States)

Puah, Wee Choo; Wasser, Martin

2016-03-01

Time-lapse microscopy in developmental biology is an emerging tool for functional genomics. Phenotypic effects of gene perturbations can be studied non-invasively at multiple time points in chronological order. During metamorphosis of Drosophila melanogaster, time-lapse microscopy using fluorescent reporters allows visualization of alternative fates of larval muscles, which are a model for the study of genes related to muscle wasting. While doomed muscles enter hormone-induced programmed cell death, a smaller population of persistent muscles survives to adulthood and undergoes morphological remodeling that involves atrophy in early, and hypertrophy in late pupation. We developed a method that combines in vivo imaging, targeted gene perturbation and image analysis to identify and characterize genes involved in muscle development. Macrozoom microscopy helps to screen for interesting muscle phenotypes, while confocal microscopy in multiple locations over 4-5 days produces time-lapse images that are used to quantify changes in cell morphology. Performing a similar investigation using fixed pupal tissues would be too time-consuming and therefore impractical. We describe three applications of our pipeline. First, we show how quantitative microscopy can track and measure morphological changes of muscle throughout metamorphosis and analyze genes involved in atrophy. Second, our assay can help to identify genes that either promote or prevent histolysis of abdominal muscles. Third, we apply our approach to test new fluorescent proteins as live markers for muscle development. We describe mKO2 tagged Cysteine proteinase 1 (Cp1) and Troponin-I (TnI) as examples of proteins showing developmental changes in subcellular localization. Finally, we discuss strategies to improve throughput of our pipeline to permit genome-wide screens in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

GOATS Image Projection Component

Science.gov (United States)

Haber, Benjamin M.; Green, Joseph J.

2011-01-01

When doing mission analysis and design of an imaging system in orbit around the Earth, answering the fundamental question of imaging performance requires an understanding of the image products that will be produced by the imaging system. GOATS software represents a series of MATLAB functions to provide for geometric image projections. Unique features of the software include function modularity, a standard MATLAB interface, easy-to-understand first-principles-based analysis, and the ability to perform geometric image projections of framing type imaging systems. The software modules are created for maximum analysis utility, and can all be used independently for many varied analysis tasks, or used in conjunction with other orbit analysis tools.

Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity.

Science.gov (United States)

De Pasquale, Francesco; Caravasso, Chiara Falletta; Péran, Patrice; Catani, Sheila; Tuovinen, Noora; Sabatini, Umberto; Formisano, Rita

2015-01-01

The aim of this preliminary study was to present a new approach for connectivity analysis in patients with severe acquired brain injury (ABI) that overcomes some of the difficulties created by anatomical abnormalities due to the brain injury. Using a data-driven approach, resting-state structural MRI (sMRI) and functional MRI (fMRI) data from three severe ABI patients - two with disorders of consciousness (DOC) and one who had recovered consciousness (non-DOC) - were integrated and analyzed. Parameters extracted from the distribution of the connectivity values, such as mean, standard deviation and skeweness, were considered. The distribution parameters estimated seem to provide an accurate multivariate classification of the considered cases that can be summarized as follows: connectivity in the severe ABI patients with DOC was on average lower than in the severe ABI non-DOC patient and healthy subjects. The dispersion of connectivity values of the severe ABI patients, non-DOC and DOC, was comparable, however the shape of the distribution was different in the non-DOC patient. Eventually, seed-based connectivity maps of the default mode Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity network show a pattern of increasing disruption of this network from the healthy subjects to non-DOC and DOC patients. Consistent results are obtained using an ICA-based approach..

Methods of filtering the graph images of the functions

Directory of Open Access Journals (Sweden)

Олександр Григорович Бурса

2017-06-01

Full Text Available The theoretical aspects of cleaning raster images of scanned graphs of functions from digital, chromatic and luminance distortions by using computer graphics techniques have been considered. The basic types of distortions characteristic of graph images of functions have been stated. To suppress the distortion several methods, providing for high-quality of the resulting images and saving their topological features, were suggested. The paper describes the techniques developed and improved by the authors: the method of cleaning the image of distortions by means of iterative contrasting, based on the step-by-step increase in image contrast in the graph by 1%; the method of small entities distortion restoring, based on the thinning of the known matrix of contrast increase filter (the allowable dimensions of the nucleus dilution radius convolution matrix, which provide for the retention of the graph lines have been established; integration technique of the noise reduction method by means of contrasting and distortion restoring method of small entities with known σ-filter. Each method in the complex has been theoretically substantiated. The developed methods involve treatment of graph images as the entire image (global processing and its fragments (local processing. The metrics assessing the quality of the resulting image with the global and local processing have been chosen, the substantiation of the choice as well as the formulas have been given. The proposed complex methods of cleaning the graphs images of functions from grayscale image distortions is adaptive to the form of an image carrier, the distortion level in the image and its distribution. The presented results of testing the developed complex of methods for a representative sample of images confirm its effectiveness

Measurement of spatial correlation functions using image processing techniques

International Nuclear Information System (INIS)

Berryman, J.G.

1985-01-01

A procedure for using digital image processing techniques to measure the spatial correlation functions of composite heterogeneous materials is presented. Methods for eliminating undesirable biases and warping in digitized photographs are discussed. Fourier transform methods and array processor techniques for calculating the spatial correlation functions are treated. By introducing a minimal set of lattice-commensurate triangles, a method of sorting and storing the values of three-point correlation functions in a compact one-dimensional array is developed. Examples are presented at each stage of the analysis using synthetic photographs of cross sections of a model random material (the penetrable sphere model) for which the analytical form of the spatial correlations functions is known. Although results depend somewhat on magnification and on relative volume fraction, it is found that photographs digitized with 512 x 512 pixels generally have sufficiently good statistics for most practical purposes. To illustrate the use of the correlation functions, bounds on conductivity for the penetrable sphere model are calculated with a general numerical scheme developed for treating the singular three-dimensional integrals which must be evaluated

Quantification of Global Left Ventricular Function: Comparison of Multidetector Computed Tomography and Magnetic Resonance Imaging. A Meta-analysis and Review of the Current Literature

International Nuclear Information System (INIS)

Vleuten, P.A. van der; Willems, T.P.; Goette, M.J.; Tio, R.A.; Greuter, M.J.; Zijlstra, F.; Oudkerk, M.

2006-01-01

Cardiac morbidity and mortality are closely related to cardiac volumes and global left ventricular (LV) function, expressed as left ventricular ejection fraction. Accurate assessment of these parameters is required for the prediction of prognosis in individual patients as well as in entire cohorts. The current standard of reference for left ventricular function is analysis by short-axis magnetic resonance imaging. In recent years, major extensive technological improvements have been achieved in computed tomography. The most marked development has been the introduction of the multidetector CT (MDCT), which has significantly improved temporal and spatial resolutions. In order to assess the current status of MDCT for analysis of LV function, the current available literature on this subject was reviewed. The data presented in this review indicate that the global left ventricular functional parameters measured by contemporary multi-detector row systems combined with adequate reconstruction algorithms and post-processing tools show a narrow diagnostic window and are interchangeable with those obtained by MRI

New developments in paediatric cardiac functional ultrasound imaging.

Science.gov (United States)

de Korte, Chris L; Nillesen, Maartje M; Saris, Anne E C M; Lopata, Richard G P; Thijssen, Johan M; Kapusta, Livia

2014-07-01

Ultrasound imaging can be used to estimate the morphology as well as the motion and deformation of tissues. If the interrogated tissue is actively deforming, this deformation is directly related to its function and quantification of this deformation is normally referred as 'strain imaging'. Tissue can also be deformed by applying an internal or external force and the resulting, induced deformation is a function of the mechanical tissue characteristics. In combination with the load applied, these strain maps can be used to estimate or reconstruct the mechanical properties of tissue. This technique was named 'elastography' by Ophir et al. in 1991. Elastography can be used for atherosclerotic plaque characterisation, while the contractility of the heart or skeletal muscles can be assessed with strain imaging. Rather than using the conventional video format (DICOM) image information, radio frequency (RF)-based ultrasound methods enable estimation of the deformation at higher resolution and with higher precision than commercial methods using Doppler (tissue Doppler imaging) or video image data (2D speckle tracking methods). However, the improvement in accuracy is mainly achieved when measuring strain along the ultrasound beam direction, so it has to be considered a 1D technique. Recently, this method has been extended to multiple directions and precision further improved by using spatial compounding of data acquired at multiple beam steered angles. Using similar techniques, the blood velocity and flow can be determined. RF-based techniques are also beneficial for automated segmentation of the ventricular cavities. In this paper, new developments in different techniques of quantifying cardiac function by strain imaging, automated segmentation, and methods of performing blood flow imaging are reviewed and their application in paediatric cardiology is discussed.

Chronic antiepileptic drug use and functional network efficiency: A functional magnetic resonance imaging study.

Science.gov (United States)

van Veenendaal, Tamar M; IJff, Dominique M; Aldenkamp, Albert P; Lazeron, Richard H C; Hofman, Paul A M; de Louw, Anton J A; Backes, Walter H; Jansen, Jacobus F A

2017-06-28

To increase our insight in the neuronal mechanisms underlying cognitive side-effects of antiepileptic drug (AED) treatment. The relation between functional magnetic resonance-acquired brain network measures, AED use, and cognitive function was investigated. Three groups of patients with epilepsy with a different risk profile for developing cognitive side effects were included: A "low risk" category (lamotrigine or levetiracetam, n = 16), an "intermediate risk" category (carbamazepine, oxcarbazepine, phenytoin, or valproate, n = 34) and a "high risk" category (topiramate, n = 5). Brain connectivity was assessed using resting state functional magnetic resonance imaging and graph theoretical network analysis. The Computerized Visual Searching Task was used to measure central information processing speed, a common cognitive side effect of AED treatment. Central information processing speed was lower in patients taking AEDs from the intermediate and high risk categories, compared with patients from the low risk category. The effect of risk category on global efficiency was significant ( P effect on the clustering coefficient (ANCOVA, P > 0.2). Also no significant associations between information processing speed and global efficiency or the clustering coefficient (linear regression analysis, P > 0.15) were observed. Only the four patients taking topiramate show aberrant network measures, suggesting that alterations in functional brain network organization may be only subtle and measureable in patients with more severe cognitive side effects.

Image-potential states and work function of graphene

International Nuclear Information System (INIS)

Niesner, Daniel; Fauster, Thomas

2014-01-01

Image-potential states of graphene on various substrates have been investigated by two-photon photoemission and scanning tunneling spectroscopy. They are used as a probe for the graphene-substrate interaction and resulting changes in the (local) work function. The latter is driven by the work function difference between graphene and the substrate. This results in a charge transfer which also contributes to core-level shifts in x-ray photoemission. In this review article, we give an overview over the theoretical models and the experimental data for image-potential states and work function of graphene on various substrates. (topical review)

Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

Science.gov (United States)

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2017-01-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

Image Analysis

DEFF Research Database (Denmark)

The 19th Scandinavian Conference on Image Analysis was held at the IT University of Copenhagen in Denmark during June 15-17, 2015. The SCIA conference series has been an ongoing biannual event for more than 30 years and over the years it has nurtured a world-class regional research and development...... area within the four participating Nordic countries. It is a regional meeting of the International Association for Pattern Recognition (IAPR). We would like to thank all authors who submitted works to this year’s SCIA, the invited speakers, and our Program Committee. In total 67 papers were submitted....... The topics of the accepted papers range from novel applications of vision systems, pattern recognition, machine learning, feature extraction, segmentation, 3D vision, to medical and biomedical image analysis. The papers originate from all the Scandinavian countries and several other European countries...

Functional imaging of the sensorimotor cortex using an ultra-fast MR imaging method

International Nuclear Information System (INIS)

Tsunoda, Akira; Nakajima, Yasoichi; Sato, Kiyoshi; Katayama, Jin; Machida, Yoshio; Nozaki, Seiji; Makita, Jun-ichi.

1996-01-01

The aim of this study was to assess changes in brain activity during a motor task and variable sensory stimulation using echo planar imaging, which represents the fastest clinically useful imaging technique available. The subjects of this study were 11 healthy volunteers, 4 males and 11 females, with an average of 26.4 years. The subjects were instructed to tap the fingers of one hand as the motor task. Compressed air was applied 5 times a second as 'simple' sensory stimulation. Simple figures were drawn on the subjects palm as 'complex' sensory stimulation. In all cases, functional imaging was performed by T 2 * -weighted echo planar imaging (TE=53 msec, TR=3000 msec, flip angle=90 degrees, matrix 64 x 64, FOV=205 mm, slice thickness=8 mm) alternately at rest and during the task (intervals: 30 sec). A total of 60 images was collected in 3 minutes. Images obtained by subtracting images at rest and during the task were analyzed. Almost all subjects showed a transient signal increase in the contralateral paracentral region during simple sensory stimulation. Continuous signal increases in the contra- and/or ipsi-lateral para-central region were observed durirg complex sensory stimulation. Some exhibited signal increases in the parietal or frontal association cortex, but they disappeared when subject's attention was distracted during stimulation. All subjects displayed signal increases in the contralateral para-central region during the motor task. Some of them exhibited signal increases in the medial frontal area (supplementary motor area) and ipsilateral para-central region. These results suggest that the signal increases of functional MRI reflect not only simple reactions to stimulation but higher cerebral function as well. (J.P.N.)

Progress in clinical research and application of resting state functional brain imaging

International Nuclear Information System (INIS)

Long Miaomiao; Ni Hongyan

2013-01-01

Resting state functional brain imaging experimental design is free of stimulus task and offers various parametric maps through different data-driven post processing methods with endogenous BOLD signal changes as the source of imaging. Mechanism of resting state brain activities could be extensively studied with improved patient compliance and clinical application compared with task related functional brain imaging. Also resting state functional brain imaging can be used as a method of data acquisition, with implicit neuronal activity as a kind of experimental design, to reveal characteristic brain activities of epileptic patient. Even resting state functional brain imaging data processing method can be used to analyze task related functional MRI data, opening new horizons of task related functional MRI study. (authors)

Magnetic resonance imaging of respiratory movement and lung function

International Nuclear Information System (INIS)

Tetzlaff, R.; Eichinger, M.

2009-01-01

Lung function measurements are the domain of spirometry or plethysmography. These methods have proven their value in clinical practice, nevertheless, being global measurements the functional indices only describe the sum of all functional units of the lung. Impairment of only a single component of the respiratory pump or of a small part of lung parenchyma can be compensated by unaffected lung tissue. Dynamic imaging can help to detect such local changes and lead to earlier adapted therapy. Magnetic resonance imaging (MRI) seems to be perfect for this application as it is not hampered by image distortion as is projection radiography and it does not expose the patient to potentially harmful radiation like computed tomography. Unfortunately, lung parenchyma is not easy to image using MRI due to its low signal intensity. For this reason first applications of MRI in lung function measurements concentrated on the movement of the thoracic wall and the diaphragm. Recent technical advances in MRI however might allow measurements of regional dynamics of the lungs. (orig.) [de

Multiscale Geoscene Segmentation for Extracting Urban Functional Zones from VHR Satellite Images

Directory of Open Access Journals (Sweden)

Xiuyuan Zhang

2018-02-01

Full Text Available Urban functional zones, such as commercial, residential, and industrial zones, are basic units of urban planning, and play an important role in monitoring urbanization. However, historical functional-zone maps are rarely available for cities in developing countries, as traditional urban investigations focus on geographic objects rather than functional zones. Recent studies have sought to extract functional zones automatically from very-high-resolution (VHR satellite images, and they mainly concentrate on classification techniques, but ignore zone segmentation which delineates functional-zone boundaries and is fundamental to functional-zone analysis. To resolve the issue, this study presents a novel segmentation method, geoscene segmentation, which can identify functional zones at multiple scales by aggregating diverse urban objects considering their features and spatial patterns. In experiments, we applied this method to three Chinese cities—Beijing, Putian, and Zhuhai—and generated detailed functional-zone maps with diverse functional categories. These experimental results indicate our method effectively delineates urban functional zones with VHR imagery; different categories of functional zones extracted by using different scale parameters; and spatial patterns that are more important than the features of individual objects in extracting functional zones. Accordingly, the presented multiscale geoscene segmentation method is important for urban-functional-zone analysis, and can provide valuable data for city planners.

[Future perspectives for diagnostic imaging in urology: from anatomic and functional to molecular imaging].

Science.gov (United States)

Macis, Giuseppe; Di Giovanni, Silvia; Di Franco, Davide; Bonomo, Lorenzo

2013-01-01

The future approach of diagnostic imaging in urology follows the technological progress, which made the visualization of in vivo molecular processes possible. From anatomo-morphological diagnostic imaging and through functional imaging molecular radiology is reached. Based on molecular probes, imaging is aimed at assessing the in vivo molecular processes, their physiology and function at cellular level. The future imaging will investigate the complex tumor functioning as metabolism, aerobic glycolysis in particular, angiogenesis, cell proliferation, metastatic potential, hypoxia, apoptosis and receptors expressed by neoplastic cells. Methods for performing molecular radiology are CT, MRI, PET-CT, PET-MRI, SPECT and optical imaging. Molecular ultrasound combines technological advancement with targeted contrast media based on microbubbles, this allowing the selective registration of microbubble signal while that of stationary tissues is suppressed. An experimental study was carried out where the ultrasound molecular probe BR55 strictly bound to prostate tumor results in strong enhancement in the early phase after contrast, this contrast being maintained in the late phase. This late enhancement is markedly significant for the detection of prostatic cancer foci and to guide the biopsy sampling. The 124I-cG250 molecular antibody which is strictly linked to cellular carbonic anhydrase IX of clear cell renal carcinoma, allows the acquisition of diagnostic PET images of clear cell renal carcinoma without biopsy. This WG-250 (RENCAREX) antibody was used as a therapy in metastatic clear cell renal carcinoma. Future advancements and applications will result in early cancer diagnosis, personalized therapy that will be specific according to the molecular features of cancer and leading to the development of catheter-based multichannel molecular imaging devices for cystoscopy-based molecular imaging diagnosis and intervention.

External marker-based fusion of functional and morphological images

International Nuclear Information System (INIS)

Kremp, S.; Schaefer, A.; Alexander, C.; Kirsch, C.M.

1999-01-01

The fusion of image data resulting from methods oriented toward morphology like CT, MRI with functional information coming from nuclear medicine (SPECT, PET) is frequently applied to allow for a better association between functional findings and anatomical structures. A new software was developed to provide image fusion using PET, SPECT, MRI and CT data within a short processing periode for brain as well as whole body examinations in particular thorax and abdomen. The software utilizes external markers (brain) or anatomical landmarks (thorax) for correlation. The fusion requires a periode of approx. 15 min. The examples shown emphasize the high gain in diagnostic information by fusing image data of anatomical and functional methods. (orig.) [de

Nephrus: expert system model in intelligent multilayers for evaluation of urinary system based on scintigraphic image analysis

International Nuclear Information System (INIS)

Silva, Jorge Wagner Esteves da; Schirru, Roberto; Boasquevisque, Edson Mendes

1999-01-01

Renal function can be measured noninvasively with radionuclides in a extremely safe way compared to other diagnosis techniques. Nevertheless, due to the fact that radioactive materials are used in this procedure, it is necessary to maximize its benefits, therefore all efforts are justifiable in the development of data analysis support tools for this diagnosis modality. The objective of this work is to develop a prototype for a system model based on Artificial Intelligence devices able to perform functions related to cintilographic image analysis of the urinary system. Rules used by medical experts in the analysis of images obtained with 99m Tc+DTPA and /or 99m Tc+DMSA were modeled and a Neural Network diagnosis technique was implemented. Special attention was given for designing programs user-interface. Human Factor Engineering techniques were taking in account allowing friendliness and robustness. The image segmentation adopts a model based on Ideal ROIs, which represent the normal anatomic concept for urinary system organs. Results obtained using Artificial Neural Networks for qualitative image analysis and knowledge model constructed show the feasibility of Artificial Neural Networks for qualitative image analysis and knowledge model constructed show feasibility of Artificial Intelligence implementation that uses inherent abilities of each technique in the medical diagnosis image analysis. (author)

Toward a functional neuroanatomy of dysthymia: a functional magnetic resonance imaging study.

Science.gov (United States)

Ravindran, Arun V; Smith, Andra; Cameron, Colin; Bhatla, Raj; Cameron, Ian; Georgescu, Tania M; Hogan, Matthew J

2009-12-01

Dysthymia is a common mood disorder. Recent studies have confirmed the neurobiological and treatment response overlap of dysthymia with major depression. There are no previous published studies of functional magnetic resonance imaging (fMRI) in dysthymia. fMRI was used to compare neural processing of 17 unmedicated dysthymic patients with 17 age, sex, and education-matched control subjects in a mood induction paradigm using the International Affective Pictures System (IAPS). Using a random effects analysis to compare the groups, the results revealed that the dysthymic patients had significantly reduced activation in the dorsolateral prefrontal cortex compared to controls. The dysthymic patients exhibited increased activation in the amygdala, anterior cingulate and insula compared to controls and these differences were more evident when processing negative than positive images. This study included both early and late subtypes of dysthymia, and participants were only imaged at one time point, which may limit the generalizability of the results. The findings suggest the involvement of the prefrontal cortex, anterior cingulate, amygdala, and insula in the neural circuitry underlying dysthymia. It is suggested that altered activation in some of these neural regions may be a common substrate for depressive disorders in general while others may relate specifically to symptom characteristics and the chronic course of dysthymia. These findings are particularly striking given the history of this deceptively mild disorder which is still confused by some with character pathology.

Processing of food, body and emotional stimuli in anorexia nervosa: a systematic review and meta-analysis of functional magnetic resonance imaging studies.

Science.gov (United States)

Zhu, Yikang; Hu, Xiaochen; Wang, Jijun; Chen, Jue; Guo, Qian; Li, Chunbo; Enck, Paul

2012-11-01

The characteristics of the cognitive processing of food, body and emotional information in patients with anorexia nervosa (AN) are debatable. We reviewed functional magnetic resonance imaging studies to assess whether there were consistent neural basis and networks in the studies to date. Searching PubMed, Ovid, Web of Science, The Cochrane Library and Google Scholar between January 1980 and May 2012, we identified 17 relevant studies. Activation likelihood estimation was used to perform a quantitative meta-analysis of functional magnetic resonance imaging studies. For both food stimuli and body stimuli, AN patients showed increased hemodynamic response in the emotion-related regions (frontal, caudate, uncus, insula and temporal) and decreased activation in the parietal region. Although no robust brain activation has been found in response to emotional stimuli, emotion-related neural networks are involved in the processing of food and body stimuli among AN. It suggests that negative emotional arousal is related to cognitive processing bias of food and body stimuli in AN. Copyright © 2012 John Wiley & Sons, Ltd and Eating Disorders Association.

Image analysis for the automated estimation of clonal growth and its application to the growth of smooth muscle cells.

Science.gov (United States)

Gavino, V C; Milo, G E; Cornwell, D G

1982-03-01

Image analysis was used for the automated measurement of colony frequency (f) and colony diameter (d) in cultures of smooth muscle cells, Initial studies with the inverted microscope showed that number of cells (N) in a colony varied directly with d: log N = 1.98 log d - 3.469 Image analysis generated the complement of a cumulative distribution for f as a function of d. The number of cells in each segment of the distribution function was calculated by multiplying f and the average N for the segment. These data were displayed as a cumulative distribution function. The total number of colonies (fT) and the total number of cells (NT) were used to calculate the average colony size (NA). Population doublings (PD) were then expressed as log2 NA. Image analysis confirmed previous studies in which colonies were sized and counted with an inverted microscope. Thus, image analysis is a rapid and automated technique for the measurement of clonal growth.

Functional magnetic resonance imaging of the primary motor cortex ...

Indian Academy of Sciences (India)

Unknown

Abbreviations used: BOLD, Blood oxygenation level dependent; CBF, cerebral blood flow; fMRI, functional magnetic resonance imaging; EPI, eco-planar imaging; FOV, field of view; MRI, Magnetic resonance imaging; MRS, magnetic resonance spectroscopy;. PET, position emission tomography; rCBF, regional cerebral ...

Whole-body imaging of whole-organ, subresolution, basic functional unit (BFU) perfusion characteristics

Science.gov (United States)

Dong, Yue; Ritman, Erik L.

2008-08-01

A BFU is an organ's smallest assembly of diverse cells that functions like the organ, such as the liver's hepatic lobules. There are approximately 107 BFUs in a human organ. These 100-200 μm structures are perfused by capillaries fed by a terminal arteriole (15μm diameter). BFU sizes, function and number per organ vary with disease, either by loss of BFUs and/or their decrease in function. The BFU is the upper limit of a spherical assembly of cells, immersed in a suitably nutrient medium, which can survive without its own blood supply. However, each BFU has its own blood supply to support the extra energy and/or solutes needed for providing its physiological function (e.g., contraction or secretion). A BFU function is best evaluated by its micro-perfusion, which can be readily evaluated with whole-body CT. Resolution of individual BFUs within in-situ organs, using clinical imaging devices, would require high radiation doses and/or the intolerably long scan-durations needed for suitable signal-to-noise image-data. However, it is possible to obtain a statistical description of the BFU number, size and function from wholebody CT by way of a model. In this study we demonstrate this capability by using the distribution of myocardial terminal arteriolar perfusion territories by way of a nested, multiple, regions-of-interest analysis of the heart wall imaged during transient opacification of its blood supply.

Functional MR imaging of the cervical spine in patients with rheumatoid arthritis

International Nuclear Information System (INIS)

Allmann, K.H.; Uhl, M.; Uhrmeister, P.; Neumann, K.; Langer, M.; Kempis, J. von

1998-01-01

Purpose: To evaluate functional MR imaging in patients with rheumatoid arthritis (RA) involving the cervical spine. Material and Methods: We used a device that allows MR examination to be made of the cervical spine in infinitely variable degrees of flexion and extension. Dynamic functional MR imaging was performed on 25 patients with RA. Results: Functional MR imaging was able to show the degree of vertebral instability of the occipito-atlantal or atlanto-axial level as well as the subaxial level. By performing functional MR imaging, we were able to demonstrate the extent of synovial tissue around the dens, and the impingement and displacement of the spinal cord during flexion and extension. The basilar impression, the cord impingement into the foramen magnum, the cord compression, the slipping of vertebrae, and the angulation of the cord were all much more evident in functional than in static MR imaging. Conclusion: Functional MR imaging provided additional information in patients with RA, and is valuable in patients who have a normal MR study in the neutral position and yet have signs of a neurological deficit. Functional MR imaging is important in the planning of stabilizing operations of the cervical spine. (orig.)

Advanced Magnetic Resonance Imaging techniques to probe muscle structure and function

Science.gov (United States)

Malis, Vadim

Structural and functional Magnetic Resonance Imaging (MRI) studies of skeletal muscle allow the elucidation of muscle physiology under normal and pathological conditions. Continuing on the efforts of the Muscle Imaging and Modeling laboratory, the focus of the thesis is to (i) extend and refine two challenging imaging modalities: structural imaging using Diffusion Tensor Imaging (DTI) and functional imaging based on Velocity Encoded Phase Contrast Imaging (VE-PC) and (ii) apply these methods to explore age related structure and functional differences of the gastrocnemius muscle. Diffusion Tensor Imaging allows the study of tissue microstructure as well as muscle fiber architecture. The images, based on an ultrafast single shot Echo Planar Imaging (EPI) sequence, suffer from geometric distortions and low signal to noise ratio. A processing pipeline was developed to correct for distortions and to improve image Signal to Noise Ratio (SNR). DTI acquired on a senior and young cohort of subjects were processed through the pipeline and differences in DTI derived indices and fiber architecture between the two cohorts were explored. The DTI indices indicated that at the microstructural level, fiber atrophy was accompanied with a reduction in fiber volume fraction. At the fiber architecture level, fiber length and pennation angles decreased with age that potentially contribute to the loss of muscle force with age. Velocity Encoded Phase Contrast imaging provides tissue (e.g. muscle) velocity at each voxel which allows the study of strain and Strain Rate (SR) under dynamic conditions. The focus of the thesis was to extract 2D strain rate tensor maps from the velocity images and apply the method to study age related differences. The tensor mapping can potentially provide unique information on the extracellular matrix and lateral transmission the role of these two elements has recently emerged as important determinants of force loss with age. In the cross sectional study on

Digital image analysis

DEFF Research Database (Denmark)

Riber-Hansen, Rikke; Vainer, Ben; Steiniche, Torben

2012-01-01

Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides...... reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques....

Image sequence analysis

CERN Document Server

1981-01-01

The processing of image sequences has a broad spectrum of important applica­ tions including target tracking, robot navigation, bandwidth compression of TV conferencing video signals, studying the motion of biological cells using microcinematography, cloud tracking, and highway traffic monitoring. Image sequence processing involves a large amount of data. However, because of the progress in computer, LSI, and VLSI technologies, we have now reached a stage when many useful processing tasks can be done in a reasonable amount of time. As a result, research and development activities in image sequence analysis have recently been growing at a rapid pace. An IEEE Computer Society Workshop on Computer Analysis of Time-Varying Imagery was held in Philadelphia, April 5-6, 1979. A related special issue of the IEEE Transactions on Pattern Anal­ ysis and Machine Intelligence was published in November 1980. The IEEE Com­ puter magazine has also published a special issue on the subject in 1981. The purpose of this book ...

Role of intensity transformation function for enhancement of bone scintigraphic images.

Science.gov (United States)

Pandey, Anil Kumar; Dhiman, Vishali; Sharma, Akshima; ArunRaj, Sreedharan Thankarajan; Baghel, Vivek; Patel, Chetan; Sharma, Param Dev; Bal, Chandrasekhar; Kumar, Rakesh

2018-03-29

The bone scintigraphic image might exceed the dynamic range (the ratio between the highest and the lowest brightness a monitor is capable of displaying) of display monitor. In this case, a high intensity area, and loss of the details of other structures in the displayed image makes the clinical interpretation a challenging task. We have investigated the role of intensity transformation function for enhancement of these types of images. Methods: Forty high dynamic range bone scintigraphic images were processed using intensity transformation (IT) function. The IT function has two parameters: threshold and slope. Keeping the threshold equal to mean counts of the image, the value of slope was varied from 1 to 20. In-house application program written in MATLAB R2013b was used to process images. Twenty output images corresponding to one input image were visually inspected by two experienced nuclear medicine (NM) physicians to select diagnostic quality images, and from their selection the standardized slope (value of slope parameter) that produced maximum numbers of diagnostic images was determined. They also rated the image quality of input and output images (at standardized slope) on scale 1 to 5 [where 1 is for poor and 5 if for the excellent diagnostic quality]. Student's t-test was used to test the significance of difference between the mean image quality score assigned to input and processed images at significance level α = 0.05. Results: The application of IT functions with standardized parameters significantly improved the quality of high dynamic range bone scintigraphic images ( P enhancement. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Fetal functional imaging portrays heterogeneous development of emerging human brain networks

Directory of Open Access Journals (Sweden)

Andras eJakab

2014-10-01

Full Text Available The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st – 38th gestational weeks (GW with a network-based statistical inference approach. The overall connectivity network, short range and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29. GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW, temporal (peak: 26 GW, frontal (peak: 26.4 GW and parietal expansion (peak: 27.5 GW. We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macroconnectivity.

Fetal functional imaging portrays heterogeneous development of emerging human brain networks.

Science.gov (United States)

Jakab, András; Schwartz, Ernst; Kasprian, Gregor; Gruber, Gerlinde M; Prayer, Daniela; Schöpf, Veronika; Langs, Georg

2014-01-01

The functional connectivity architecture of the adult human brain enables complex cognitive processes, and exhibits a remarkably complex structure shared across individuals. We are only beginning to understand its heterogeneous structure, ranging from a strongly hierarchical organization in sensorimotor areas to widely distributed networks in areas such as the parieto-frontal cortex. Our study relied on the functional magnetic resonance imaging (fMRI) data of 32 fetuses with no detectable morphological abnormalities. After adapting functional magnetic resonance acquisition, motion correction, and nuisance signal reduction procedures of resting-state functional data analysis to fetuses, we extracted neural activity information for major cortical and subcortical structures. Resting fMRI networks were observed for increasing regional functional connectivity from 21st to 38th gestational weeks (GWs) with a network-based statistical inference approach. The overall connectivity network, short range, and interhemispheric connections showed sigmoid expansion curve peaking at the 26-29 GW. In contrast, long-range connections exhibited linear increase with no periods of peaking development. Region-specific increase of functional signal synchrony followed a sequence of occipital (peak: 24.8 GW), temporal (peak: 26 GW), frontal (peak: 26.4 GW), and parietal expansion (peak: 27.5 GW). We successfully adapted functional neuroimaging and image post-processing approaches to correlate macroscopical scale activations in the fetal brain with gestational age. This in vivo study reflects the fact that the mid-fetal period hosts events that cause the architecture of the brain circuitry to mature, which presumably manifests in increasing strength of intra- and interhemispheric functional macro connectivity.

Functional magnetic resonance imaging phase synchronization as a measure of dynamic functional connectivity.

Science.gov (United States)

Glerean, Enrico; Salmi, Juha; Lahnakoski, Juha M; Jääskeläinen, Iiro P; Sams, Mikko

2012-01-01

Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on an fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04-0.07 Hz) was used in the PS analysis to avoid artifactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A MATLAB toolbox FUNPSY ( http://becs.aalto.fi/bml/software.html ) is openly available for using these metrics in fMRI data analysis.

The apport of functional cerebral imaging in the psychiatric pathology

International Nuclear Information System (INIS)

Maktouf, Ch.; Kotzki, P.O.; Humbert, Th.

1992-01-01

Recent advances in medical brain imaging using structural and functional brain imaging techniques have contributed to the investigation of the living human brain. These new techniques hold great promise for the evaluation and understanding mental disorders. We report the position emission tomography (PET) and the more widely available single emission photon (SPECT) studies, as functional brain imaging, to assess regional cerebral metabolism and blood flow in psychiatric illness. (author)

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

Applications of wavelets in morphometric analysis of medical images

Science.gov (United States)

Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

2003-11-01

Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

Science.gov (United States)

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Introduction to Medical Image Analysis

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

High resolution multiplexed functional imaging in live embryos (Conference Presentation)

Science.gov (United States)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Fourier multiplexed fluorescence lifetime imaging (FmFLIM) scanning laser optical tomography (FmFLIM-SLOT) combines FmFLIM and Scanning laser optical tomography (SLOT) to perform multiplexed 3D FLIM imaging of live embryos. The system had demonstrate multiplexed functional imaging of zebrafish embryos genetically express Foster Resonant Energy Transfer (FRET) sensors. However, previous system has a 20 micron resolution because the focused Gaussian beam diverges quickly from the focused plane, makes it difficult to achieve high resolution imaging over a long projection depth. Here, we present a high-resolution FmFLIM-SLOT system with achromatic Bessel beam, which achieves 3 micron resolution in 3D deep tissue imaging. In Bessel-FmFLIM-SLOT, multiple laser excitation lines are firstly intensity modulated by a Michelson interferometer with a spinning polygon mirror optical delay line, which enables Fourier multiplexed multi-channel lifetime measurements. Then, a spatial light modulator and a prism are used to transform the modulated Gaussian laser beam to an achromatic Bessel beam. The achromatic Bessel beam scans across the whole specimen with equal angular intervals as sample rotated. After tomography reconstruction and the frequency domain lifetime analysis method, both the 3D intensity and lifetime image of multiple excitation-emission can be obtained. Using Bessel-FmFLIM-SLOT system, we performed cellular-resolution FLIM tomography imaging of live zebrafish embryo. Genetically expressed FRET sensors in these embryo will allow non-invasive observation of multiple biochemical processes in vivo.

Wavefront analysis for plenoptic camera imaging

International Nuclear Information System (INIS)

Luan Yin-Sen; Xu Bing; Yang Ping; Tang Guo-Mao

2017-01-01

The plenoptic camera is a single lens stereo camera which can retrieve the direction of light rays while detecting their intensity distribution. In this paper, to reveal more truths of plenoptic camera imaging, we present the wavefront analysis for the plenoptic camera imaging from the angle of physical optics but not from the ray tracing model of geometric optics. Specifically, the wavefront imaging model of a plenoptic camera is analyzed and simulated by scalar diffraction theory and the depth estimation is redescribed based on physical optics. We simulate a set of raw plenoptic images of an object scene, thereby validating the analysis and derivations and the difference between the imaging analysis methods based on geometric optics and physical optics are also shown in simulations. (paper)

Comparative analysis of imaging configurations and objectives for Fourier microscopy.

Science.gov (United States)

Kurvits, Jonathan A; Jiang, Mingming; Zia, Rashid

2015-11-01

Fourier microscopy is becoming an increasingly important tool for the analysis of optical nanostructures and quantum emitters. However, achieving quantitative Fourier space measurements requires a thorough understanding of the impact of aberrations introduced by optical microscopes that have been optimized for conventional real-space imaging. Here we present a detailed framework for analyzing the performance of microscope objectives for several common Fourier imaging configurations. To this end, we model objectives from Nikon, Olympus, and Zeiss using parameters that were inferred from patent literature and confirmed, where possible, by physical disassembly. We then examine the aberrations most relevant to Fourier microscopy, including the alignment tolerances of apodization factors for different objective classes, the effect of magnification on the modulation transfer function, and vignetting-induced reductions of the effective numerical aperture for wide-field measurements. Based on this analysis, we identify an optimal objective class and imaging configuration for Fourier microscopy. In addition, the Zemax files for the objectives and setups used in this analysis have been made publicly available as a resource for future studies.

REST: a toolkit for resting-state functional magnetic resonance imaging data processing.

Directory of Open Access Journals (Sweden)

Xiao-Wei Song

Full Text Available Resting-state fMRI (RS-fMRI has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST. REST was developed in MATLAB with graphical user interface (GUI. After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF, and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.. REST is an open-source package and is freely available at http://www.restfmri.net.

Imaging gait analysis: An fMRI dual task study.

Science.gov (United States)

Bürki, Céline N; Bridenbaugh, Stephanie A; Reinhardt, Julia; Stippich, Christoph; Kressig, Reto W; Blatow, Maria

2017-08-01

In geriatric clinical diagnostics, gait analysis with cognitive-motor dual tasking is used to predict fall risk and cognitive decline. To date, the neural correlates of cognitive-motor dual tasking processes are not fully understood. To investigate these underlying neural mechanisms, we designed an fMRI paradigm to reproduce the gait analysis. We tested the fMRI paradigm's feasibility in a substudy with fifteen young adults and assessed 31 healthy older adults in the main study. First, gait speed and variability were quantified using the GAITRite © electronic walkway. Then, participants lying in the MRI-scanner were stepping on pedals of an MRI-compatible stepping device used to imitate gait during functional imaging. In each session, participants performed cognitive and motor single tasks as well as cognitive-motor dual tasks. Behavioral results showed that the parameters of both gait analyses, GAITRite © and fMRI, were significantly positively correlated. FMRI results revealed significantly reduced brain activation during dual task compared to single task conditions. Functional ROI analysis showed that activation in the superior parietal lobe (SPL) decreased less from single to dual task condition than activation in primary motor cortex and in supplementary motor areas. Moreover, SPL activation was increased during dual tasks in subjects exhibiting lower stepping speed and lower executive control. We were able to simulate walking during functional imaging with valid results that reproduce those from the GAITRite © gait analysis. On the neural level, SPL seems to play a crucial role in cognitive-motor dual tasking and to be linked to divided attention processes, particularly when motor activity is involved.

Image-analysis techniques for investigation localized corrosion processes

International Nuclear Information System (INIS)

Quinn, M.J.; Bailey, M.G.; Ikeda, B.M.; Shoesmith, D.W.

1993-12-01

We have developed a procedure for determining the mode and depth of penetration of localized corrosion by combining metallography and image analysis of corroded coupons. Two techniques, involving either a face-profiling or an edge-profiling procedure, have been developed. In the face-profiling procedure, successive surface grindings and image analyses were performed until corrosion was no longer visible. In this manner, the distribution of corroded sites on the surface and the total area of the surface corroded were determined as a function of depth into the specimen. In the edge-profiling procedure, surface grinding exposed successive cross sections of the corroded region. Image analysis of the cross section quantified the distribution of depths across the corroded section, and a three-dimensional distribution of penetration depths was obtained. To develop these procedures, we used artificially creviced Grade-2 titanium specimens that were corroded in saline solutions containing various amounts of chloride maintained at various fixed temperatures (105 to 150 degrees C) using a previously developed galvanic-coupling technique. We discuss some results from these experiments to illustrate how the procedures developed can be applied to a real corroded system. (author). 6 refs., 4 tabs., 21 figs

Multimodality image analysis work station

International Nuclear Information System (INIS)

Ratib, O.; Huang, H.K.

1989-01-01

The goal of this project is to design and implement a PACS (picture archiving and communication system) workstation for quantitative analysis of multimodality images. The Macintosh II personal computer was selected for its friendly user interface, its popularity among the academic and medical community, and its low cost. The Macintosh operates as a stand alone workstation where images are imported from a central PACS server through a standard Ethernet network and saved on a local magnetic or optical disk. A video digitizer board allows for direct acquisition of images from sonograms or from digitized cine angiograms. The authors have focused their project on the exploration of new means of communicating quantitative data and information through the use of an interactive and symbolic user interface. The software developed includes a variety of image analysis, algorithms for digitized angiograms, sonograms, scintigraphic images, MR images, and CT scans

Functional dynamic MR imaging and pharmacokinetics of Gd-DTPA in patients with renal failure

International Nuclear Information System (INIS)

Krestin, G.P.; Neufang, K.F.R.; Friedmann, G.; Clauss, W.; Schuhmann-Giampieri, G.; Stoeckl, B.

1989-01-01

This paper reports excretion of Gd-DTPA analyzed in 20 patients with renal parenchymal disease and decreased creatinine clearance (20-80 mL/min) and compared with excretion in five patients with normal renal function. All 25 underwent a dynamic MR study that employed fast gradient-echo sequences with single images during breath holding. The time between appearance of the contrast agent in the renal cortex and signal intensity drop in the medulla was an indicator of glomerular filtration rate and correlated well with creatinine clearance values. Fractionate urine collection and serum analysis up to 120 hours showed a prolonged but complete (98%) elimination of Gd-DTPA. Renal functional parameters did not change after administration of Gd-DTPA, and no nephrotoxic effects were observed. Thus, MR imaging provides a good quantitative evaluation of the glomerular filtration rate; moreover, administration of Gd-DTPA in patients with renal failure does not impair excretory function and can therefore be safely applied in patients with reduced excretory function

Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets.

Directory of Open Access Journals (Sweden)

Ilya Belevich

2016-01-01

Full Text Available Understanding the structure-function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.

Imaging structural and functional brain networks in temporal lobe epilepsy

Science.gov (United States)

Bernhardt, Boris C.; Hong, SeokJun; Bernasconi, Andrea; Bernasconi, Neda

2013-01-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy. PMID:24098281

Imaging structural and functional brain networks in temporal lobe epilepsy.

Science.gov (United States)

Bernhardt, Boris C; Hong, Seokjun; Bernasconi, Andrea; Bernasconi, Neda

2013-10-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.

Imaging structural and functional brain networks in temporal lobe epilepsy

Directory of Open Access Journals (Sweden)

Boris eBernhardt

2013-10-01

Full Text Available Early imaging studies in temporal lobe epilepsy (TLE focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.

Method for estimating modulation transfer function from sample images.

Science.gov (United States)

Saiga, Rino; Takeuchi, Akihisa; Uesugi, Kentaro; Terada, Yasuko; Suzuki, Yoshio; Mizutani, Ryuta

2018-02-01

The modulation transfer function (MTF) represents the frequency domain response of imaging modalities. Here, we report a method for estimating the MTF from sample images. Test images were generated from a number of images, including those taken with an electron microscope and with an observation satellite. These original images were convolved with point spread functions (PSFs) including those of circular apertures. The resultant test images were subjected to a Fourier transformation. The logarithm of the squared norm of the Fourier transform was plotted against the squared distance from the origin. Linear correlations were observed in the logarithmic plots, indicating that the PSF of the test images can be approximated with a Gaussian. The MTF was then calculated from the Gaussian-approximated PSF. The obtained MTF closely coincided with the MTF predicted from the original PSF. The MTF of an x-ray microtomographic section of a fly brain was also estimated with this method. The obtained MTF showed good agreement with the MTF determined from an edge profile of an aluminum test object. We suggest that this approach is an alternative way of estimating the MTF, independently of the image type. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rapid Analysis and Exploration of Fluorescence Microscopy Images

OpenAIRE

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason; Steininger, Robert J; Wu, Lani; Altschuler, Steven

2014-01-01

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard.

Functional Object Analysis

DEFF Research Database (Denmark)

Raket, Lars Lau

We propose a direction it the field of statistics which we will call functional object analysis. This subfields considers the analysis of functional objects defined on continuous domains. In this setting we will focus on model-based statistics, with a particularly emphasis on mixed......-effect formulations, where the observed functional signal is assumed to consist of both fixed and random functional effects. This thesis takes the initial steps toward the development of likelihood-based methodology for functional objects. We first consider analysis of functional data defined on high...

Functional imaging of sleep vertex sharp transients.

Science.gov (United States)

Stern, John M; Caporro, Matteo; Haneef, Zulfi; Yeh, Hsiang J; Buttinelli, Carla; Lenartowicz, Agatha; Mumford, Jeanette A; Parvizi, Josef; Poldrack, Russell A

2011-07-01

The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI). Simultaneous EEG and fMRI were recorded from seven individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3. Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present. The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch. The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Mesh Processing in Medical Image Analysis

DEFF Research Database (Denmark)

The following topics are dealt with: mesh processing; medical image analysis; interactive freeform modeling; statistical shape analysis; clinical CT images; statistical surface recovery; automated segmentation; cerebral aneurysms; and real-time particle-based representation....

Image quality analysis of digital mammographic equipments

Energy Technology Data Exchange (ETDEWEB)

Mayo, P.; Pascual, A.; Verdu, G. [Valencia Univ. Politecnica, Chemical and Nuclear Engineering Dept. (Spain); Rodenas, F. [Valencia Univ. Politecnica, Applied Mathematical Dept. (Spain); Campayo, J.M. [Valencia Univ. Hospital Clinico, Servicio de Radiofisica y Proteccion Radiologica (Spain); Villaescusa, J.I. [Hospital Clinico La Fe, Servicio de Proteccion Radiologica, Valencia (Spain)

2006-07-01

The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

Image quality analysis of digital mammographic equipments

International Nuclear Information System (INIS)

Mayo, P.; Pascual, A.; Verdu, G.; Rodenas, F.; Campayo, J.M.; Villaescusa, J.I.

2006-01-01

The image quality assessment of a radiographic phantom image is one of the fundamental points in a complete quality control programme. The good functioning result of all the process must be an image with an appropriate quality to carry out a suitable diagnostic. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. Contrast-detail phantoms are applied to digital radiography to study the threshold contrast detail sensitivity at operation conditions of the equipment. The phantom that is studied in this work is C.D.M.A.M. 3.4, which facilitates the evaluation of image contrast and detail resolution. One of the most extended indexes to measure the image quality in an objective way is the Image Quality Figure (I.Q.F.). This parameter is useful to calculate the image quality taking into account the contrast and detail resolution of the image analysed. The contrast-detail curve is useful as a measure of the image quality too, because it is a graphical representation in which the hole thickness and diameter are plotted for each contrast-detail combination detected in the radiographic image of the phantom. It is useful for the comparison of the functioning of different radiographic image systems, for phantom images under the same exposition conditions. The aim of this work is to study the image quality of different images contrast-detail phantom C.D.M.A.M. 3.4, carrying out the automatic detection of the contrast-detail combination and to establish a parameter which characterize in an objective way the mammographic image quality. This is useful to compare images obtained at different digital mammographic equipments to study the functioning of the equipments. (authors)

PlantCV v2: Image analysis software for high-throughput plant phenotyping

Directory of Open Access Journals (Sweden)

Malia A. Gehan

2017-12-01

Full Text Available Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

Iso-precision scaling of digitized mammograms to facilitate image analysis

International Nuclear Information System (INIS)

Karssmeijer, N.; van Erning, L.

1991-01-01

This paper reports on a 12 bit CCD camera equipped with a linear sensor of 4096 photodiodes which is used to digitize conventional mammographic films. An iso-precision conversion of the pixel values is preformed to transform the image data to a scale on which the image noise is equal at each level. For this purpose film noise and digitization noise have been determined as a function of optical density and pixel size. It appears that only at high optical densities digitization noise is comparable to or larger than film noise. The quantization error caused by compression of images recorded with 12 bits per pixel to 8 bit images by an iso-precision conversion has been calculated as a function of the number of quantization levels. For mammograms digitized in a 4096 2 matrix the additional error caused by such a scale transform is only about 1.5 percent. An iso-precision scale transform can be advantageous when automated procedures for quantitative image analysis are developed. Especially when detection of signals in noise is aimed at, a constant noise level over the whole pixel value range is very convenient. This is demonstrated by applying local thresholding to detect small microcalcifications. Results are compared to those obtained by using logarithmic or linearized scales

A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing.

Science.gov (United States)

Schwertner, Ryan W; Garand, Kendrea L; Pearson, William G

2016-01-01

Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data.

Perceptual and statistical analysis of cardiac phase and amplitude images

International Nuclear Information System (INIS)

Houston, A.; Craig, A.

1991-01-01

A perceptual experiment was conducted using cardiac phase and amplitude images. Estimates of statistical parameters were derived from the images and the diagnostic potential of human and statistical decisions compared. Five methods were used to generate the images from 75 gated cardiac studies, 39 of which were classified as pathological. The images were presented to 12 observers experienced in nuclear medicine. The observers rated the images using a five-category scale based on their confidence of an abnormality presenting. Circular and linear statistics were used to analyse phase and amplitude image data, respectively. Estimates of mean, standard deviation (SD), skewness, kurtosis and the first term of the spatial correlation function were evaluated in the region of the left ventricle. A receiver operating characteristic analysis was performed on both sets of data and the human and statistical decisions compared. For phase images, circular SD was shown to discriminate better between normal and abnormal than experienced observers, but no single statistic discriminated as well as the human observer for amplitude images. (orig.)

WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT

Energy Technology Data Exchange (ETDEWEB)

Huang, Q; Zhang, M; Chen, T; Yue, N; Zou, J [Rutgers University, New Brunswick, NJ (United States)

2016-06-15

Purpose: Variation in function of different lung regions has been ignored so far for conventional lung cancer treatment planning, which may lead to higher risk of radiation induced lung disease. 4DCT based lung ventilation imaging provides a novel yet convenient approach for lung functional imaging as 4DCT is taken as routine for lung cancer treatment. Our work aims to evaluate the impact of accounting for spatial heterogeneity in lung function using 4DCT based lung ventilation imaging for proton and IMRT plans. Methods: Six patients with advanced stage lung cancer of various tumor locations were retrospectively evaluated for the study. Proton and IMRT plans were designed following identical planning objective and constrains for each patient. Ventilation images were calculated from patients’ 4DCT using deformable image registration implemented by Velocity AI software based on Jacobian-metrics. Lung was delineated into two function level regions based on ventilation (low and high functional area). High functional region was defined as lung ventilation greater than 30%. Dose distribution and statistics in different lung function area was calculated for patients. Results: Variation in dosimetric statistics of different function lung region was observed between proton and IMRT plans. In all proton plans, high function lung regions receive lower maximum dose (100.2%–108.9%), compared with IMRT plans (106.4%–119.7%). Interestingly, three out of six proton plans gave higher mean dose by up to 2.2% than IMRT to high function lung region. Lower mean dose (lower by up to 14.1%) and maximum dose (lower by up to 9%) were observed in low function lung for proton plans. Conclusion: A systematic approach was developed to generate function lung ventilation imaging and use it to evaluate plans. This method hold great promise in function analysis of lung during planning. We are currently studying more subjects to evaluate this tool.

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

Science.gov (United States)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Wave-equation Migration Velocity Analysis Using Plane-wave Common Image Gathers

KAUST Repository

Guo, Bowen

2017-06-01

Wave-equation migration velocity analysis (WEMVA) based on subsurface-offset, angle domain or time-lag common image gathers (CIGs) requires significant computational and memory resources because it computes higher dimensional migration images in the extended image domain. To mitigate this problem, a WEMVA method using plane-wave CIGs is presented. Plane-wave CIGs reduce the computational cost and memory storage because they are directly calculated from prestack plane-wave migration, and the number of plane waves is often much smaller than the number of shots. In the case of an inaccurate migration velocity, the moveout of plane-wave CIGs is automatically picked by a semblance analysis method, which is then linked to the migration velocity update by a connective function. Numerical tests on two synthetic datasets and a field dataset validate the efficiency and effectiveness of this method.

Quantitative analysis of receptor imaging

International Nuclear Information System (INIS)

Fu Zhanli; Wang Rongfu

2004-01-01

Model-based methods for quantitative analysis of receptor imaging, including kinetic, graphical and equilibrium methods, are introduced in detail. Some technical problem facing quantitative analysis of receptor imaging, such as the correction for in vivo metabolism of the tracer and the radioactivity contribution from blood volume within ROI, and the estimation of the nondisplaceable ligand concentration, is also reviewed briefly

Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment

Science.gov (United States)

Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann

2010-01-01

Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782

Color image analysis of contaminants and bacteria transport in porous media

Science.gov (United States)

Rashidi, Mehdi; Dehmeshki, Jamshid; Daemi, Mohammad F.; Cole, Larry; Dickenson, Eric

1997-10-01

Transport of contaminants and bacteria in aqueous heterogeneous saturated porous systems have been studied experimentally using a novel fluorescent microscopic imaging technique. The approach involves color visualization and quantification of bacterium and contaminant distributions within a transparent porous column. By introducing stained bacteria and an organic dye as a contaminant into the column and illuminating the porous regions with a planar sheet of laser beam, contaminant and bacterial transport processes through the porous medium can be observed and measured microscopically. A computer controlled color CCD camera is used to record the fluorescent images as a function of time. These images are recorded by a frame accurate high resolution VCR and are then analyzed using a color image analysis code written in our laboratories. The color images are digitized this way and simultaneous concentration and velocity distributions of both contaminant and bacterium are evaluated as a function of time and pore characteristics. The approach provides a unique dynamic probe to observe these transport processes microscopically. These results are extremely valuable in in-situ bioremediation problems since microscopic particle-contaminant- bacterium interactions are the key to understanding and optimization of these processes.

The Scientific Image in Behavior Analysis.

Science.gov (United States)

Keenan, Mickey

2016-05-01

Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press.

Functional Imaging: CT and MRI

OpenAIRE

van Beek, Edwin JR; Hoffman, Eric A

2008-01-01

Numerous imaging techniques permit evaluation of regional pulmonary function. Contrast-enhanced CT methods now allow assessment of vasculature and lung perfusion. Techniques using spirometric controlled MDCT allow for quantification of presence and distribution of parenchymal and airway pathology, Xenon gas can be employed to assess regional ventilation of the lungs and rapid bolus injections of iodinated contrast agent can provide quantitative measure of regional parenchymal perfusion. Advan...

Application of a logistic function to the analysis of contrast-detail curves

International Nuclear Information System (INIS)

Mumma, C.G.; Prince, J.R.

1987-01-01

A general logistic function has been applied to the regression analysis of radioscintigraphic contrast-detail (CD) curves obtained in the authors' laboratory and to previously published results in assorted imaging modalities. Regression analysis is based on the logistic function: d/sub min/ = d/sub min//sup sat/(1 - EXP - (K + CX)), where d/sub min/ is the minimum perceptible detail diameter at a primary contrast X, and d/sub min//sup sat/ is the saturation value of d/sub min/. K and C are regression parameters. Logistic regression in assorted imaging modalities yielded r 2 values ranging from 0.95 to 0.99. A figure of merit (FOM), the area under the CD curve (AUC), is obtained by integrating the logistic function over mathematically and clinically acceptable limits. For count densities of 200 countscm 2 and 1,000 countscm 2 , the AUC differed approximately by a factor of 2. Thus, the AUC may be a sensitive FOM

Synchronized 2D/3D optical mapping for interactive exploration and real-time visualization of multi-function neurological images.

Science.gov (United States)

Zhang, Qi; Alexander, Murray; Ryner, Lawrence

2013-01-01

Efficient software with the ability to display multiple neurological image datasets simultaneously with full real-time interactivity is critical for brain disease diagnosis and image-guided planning. In this paper, we describe the creation and function of a new comprehensive software platform that integrates novel algorithms and functions for multiple medical image visualization, processing, and manipulation. We implement an opacity-adjustment algorithm to build 2D lookup tables for multiple slice image display and fusion, which achieves a better visual result than those of using VTK-based methods. We also develop a new real-time 2D and 3D data synchronization scheme for multi-function MR volume and slice image optical mapping and rendering simultaneously through using the same adjustment operation. All these methodologies are integrated into our software framework to provide users with an efficient tool for flexibly, intuitively, and rapidly exploring and analyzing the functional and anatomical MR neurological data. Finally, we validate our new techniques and software platform with visual analysis and task-specific user studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Tool for Classifying Individuals with Chronic Back Pain: Using Multivariate Pattern Analysis with Functional Magnetic Resonance Imaging Data

Science.gov (United States)

Callan, Daniel; Mills, Lloyd; Nott, Connie; England, Robert; England, Shaun

2014-01-01

Chronic pain is one of the most prevalent health problems in the world today, yet neurological markers, critical to diagnosis of chronic pain, are still largely unknown. The ability to objectively identify individuals with chronic pain using functional magnetic resonance imaging (fMRI) data is important for the advancement of diagnosis, treatment, and theoretical knowledge of brain processes associated with chronic pain. The purpose of our research is to investigate specific neurological markers that could be used to diagnose individuals experiencing chronic pain by using multivariate pattern analysis with fMRI data. We hypothesize that individuals with chronic pain have different patterns of brain activity in response to induced pain. This pattern can be used to classify the presence or absence of chronic pain. The fMRI experiment consisted of alternating 14 seconds of painful electric stimulation (applied to the lower back) with 14 seconds of rest. We analyzed contrast fMRI images in stimulation versus rest in pain-related brain regions to distinguish between the groups of participants: 1) chronic pain and 2) normal controls. We employed supervised machine learning techniques, specifically sparse logistic regression, to train a classifier based on these contrast images using a leave-one-out cross-validation procedure. We correctly classified 92.3% of the chronic pain group (N = 13) and 92.3% of the normal control group (N = 13) by recognizing multivariate patterns of activity in the somatosensory and inferior parietal cortex. This technique demonstrates that differences in the pattern of brain activity to induced pain can be used as a neurological marker to distinguish between individuals with and without chronic pain. Medical, legal and business professionals have recognized the importance of this research topic and of developing objective measures of chronic pain. This method of data analysis was very successful in correctly classifying each of the two

A tool for classifying individuals with chronic back pain: using multivariate pattern analysis with functional magnetic resonance imaging data.

Directory of Open Access Journals (Sweden)

Daniel Callan

Full Text Available Chronic pain is one of the most prevalent health problems in the world today, yet neurological markers, critical to diagnosis of chronic pain, are still largely unknown. The ability to objectively identify individuals with chronic pain using functional magnetic resonance imaging (fMRI data is important for the advancement of diagnosis, treatment, and theoretical knowledge of brain processes associated with chronic pain. The purpose of our research is to investigate specific neurological markers that could be used to diagnose individuals experiencing chronic pain by using multivariate pattern analysis with fMRI data. We hypothesize that individuals with chronic pain have different patterns of brain activity in response to induced pain. This pattern can be used to classify the presence or absence of chronic pain. The fMRI experiment consisted of alternating 14 seconds of painful electric stimulation (applied to the lower back with 14 seconds of rest. We analyzed contrast fMRI images in stimulation versus rest in pain-related brain regions to distinguish between the groups of participants: 1 chronic pain and 2 normal controls. We employed supervised machine learning techniques, specifically sparse logistic regression, to train a classifier based on these contrast images using a leave-one-out cross-validation procedure. We correctly classified 92.3% of the chronic pain group (N = 13 and 92.3% of the normal control group (N = 13 by recognizing multivariate patterns of activity in the somatosensory and inferior parietal cortex. This technique demonstrates that differences in the pattern of brain activity to induced pain can be used as a neurological marker to distinguish between individuals with and without chronic pain. Medical, legal and business professionals have recognized the importance of this research topic and of developing objective measures of chronic pain. This method of data analysis was very successful in correctly classifying

Functional data analysis

CERN Document Server

Ramsay, J O

1997-01-01

Scientists today collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modelling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis; they are drwan from growth analysis, meterology, biomechanics, equine science, economics, and medicine. The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, to applied data analysts, and to experienced researc...

Information granules in image histogram analysis.

Science.gov (United States)

Wieclawek, Wojciech

2018-04-01

A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

Introduction to Medical Image Analysis

DEFF Research Database (Denmark)

Paulsen, Rasmus Reinhold; Moeslund, Thomas B.

This book is a result of a collaboration between DTU Informatics at the Technical University of Denmark and the Laboratory of Computer Vision and Media Technology at Aalborg University. It is partly based on the book ”Image and Video Processing”, second edition by Thomas Moeslund. The aim...... of the book is to present the fascinating world of medical image analysis in an easy and interesting way. Compared to many standard books on image analysis, the approach we have chosen is less mathematical and more casual. Some of the key algorithms are exemplified in C-code. Please note that the code...

Surface-functionalized nanoparticles for biosensing and imaging-guided therapeutics

Science.gov (United States)

Jiang, Shan; Win, Khin Yin; Liu, Shuhua; Teng, Choon Peng; Zheng, Yuangang; Han, Ming-Yong

2013-03-01

In this article, the very recent progress of various functional inorganic nanomaterials is reviewed including their unique properties, surface functionalization strategies, and applications in biosensing and imaging-guided therapeutics. The proper surface functionalization renders them with stability, biocompatibility and functionality in physiological environments, and further enables their targeted use in bioapplications after bioconjugation via selective and specific recognition. The surface-functionalized nanoprobes using the most actively studied nanoparticles (i.e., gold nanoparticles, quantum dots, upconversion nanoparticles, and magnetic nanoparticles) make them an excellent platform for a wide range of bioapplications. With more efforts in recent years, they have been widely developed as labeling probes to detect various biological species such as proteins, nucleic acids and ions, and extensively employed as imaging probes to guide therapeutics such as drug/gene delivery and photothermal/photodynamic therapy.

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

Energy Technology Data Exchange (ETDEWEB)

Owen, D; Anderson, C; Mayo, C; El Naqa, I; Ten Haken, R; Cao, Y; Balter, J; Matuszak, M [University of Michigan, Ann Arbor, MI (United States)

2016-06-15

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinForms to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response

Imaging insights into basal ganglia function, Parkinson's disease, and dystonia.

Science.gov (United States)

Stoessl, A Jon; Lehericy, Stephane; Strafella, Antonio P

2014-08-09

Recent advances in structural and functional imaging have greatly improved our ability to assess normal functions of the basal ganglia, diagnose parkinsonian syndromes, understand the pathophysiology of parkinsonism and other movement disorders, and detect and monitor disease progression. Radionuclide imaging is the best way to detect and monitor dopamine deficiency, and will probably continue to be the best biomarker for assessment of the effects of disease-modifying therapies. However, advances in magnetic resonance enable the separation of patients with Parkinson's disease from healthy controls, and show great promise for differentiation between Parkinson's disease and other akinetic-rigid syndromes. Radionuclide imaging is useful to show the dopaminergic basis for both motor and behavioural complications of Parkinson's disease and its treatment, and alterations in non-dopaminergic systems. Both PET and MRI can be used to study patterns of functional connectivity in the brain, which is disrupted in Parkinson's disease and in association with its complications, and in other basal-ganglia disorders such as dystonia, in which an anatomical substrate is not otherwise apparent. Functional imaging is increasingly used to assess underlying pathological processes such as neuroinflammation and abnormal protein deposition. This imaging is another promising approach to assess the effects of treatments designed to slow disease progression. Copyright © 2014 Elsevier Ltd. All rights reserved.

Residual stress distribution analysis of heat treated APS TBC using image based modelling.

Science.gov (United States)

Li, Chun; Zhang, Xun; Chen, Ying; Carr, James; Jacques, Simon; Behnsen, Julia; di Michiel, Marco; Xiao, Ping; Cernik, Robert

2017-08-01

We carried out a residual stress distribution analysis in a APS TBC throughout the depth of the coatings. The samples were heat treated at 1150 °C for 190 h and the data analysis used image based modelling based on the real 3D images measured by Computed Tomography (CT). The stress distribution in several 2D slices from the 3D model is included in this paper as well as the stress distribution along several paths shown on the slices. Our analysis can explain the occurrence of the "jump" features near the interface between the top coat and the bond coat. These features in the residual stress distribution trend were measured (as a function of depth) by high-energy synchrotron XRD (as shown in our related research article entitled 'Understanding the Residual Stress Distribution through the Thickness of Atmosphere Plasma Sprayed (APS) Thermal Barrier Coatings (TBCs) by high energy Synchrotron XRD; Digital Image Correlation (DIC) and Image Based Modelling') (Li et al., 2017) [1].

Multispectral analysis of multimodal images

Energy Technology Data Exchange (ETDEWEB)

Kvinnsland, Yngve; Brekke, Njaal (Dept. of Surgical Sciences, Univ. of Bergen, Bergen (Norway)); Taxt, Torfinn M.; Gruener, Renate (Dept. of Biomedicine, Univ. of Bergen, Bergen (Norway))

2009-02-15

An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. Materials and methods. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. Results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentation that seem to be sensible. Discussion. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

Directory of Open Access Journals (Sweden)

Bradford A. Moffat

2006-04-01

Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

MiToBo - A Toolbox for Image Processing and Analysis

Directory of Open Access Journals (Sweden)

Birgit Möller

2016-04-01

Full Text Available MiToBo is a toolbox and Java library for solving basic as well as advanced image processing and analysis tasks. It features a rich collection of fundamental, intermediate and high-level image processing operators and algorithms as well as a couple of sophisticated tools for specific biological and biomedical applications. These tools include operators for elucidating cellular morphology and locomotion as well as operators for the characterization of certain intracellular particles and structures. MiToBo builds upon and integrates into the widely-used image analysis software packages ImageJ and Fiji [11, 10], and all of its operators can easily be run in ImageJ and Fiji via a generic operator runner plugin. Alternatively MiToBo operators can directly be run from command line, and using its functionality as a library for developing own applications is also supported. Thanks to the Alida library [8] forming the base of MiToBo all operators share unified APIs fostering reusability, and graphical as well as command line user interfaces for operators are automatically generated. MiToBo is available from its website http://www.informatik.uni-halle.de/mitobo, on Github, via an Apache Archiva Maven repository server, and it can easily be activated in Fiji via its own update site.

An Imaging And Graphics Workstation For Image Sequence Analysis

Science.gov (United States)

Mostafavi, Hassan

1990-01-01

This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.

Brain-inspired algorithms for retinal image analysis

NARCIS (Netherlands)

ter Haar Romeny, B.M.; Bekkers, E.J.; Zhang, J.; Abbasi-Sureshjani, S.; Huang, F.; Duits, R.; Dasht Bozorg, Behdad; Berendschot, T.T.J.M.; Smit-Ockeloen, I.; Eppenhof, K.A.J.; Feng, J.; Hannink, J.; Schouten, J.; Tong, M.; Wu, H.; van Triest, J.W.; Zhu, S.; Chen, D.; He, W.; Xu, L.; Han, P.; Kang, Y.

2016-01-01

Retinal image analysis is a challenging problem due to the precise quantification required and the huge numbers of images produced in screening programs. This paper describes a series of innovative brain-inspired algorithms for automated retinal image analysis, recently developed for the RetinaCheck

The cumulative verification image analysis tool for offline evaluation of portal images

International Nuclear Information System (INIS)

Wong, John; Yan Di; Michalski, Jeff; Graham, Mary; Halverson, Karen; Harms, William; Purdy, James

1995-01-01

Purpose: Daily portal images acquired using electronic portal imaging devices contain important information about the setup variation of the individual patient. The data can be used to evaluate the treatment and to derive correction for the individual patient. The large volume of images also require software tools for efficient analysis. This article describes the approach of cumulative verification image analysis (CVIA) specifically designed as an offline tool to extract quantitative information from daily portal images. Methods and Materials: The user interface, image and graphics display, and algorithms of the CVIA tool have been implemented in ANSCI C using the X Window graphics standards. The tool consists of three major components: (a) definition of treatment geometry and anatomical information; (b) registration of portal images with a reference image to determine setup variation; and (c) quantitative analysis of all setup variation measurements. The CVIA tool is not automated. User interaction is required and preferred. Successful alignment of anatomies on portal images at present remains mostly dependent on clinical judgment. Predefined templates of block shapes and anatomies are used for image registration to enhance efficiency, taking advantage of the fact that much of the tool's operation is repeated in the analysis of daily portal images. Results: The CVIA tool is portable and has been implemented on workstations with different operating systems. Analysis of 20 sequential daily portal images can be completed in less than 1 h. The temporal information is used to characterize setup variation in terms of its systematic, random and time-dependent components. The cumulative information is used to derive block overlap isofrequency distributions (BOIDs), which quantify the effective coverage of the prescribed treatment area throughout the course of treatment. Finally, a set of software utilities is available to facilitate feedback of the information for

Functional brain imaging of gastrointestinal sensation in health and disease

Institute of Scientific and Technical Information of China (English)

Lukas Van Oudenhove; Steven J Coen; Qasim Aziz

2007-01-01

It has since long been known, from everyday experience as well as from animal and human studies, that psychological processes-both affective and cognitiveexert an influence on gastrointestinal sensorimotor function. More specifically, a link between psychological factors and visceral hypersensitivity has been suggested,mainly based on research in functional gastrointestinal disorder patients. However, until recently, the exact nature of this putative relationship remained unclear,mainly due to a lack of non-invasive methods to study the (neurobiological) mechanisms underlying this relationship in non-sleeping humans. As functional brain imaging, introduced in visceral sensory neuroscience some 10 years ago, does provide a method for in vivo study of brain-gut interactions, insight into the neurobiological mechanisms underlying visceral sensation in general and the influence of psychological factors more particularly,has rapidly grown. In this article, an overview of brain imaging evidence on gastrointestinal sensation will be given, with special emphasis on the brain mechanisms underlying the interaction between affective & cognitive processes and visceral sensation. First, the reciprocal neural pathways between the brain and the gut (braingut axis) will be briefly outlined, including brain imaging evidence in healthy volunteers. Second, functional brain imaging studies assessing the influence of psychological factors on brain processing of visceral sensation in healthy humans will be discussed in more detail.Finally, brain imaging work investigating differences in brain responses to visceral distension between healthy volunteers and functional gastrointestinal disorder patients will be highlighted.

Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review.

Science.gov (United States)

Ohkubo, Hirotsugu; Nakagawa, Hiroaki; Niimi, Akio

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is the most common type of progressive idiopathic interstitial pneumonia in adults. Many computer-based image analysis methods of chest computed tomography (CT) used in patients with IPF include the mean CT value of the whole lungs, density histogram analysis, density mask technique, and texture classification methods. Most of these methods offer good assessment of pulmonary functions, disease progression, and mortality. Each method has merits that can be used in clinical practice. One of the texture classification methods is reported to be superior to visual CT scoring by radiologist for correlation with pulmonary function and prediction of mortality. In this mini review, we summarize the current literature on computer-based CT image analysis of IPF and discuss its limitations and several future directions. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

Multiple image x-radiography for functional lung imaging

Science.gov (United States)

Aulakh, G. K.; Mann, A.; Belev, G.; Wiebe, S.; Kuebler, W. M.; Singh, B.; Chapman, D.

2018-01-01

Detection and visualization of lung tissue structures is impaired by predominance of air. However, by using synchrotron x-rays, refraction of x-rays at the interface of tissue and air can be utilized to generate contrast which may in turn enable quantification of lung optical properties. We utilized multiple image radiography, a variant of diffraction enhanced imaging, at the Canadian light source to quantify changes in unique x-ray optical properties of lungs, namely attenuation, refraction and ultra small-angle scatter (USAXS or width) contrast ratios as a function of lung orientation in free-breathing or respiratory-gated mice before and after intra-nasal bacterial endotoxin (lipopolysaccharide) instillation. The lung ultra small-angle scatter and attenuation contrast ratios were significantly higher 9 h post lipopolysaccharide instillation compared to saline treatment whereas the refraction contrast decreased in magnitude. In ventilated mice, end-expiratory pressures result in an increase in ultra small-angle scatter contrast ratio when compared to end-inspiratory pressures. There were no detectable changes in lung attenuation or refraction contrast ratio with change in lung pressure alone. In effect, multiple image radiography can be applied towards following optical properties of lung air-tissue barrier over time during pathologies such as acute lung injury.

Preoperative Estimation of Future Remnant Liver Function Following Portal Vein Embolization Using Relative Enhancement on Gadoxetic Acid Disodium-Enhanced Magnetic Resonance Imaging

Energy Technology Data Exchange (ETDEWEB)

Sato, Yozo [Department of Radiology, Aichi Medical University, Aichi 480-1195 (Japan); Department of Diagnostic and Interventional Radiology, Aichi Cancer Center Hospital, Nagoya 464-8681 (Japan); Matsushima, Shigeru; Inaba, Yoshitaka [Department of Diagnostic and Interventional Radiology, Aichi Cancer Center Hospital, Nagoya 464-8681 (Japan); Sano, Tsuyoshi [Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Nagoya 464-8681 (Japan); Yamaura, Hidekazu; Kato, Mina [Department of Diagnostic and Interventional Radiology, Aichi Cancer Center Hospital, Nagoya 464-8681 (Japan); Shimizu, Yasuhiro; Senda, Yoshiki [Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Nagoya 464-8681 (Japan); Ishiguchi, Tsuneo [Department of Radiology, Aichi Medical University, Aichi 480-1195 (Japan)

2015-11-01

To retrospectively evaluate relative enhancement (RE) in the hepatobiliary phase of gadoxetic acid disodium-enhanced magnetic resonance (MR) imaging as a preoperative estimation of future remnant liver (FRL) function in a patients who underwent portal vein embolization (PVE). In 53 patients, the correlation between the indocyanine green clearance (ICG-K) and RE imaging was analyzed before hepatectomy (first analysis). Twenty-three of the 53 patients underwent PVE followed by a repeat RE imaging and ICG test before an extended hepatectomy and their results were further analyzed (second analysis). Whole liver function and FRL function were calculated on the MR imaging as follows: RE x total liver volume (RE Index) and FRL-RE x FRL volume (Rem RE Index), respectively. Regarding clinical outcome, posthepatectomy liver failure (PHLF) was evaluated in patients undergoing PVE. Indocyanine green clearance correlated with the RE Index (r = 0.365, p = 0.007), and ICG-K of FRL (ICG-Krem) strongly correlated with the Rem RE Index (r = 0.738, p < 0.001) in the first analysis. Both the ICG-Krem and the Rem RE Index were significantly correlated after PVE (r = 0.508, p = 0.013) at the second analysis. The rate of improvement of the Rem RE Index from before PVE to after PVE was significantly higher than that of ICG-Krem (p = 0.014). Patients with PHLF had a significantly lower Rem RE Index than patients without PHLF (p = 0.023). Relative enhancement imaging can be used to estimate FRL function after PVE.

Image sequence analysis workstation for multipoint motion analysis

Science.gov (United States)

Mostafavi, Hassan

1990-08-01

This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

Automated MicroSPECT/MicroCT Image Analysis of the Mouse Thyroid Gland.

Science.gov (United States)

Cheng, Peng; Hollingsworth, Brynn; Scarberry, Daniel; Shen, Daniel H; Powell, Kimerly; Smart, Sean C; Beech, John; Sheng, Xiaochao; Kirschner, Lawrence S; Menq, Chia-Hsiang; Jhiang, Sissy M

2017-11-01

The ability of thyroid follicular cells to take up iodine enables the use of radioactive iodine (RAI) for imaging and targeted killing of RAI-avid thyroid cancer following thyroidectomy. To facilitate identifying novel strategies to improve 131 I therapeutic efficacy for patients with RAI refractory disease, it is desired to optimize image acquisition and analysis for preclinical mouse models of thyroid cancer. A customized mouse cradle was designed and used for microSPECT/CT image acquisition at 1 hour (t1) and 24 hours (t24) post injection of 123 I, which mainly reflect RAI influx/efflux equilibrium and RAI retention in the thyroid, respectively. FVB/N mice with normal thyroid glands and TgBRAF V600E mice with thyroid tumors were imaged. In-house CTViewer software was developed to streamline image analysis with new capabilities, along with display of 3D voxel-based 123 I gamma photon intensity in MATLAB. The customized mouse cradle facilitates consistent tissue configuration among image acquisitions such that rigid body registration can be applied to align serial images of the same mouse via the in-house CTViewer software. CTViewer is designed specifically to streamline SPECT/CT image analysis with functions tailored to quantify thyroid radioiodine uptake. Automatic segmentation of thyroid volumes of interest (VOI) from adjacent salivary glands in t1 images is enabled by superimposing the thyroid VOI from the t24 image onto the corresponding aligned t1 image. The extent of heterogeneity in 123 I accumulation within thyroid VOIs can be visualized by 3D display of voxel-based 123 I gamma photon intensity. MicroSPECT/CT image acquisition and analysis for thyroidal RAI uptake is greatly improved by the cradle and the CTViewer software, respectively. Furthermore, the approach of superimposing thyroid VOIs from t24 images to select thyroid VOIs on corresponding aligned t1 images can be applied to studies in which the target tissue has differential radiotracer retention

Combining MRI with PET for partial volume correction improves image-derived input functions in mice

Energy Technology Data Exchange (ETDEWEB)

Evans, Eleanor; Buonincontri, Guido [Wolfson Brain Imaging Centre, University of Cambridge, Cambridge (United Kingdom); Izquierdo, David [Athinoula A Martinos Centre, Harvard University, Cambridge, MA (United States); Methner, Carmen [Department of Medicine, University of Cambridge, Cambridge (United Kingdom); Hawkes, Rob C [Wolfson Brain Imaging Centre, University of Cambridge, Cambridge (United Kingdom); Ansorge, Richard E [Department of Physics, University of Cambridge, Cambridge (United Kingdom); Kreig, Thomas [Department of Medicine, University of Cambridge, Cambridge (United Kingdom); Carpenter, T Adrian [Wolfson Brain Imaging Centre, University of Cambridge, Cambridge (United Kingdom); Sawiak, Stephen J [Wolfson Brain Imaging Centre, University of Cambridge, Cambridge (United Kingdom); Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge (United Kingdom)

2014-07-29

Kinetic modelling in PET requires the arterial input function (AIF), defined as the time-activity curve (TAC) in plasma. This measure is challenging to obtain in mice due to low blood volumes, resulting in a reliance on image-based methods for AIF derivation. We present a comparison of PET- and MR-based region-of-interest (ROI) analysis to obtain image-derived AIFs from the left ventricle (LV) of a mouse model. ROI-based partial volume correction (PVC) was performed to improve quantification.

Combining MRI with PET for partial volume correction improves image-derived input functions in mice

International Nuclear Information System (INIS)

Evans, Eleanor; Buonincontri, Guido; Izquierdo, David; Methner, Carmen; Hawkes, Rob C; Ansorge, Richard E; Kreig, Thomas; Carpenter, T Adrian; Sawiak, Stephen J

2014-01-01

Kinetic modelling in PET requires the arterial input function (AIF), defined as the time-activity curve (TAC) in plasma. This measure is challenging to obtain in mice due to low blood volumes, resulting in a reliance on image-based methods for AIF derivation. We present a comparison of PET- and MR-based region-of-interest (ROI) analysis to obtain image-derived AIFs from the left ventricle (LV) of a mouse model. ROI-based partial volume correction (PVC) was performed to improve quantification.

[Present status and trend of heart fluid mechanics research based on medical image analysis].

Science.gov (United States)

Gan, Jianhong; Yin, Lixue; Xie, Shenghua; Li, Wenhua; Lu, Jing; Luo, Anguo

2014-06-01

With introduction of current main methods for heart fluid mechanics researches, we studied the characteristics and weakness for three primary analysis methods based on magnetic resonance imaging, color Doppler ultrasound and grayscale ultrasound image, respectively. It is pointed out that particle image velocity (PIV), speckle tracking and block match have the same nature, and three algorithms all adopt block correlation. The further analysis shows that, with the development of information technology and sensor, the research for cardiac function and fluid mechanics will focus on energy transfer process of heart fluid, characteristics of Chamber wall related to blood fluid and Fluid-structure interaction in the future heart fluid mechanics fields.

MR imaging of kidneys: functional evaluation using F-15 perfusion imaging

International Nuclear Information System (INIS)

Grattan-Smith, J. Damien; Jones, Richard A.; Little, Stephen; Perez-Bayfield, Marcos R.; Broecker, Bruce; Smith, Edwin A.; Scherz, Hal C.; Kirsch, Andrew J.

2003-01-01

Children with hydronephrosis are typically investigated by a combination of diuretic renal scintigraphy, ultrasound, and voiding cystourethrography. Unfortunately, there is no gold standard to assess obstruction. The purpose of our study was to evaluate the utility of dynamic contrast enhanced MR urography in the investigation of children with hydronephrosis to define urinary tract anatomy, to calculate differential renal function and to assess urinary tract obstruction. Dynamic contrast-enhanced MR imaging was performed in 40 children with unilateral hydronephrosis. There were 14 girls and 26 boys with an age range of 1 month to 14 years (mean 1.4 years). The information from traditional imaging modalities was compared to the information obtained from the single MR study. The anatomic imaging with MR urography was superior to other modalities. The split renal function was estimated with MR urography by calculating the volume of enhancing renal parenchyma and was comparable to renal scintigraphy (r=0.98). By using surgery versus non-surgery as the decision point, with MR urography the sensitivity was 100%, specificity 71%, positive predictive value 86%, negative predictive value 100%, and diagnostic efficiency 90%. For renal scintigraphy the sensitivity was 96%, the specificity 56%, positive predictive value 76%, negative predictive value 90%, and diagnostic efficiency 79%. Dynamic contrast-enhanced MR urography provides superior anatomic and functional information when compared with ultrasound and diuretic renal scintigraphy. The information is gathered in a single study that does not use ionizing radiation. It is likely that MR urography will replace renal scintigraphy in the evaluation of hydronephrosis in children. (orig.)

MR imaging of kidneys: functional evaluation using F-15 perfusion imaging

Energy Technology Data Exchange (ETDEWEB)

Grattan-Smith, J. Damien; Jones, Richard A.; Little, Stephen [Department of Pediatric Radiology, Children' s Healthcare of Atlanta, Emory University School of Medicine, 1001 Johnson Ferry Road, GA 30342, Atlanta (United States); Perez-Bayfield, Marcos R.; Broecker, Bruce; Smith, Edwin A.; Scherz, Hal C.; Kirsch, Andrew J. [Department of Pediatric Urology, Children' s Healthcare of Atlanta, Emory University School of Medicine, GA 30342, Atlanta (United States)

2003-05-01

Children with hydronephrosis are typically investigated by a combination of diuretic renal scintigraphy, ultrasound, and voiding cystourethrography. Unfortunately, there is no gold standard to assess obstruction. The purpose of our study was to evaluate the utility of dynamic contrast enhanced MR urography in the investigation of children with hydronephrosis to define urinary tract anatomy, to calculate differential renal function and to assess urinary tract obstruction. Dynamic contrast-enhanced MR imaging was performed in 40 children with unilateral hydronephrosis. There were 14 girls and 26 boys with an age range of 1 month to 14 years (mean 1.4 years). The information from traditional imaging modalities was compared to the information obtained from the single MR study. The anatomic imaging with MR urography was superior to other modalities. The split renal function was estimated with MR urography by calculating the volume of enhancing renal parenchyma and was comparable to renal scintigraphy (r=0.98). By using surgery versus non-surgery as the decision point, with MR urography the sensitivity was 100%, specificity 71%, positive predictive value 86%, negative predictive value 100%, and diagnostic efficiency 90%. For renal scintigraphy the sensitivity was 96%, the specificity 56%, positive predictive value 76%, negative predictive value 90%, and diagnostic efficiency 79%. Dynamic contrast-enhanced MR urography provides superior anatomic and functional information when compared with ultrasound and diuretic renal scintigraphy. The information is gathered in a single study that does not use ionizing radiation. It is likely that MR urography will replace renal scintigraphy in the evaluation of hydronephrosis in children. (orig.)

Magnetic resonance imaging research progress on brain functional reorganization after peripheral nerve injury

International Nuclear Information System (INIS)

Wang Weiwei; Liu Hanqiu

2013-01-01

In the recent years, with the development of functional magnetic resonance imaging technology the brain plasticity and functional reorganization are hot topics in the central nervous system imaging studies. Brain functional reorganization and rehabilitation after peripheral nerve injury may have certain regularity. In this paper, the progress of brain functional magnetic resonance imaging technology and its applications in the world wide clinical and experimental researches of the brain functional reorganization after peripheral nerve injury is are reviewed. (authors)

Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

Science.gov (United States)

Chang, Catie; Raven, Erika P; Duyn, Jeff H

2016-05-13

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions. © 2016 The Author(s).

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

Science.gov (United States)

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Image analysis enhancement and interpretation

International Nuclear Information System (INIS)

Glauert, A.M.

1978-01-01

The necessary practical and mathematical background are provided for the analysis of an electron microscope image in order to extract the maximum amount of structural information. Instrumental methods of image enhancement are described, including the use of the energy-selecting electron microscope and the scanning transmission electron microscope. The problems of image interpretation are considered with particular reference to the limitations imposed by radiation damage and specimen thickness. A brief survey is given of the methods for producing a three-dimensional structure from a series of two-dimensional projections, although emphasis is really given on the analysis, processing and interpretation of the two-dimensional projection of a structure. (Auth.)

Data Analysis Strategies in Medical Imaging.

Science.gov (United States)

Parmar, Chintan; Barry, Joseph D; Hosny, Ahmed; Quackenbush, John; Aerts, Hugo Jwl

2018-03-26

Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence (AI) has allowed for detailed quantification of radiographic characteristics of tissues using predefined engineered algorithms or deep learning methods. Precedents in radiology as well as a wealth of research studies hint at the clinical relevance of these characteristics. However, there are critical challenges associated with the analysis of medical imaging data. While some of these challenges are specific to the imaging field, many others like reproducibility and batch effects are generic and have already been addressed in other quantitative fields such as genomics. Here, we identify these pitfalls and provide recommendations for analysis strategies of medical imaging data including data normalization, development of robust models, and rigorous statistical analyses. Adhering to these recommendations will not only improve analysis quality, but will also enhance precision medicine by allowing better integration of imaging data with other biomedical data sources. Copyright ©2018, American Association for Cancer Research.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Science.gov (United States)

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system. PMID:25371701

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Directory of Open Access Journals (Sweden)

Tae-Yun Kim

2014-01-01

Full Text Available One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.

The ImageJ ecosystem: An open platform for biomedical image analysis.

Science.gov (United States)

Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

2015-01-01

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. © 2015 Wiley Periodicals, Inc.

Optimization of shearography image quality analysis

International Nuclear Information System (INIS)

Rafhayudi Jamro

2005-01-01

Shearography is an optical technique based on speckle pattern to measure the deformation of the object surface in which the fringe pattern is obtained through the correlation analysis from the speckle pattern. Analysis of fringe pattern for engineering application is limited for qualitative measurement. Therefore, for further analysis that lead to qualitative data, series of image processing mechanism are involved. In this paper, the fringe pattern for qualitative analysis is discussed. In principal field of applications is qualitative non-destructive testing such as detecting discontinuity, defect in the material structure, locating fatigue zones and etc and all these required image processing application. In order to performed image optimisation successfully, the noise in the fringe pattern must be minimised and the fringe pattern itself must be maximise. This can be achieved by applying a filtering method with a kernel size ranging from 2 X 2 to 7 X 7 pixels size and also applying equalizer in the image processing. (Author)

A Study on Analysis of EEG Caused by Grating Stimulation Imaging

Science.gov (United States)

Urakawa, Hiroshi; Nishimura, Toshihiro; Tsubai, Masayoshi; Itoh, Kenji

Recently, many researchers have studied a visual perception. Focus is attended to studies of the visual perception phenomenon by using the grating stimulation images. The previous researches have suggested that a subset of retinal ganglion cells responds to motion in the receptive field center, but only if the wider surround moves with a different trajectory. We discuss the function of human retina, and measure and analysis EEG(electroencephalography) of a normal subject who looks on grating stimulation images. We confirmed the visual perception of human by EEG signal analysis. We also have obtained that a sinusoidal grating stimulation was given, asymmetry was observed the α wave element in EEG of the symmetric part in a left hemisphere and a right hemisphere of the brain. Therefore, it is presumed that projected image is even when the still picture is seen and the image projected onto retinas of right and left eyes is not even for the dynamic scene. It evaluated it by taking the envelope curve for the detected α wave, and using the average and standard deviation.

Functional requirements for a central research imaging data repository.

Science.gov (United States)

Franke, Thomas; Gruetz, Romanus; Dickmann, Frank

2013-01-01

The current situation at many university medical centers regarding the management of biomedical research imaging data leaves much to be desired. In contrast to the recommendations of the German Research Foundation (DFG) and the German Council of Sciences and Humanities regarding the professional management of research data, there are commonly many individual data pools for research data in each institute and the management remains the responsibility of the researcher. A possible solution for this situation would be to install local central repositories for biomedical research imaging data. In this paper, we developed a scenario based on abstracted use-cases for institutional research undertakings as well as collaborative biomedical research projects and analyzed the functional requirements that a local repository would have to fulfill. We determined eight generic categories of functional requirements, which can be viewed as a basic guideline for the minimum functionality of a central repository for biomedical research imaging data.

Analysis of MUSIC-type imaging functional for single, thin electromagnetic inhomogeneity in limited-view inverse scattering problem

Science.gov (United States)

Ahn, Chi Young; Jeon, Kiwan; Park, Won-Kwang

2015-06-01

This study analyzes the well-known MUltiple SIgnal Classification (MUSIC) algorithm to identify unknown support of thin penetrable electromagnetic inhomogeneity from scattered field data collected within the so-called multi-static response matrix in limited-view inverse scattering problems. The mathematical theories of MUSIC are partially discovered, e.g., in the full-view problem, for an unknown target of dielectric contrast or a perfectly conducting crack with the Dirichlet boundary condition (Transverse Magnetic-TM polarization) and so on. Hence, we perform further research to analyze the MUSIC-type imaging functional and to certify some well-known but theoretically unexplained phenomena. For this purpose, we establish a relationship between the MUSIC imaging functional and an infinite series of Bessel functions of integer order of the first kind. This relationship is based on the rigorous asymptotic expansion formula in the existence of a thin inhomogeneity with a smooth supporting curve. Various results of numerical simulation are presented in order to support the identified structure of MUSIC. Although a priori information of the target is needed, we suggest a least condition of range of incident and observation directions to apply MUSIC in the limited-view problem.

Recent applications of harmonic analysis to function spaces, differential equations, and data science novel methods in harmonic analysis

CERN Document Server

Gia, Quoc; Mayeli, Azita; Mhaskar, Hrushikesh; Zhou, Ding-Xuan

2017-01-01

The second of a two volume set on novel methods in harmonic analysis, this book draws on a number of original research and survey papers from well-known specialists detailing the latest innovations and recently discovered links between various fields. Along with many deep theoretical results, these volumes contain numerous applications to problems in signal processing, medical imaging, geodesy, statistics, and data science. The chapters within cover an impressive range of ideas from both traditional and modern harmonic analysis, such as: the Fourier transform, Shannon sampling, frames, wavelets, functions on Euclidean spaces, analysis on function spaces of Riemannian and sub-Riemannian manifolds, Fourier analysis on manifolds and Lie groups, analysis on combinatorial graphs, sheaves, co-sheaves, and persistent homologies on topological spaces. Volume II is organized around the theme of recent applications of harmonic analysis to function spaces, differential equations, and data science, covering topics such a...

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

Directory of Open Access Journals (Sweden)

Mao-Gui Hu

2009-10-01

Full Text Available Satellite remote sensing (RS is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intraurban. In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolutionenhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well indetail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics.

Functional magnetic resonance imaging in a low-field intraoperative scanner.

Science.gov (United States)

Schulder, Michael; Azmi, Hooman; Biswal, Bharat

2003-01-01

Functional magnetic resonance imaging (fMRI) has been used for preoperative planning and intraoperative surgical navigation. However, most experience to date has been with preoperative images acquired on high-field echoplanar MRI units. We explored the feasibility of acquiring fMRI of the motor cortex with a dedicated low-field intraoperative MRI (iMRI). Five healthy volunteers were scanned with the 0.12-tesla PoleStar N-10 iMRI (Odin Medical Technologies, Israel). A finger-tapping motor paradigm was performed with sequential scans, acquired alternately at rest and during activity. In addition, scans were obtained during breath holding alternating with normal breathing. The same paradigms were repeated using a 3-tesla MRI (Siemens Corp., Allandale, N.J., USA). Statistical analysis was performed offline using cross-correlation and cluster techniques. Data were resampled using the 'jackknife' process. The location, number of activated voxels and degrees of statistical significance between the two scanners were compared. With both the 0.12- and 3-tesla imagers, motor cortex activation was seen in all subjects to a significance of p < 0.02 or greater. No clustered pixels were seen outside the sensorimotor cortex. The resampled correlation coefficients were normally distributed, with a mean of 0.56 for both the 0.12- and 3-tesla scanners (standard deviations 0.11 and 0.08, respectively). The breath holding paradigm confirmed that the expected diffuse activation was seen on 0.12- and 3-tesla scans. Accurate fMRI with a low-field iMRI is feasible. Such data could be acquired immediately before or even during surgery. This would increase the utility of iMRI and allow for updated intraoperative functional imaging, free of the limitations of brain shift. Copyright 2003 S. Karger AG, Basel

Prussian blue nanocubes: multi-functional nanoparticles for multimodal imaging and image-guided therapy (Conference Presentation)

Science.gov (United States)

Cook, Jason R.; Dumani, Diego S.; Kubelick, Kelsey P.; Luci, Jeffrey; Emelianov, Stanislav Y.

2017-03-01

Imaging modalities utilize contrast agents to improve morphological visualization and to assess functional and molecular/cellular information. Here we present a new type of nanometer scale multi-functional particle that can be used for multi-modal imaging and therapeutic applications. Specifically, we synthesized monodisperse 20 nm Prussian Blue Nanocubes (PBNCs) with desired optical absorption in the near-infrared region and superparamagnetic properties. PBNCs showed excellent contrast in photoacoustic (700 nm wavelength) and MR (3T) imaging. Furthermore, photostability was assessed by exposing the PBNCs to nearly 1,000 laser pulses (5 ns pulse width) with up to 30 mJ/cm2 laser fluences. The PBNCs exhibited insignificant changes in photoacoustic signal, demonstrating enhanced robustness compared to the commonly used gold nanorods (substantial photodegradation with fluences greater than 5 mJ/cm2). Furthermore, the PBNCs exhibited superparamagnetism with a magnetic saturation of 105 emu/g, a 5x improvement over superparamagnetic iron-oxide (SPIO) nanoparticles. PBNCs exhibited enhanced T2 contrast measured using 3T clinical MRI. Because of the excellent optical absorption and magnetism, PBNCs have potential uses in other imaging modalities including optical tomography, microscopy, magneto-motive OCT/ultrasound, etc. In addition to multi-modal imaging, the PBNCs are multi-functional and, for example, can be used to enhance magnetic delivery and as therapeutic agents. Our initial studies show that stem cells can be labeled with PBNCs to perform image-guided magnetic delivery. Overall, PBNCs can act as imaging/therapeutic agents in diverse applications including cancer, cardiovascular disease, ophthalmology, and tissue engineering. Furthermore, PBNCs are based on FDA approved Prussian Blue thus potentially easing clinical translation of PBNCs.

Towards functional 3D T-ray imaging

International Nuclear Information System (INIS)

Ferguson, Bradley; Wang, Shaohong; Gray, Doug; Abbott, Derek; Zhang, X-C

2002-01-01

We review the recent development of T-ray computed tomography, a terahertz imaging technique that allows the reconstruction of the three-dimensional refractive index profile of weakly scattering objects. Terahertz pulse imaging is used to obtain images of the target at multiple projection angles and the filtered backprojection algorithm enables the reconstruction of the object's frequency-dependent refractive index. The application of this technique to a biological bone sample and a plastic test structure is demonstrated. The structure of each target is accurately resolved and the frequency-dependent refractive index is determined. The frequency-dependent information may potentially be used to extract functional information from the target, to uniquely identify different materials or to diagnose medical conditions

Discrete imaging models for three-dimensional optoacoustic tomography using radially symmetric expansion functions.

Science.gov (United States)

Wang, Kun; Schoonover, Robert W; Su, Richard; Oraevsky, Alexander; Anastasio, Mark A

2014-05-01

Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT.

Some developments in multivariate image analysis

DEFF Research Database (Denmark)

Kucheryavskiy, Sergey

be up to several million. The main MIA tool for exploratory analysis is score density plot – all pixels are projected into principal component space and on the corresponding scores plots are colorized according to their density (how many pixels are crowded in the unit area of the plot). Looking...... for and analyzing patterns on these plots and the original image allow to do interactive analysis, to get some hidden information, build a supervised classification model, and much more. In the present work several alternative methods to original principal component analysis (PCA) for building the projection......Multivariate image analysis (MIA), one of the successful chemometric applications, now is used widely in different areas of science and industry. Introduced in late 80s it has became very popular with hyperspectral imaging, where MIA is one of the most efficient tools for exploratory analysis...

Rapid analysis and exploration of fluorescence microscopy images.

Science.gov (United States)

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

UV imaging in pharmaceutical analysis

DEFF Research Database (Denmark)

Østergaard, Jesper

2018-01-01

UV imaging provides spatially and temporally resolved absorbance measurements, which are highly useful in pharmaceutical analysis. Commercial UV imaging instrumentation was originally developed as a detector for separation sciences, but the main use is in the area of in vitro dissolution...

Benchmarking the performance of fixed-image receptor digital radiographic systems part 1: a novel method for image quality analysis.

Science.gov (United States)

Lee, Kam L; Ireland, Timothy A; Bernardo, Michael

2016-06-01

This is the first part of a two-part study in benchmarking the performance of fixed digital radiographic general X-ray systems. This paper concentrates on reporting findings related to quantitative analysis techniques used to establish comparative image quality metrics. A systematic technical comparison of the evaluated systems is presented in part two of this study. A novel quantitative image quality analysis method is presented with technical considerations addressed for peer review. The novel method was applied to seven general radiographic systems with four different makes of radiographic image receptor (12 image receptors in total). For the System Modulation Transfer Function (sMTF), the use of grid was found to reduce veiling glare and decrease roll-off. The major contributor in sMTF degradation was found to be focal spot blurring. For the System Normalised Noise Power Spectrum (sNNPS), it was found that all systems examined had similar sNNPS responses. A mathematical model is presented to explain how the use of stationary grid may cause a difference between horizontal and vertical sNNPS responses.

Functional imaging in the Neuroscience. The role of PET, MR and SPECT

International Nuclear Information System (INIS)

Fulham, M.J.

1998-01-01

Full text: Functional imaging is commonly used to describe imaging techniques that provide data about aspects of tissue metabolism, such as glucose / protein metabolism, metabolite concentrations, neuro receptor density and blood flow / perfusion / diffusion when compared with the depiction of anatomy obtained with Computed Tomography (CT) and clinical Magnetic Resonance (MR) imaging. In the neuroscience this is a rapidly evolving area and unlike in the past where imaging of the nervous system was carried out by neuroradiologists participants in this dynamic field now come from diverse backgrounds and include basic scientists, clinicians, psychologists, physicists and chemists. PET and SPECT combine the principles of the tracer kinetic method and tomographic (as in CT) image reconstruction. A mathematical model can be derived to describe the biochemical process (in picomolar concentrations) under study and the raw counts of radioactivity that are detected by the scanner can be converted into units of physiological function in-vivo e.g. cerebral metabolic rate for glucose and receptor density. These techniques, using a variety of ligands, have been employed for evaluation of cerebral blood flow / volume, oxygen utilization / metabolism, glucose metabolism, amino acid transport / metabolism, protein synthesis, the dopaminergic, opiate, benzodiazepine, cholinergic and serotonergic systems and for brain mapping in humans. Meanwhile, the term 'functional MR imaging' encompasses MR spectroscopy, echoplanar imaging, diffusion tensor imaging and techniques that rely on the change in blood oxygenation levels to provide an indirect image of neuronal activity (referred to as fMRI). Unlike PET and SPECT, however, these data are obtained without using ionising radiation. In MRS, signals are obtained from nuclei (in mM concentrations) that are constituents of molecules other than water that provide the signal in clinical MR imaging; fibre tract directions have been depicted with

Image Analysis of Eccentric Photorefraction

Directory of Open Access Journals (Sweden)

J. Dušek

2004-01-01

Full Text Available This article deals with image and data analysis of the recorded video-sequences of strabistic infants. It describes a unique noninvasive measuring system based on two measuring methods (position of I. Purkynje image with relation to the centre of the lens and eccentric photorefraction for infants. The whole process is divided into three steps. The aim of the first step is to obtain video sequences on our special system (Eye Movement Analyser. Image analysis of the recorded sequences is performed in order to obtain curves of basic eye reactions (accommodation and convergence. The last step is to calibrate of these curves to corresponding units (diopter and degrees of movement.

Automated striatal uptake analysis of 18F-FDOPA PET images applied to Parkinson's disease patients

International Nuclear Information System (INIS)

Chang Icheng; Lue Kunhan; Hsieh Hungjen; Liu Shuhsin; Kao, Chinhao K.

2011-01-01

6-[ 18 F]Fluoro-L-DOPA (FDOPA) is a radiopharmaceutical valuable for assessing the presynaptic dopaminergic function when used with positron emission tomography (PET). More specifically, the striatal-to-occipital ratio (SOR) of FDOPA uptake images has been extensively used as a quantitative parameter in these PET studies. Our aim was to develop an easy, automated method capable of performing objective analysis of SOR in FDOPA PET images of Parkinson's disease (PD) patients. Brain images from FDOPA PET studies of 21 patients with PD and 6 healthy subjects were included in our automated striatal analyses. Images of each individual were spatially normalized into an FDOPA template. Subsequently, the image slice with the highest level of basal ganglia activity was chosen among the series of normalized images. Also, the immediate preceding and following slices of the chosen image were then selected. Finally, the summation of these three images was used to quantify and calculate the SOR values. The results obtained by automated analysis were compared with manual analysis by a trained and experienced image processing technologist. The SOR values obtained from the automated analysis had a good agreement and high correlation with manual analysis. The differences in caudate, putamen, and striatum were -0.023, -0.029, and -0.025, respectively; correlation coefficients 0.961, 0.957, and 0.972, respectively. We have successfully developed a method for automated striatal uptake analysis of FDOPA PET images. There was no significant difference between the SOR values obtained from this method and using manual analysis. Yet it is an unbiased time-saving and cost-effective program and easy to implement on a personal computer. (author)

Knowledge-based image analysis: some aspects on the analysis of images using other types of information

Energy Technology Data Exchange (ETDEWEB)

Eklundh, J O

1982-01-01

The computer vision approach to image analysis is discussed from two aspects. First, this approach is constrasted to the pattern recognition approach. Second, how external knowledge and information and models from other fields of science and engineering can be used for image and scene analysis is discussed. In particular, the connections between computer vision and computer graphics are pointed out.

Capability of differentiating smokers with normal pulmonary function from COPD patients: a comparison of CT pulmonary volume analysis and MR perfusion imaging

Energy Technology Data Exchange (ETDEWEB)

Fan, Li; Xia, Yi; Guan, Yu; Yu, Hong; Liu, Shi-yuan [Changzheng Hospital of the Second Military Medical University, Department of Radiology, Shanghai (China); Zhang, Tie-feng; Li, Bing [Changzheng Hospital of the Second Military Medical University, Department of Respiration Medicine, Shanghai (China)

2013-05-15

To compare CT volume analysis with MR perfusion imaging in differentiating smokers with normal pulmonary function (controls) from COPD patients. Sixty-two COPD patients and 17 controls were included. The total lung volume (TLV), total emphysema volume (TEV) and emphysema index (EI) were quantified by CT. MR perfusion evaluated positive enhancement integral (PEI), maximum slope of increase (MSI), maximum slope of decrease (MSD), signal enhancement ratio (SER) and signal intensity ratio (R{sub SI}) of perfusion defects to normal lung. There were 19 class I, 17 class II, 14 class III and 12 class IV COPD patients. No differences were observed in TLV, TEV and EI between control and class I COPD. The control was different from class II, III and IV COPD in TEV and EI. The control was different from each class of COPD in R{sub SI,} MSI, PEI and MSD. Differences were found in R{sub SI} between class I and III, I and IV, and II and IV COPD. Amongst controls, MR detected perfusion defects more frequently than CT detected emphysema. Compared with CT, MR perfusion imaging shows higher potential to distinguish controls from mild COPD and appears more sensitive in identifying abnormalities amongst smokers with normal pulmonary function (controls). (orig.)

Capability of differentiating smokers with normal pulmonary function from COPD patients: a comparison of CT pulmonary volume analysis and MR perfusion imaging

International Nuclear Information System (INIS)

Fan, Li; Xia, Yi; Guan, Yu; Yu, Hong; Liu, Shi-yuan; Zhang, Tie-feng; Li, Bing

2013-01-01

To compare CT volume analysis with MR perfusion imaging in differentiating smokers with normal pulmonary function (controls) from COPD patients. Sixty-two COPD patients and 17 controls were included. The total lung volume (TLV), total emphysema volume (TEV) and emphysema index (EI) were quantified by CT. MR perfusion evaluated positive enhancement integral (PEI), maximum slope of increase (MSI), maximum slope of decrease (MSD), signal enhancement ratio (SER) and signal intensity ratio (R SI ) of perfusion defects to normal lung. There were 19 class I, 17 class II, 14 class III and 12 class IV COPD patients. No differences were observed in TLV, TEV and EI between control and class I COPD. The control was different from class II, III and IV COPD in TEV and EI. The control was different from each class of COPD in R SI, MSI, PEI and MSD. Differences were found in R SI between class I and III, I and IV, and II and IV COPD. Amongst controls, MR detected perfusion defects more frequently than CT detected emphysema. Compared with CT, MR perfusion imaging shows higher potential to distinguish controls from mild COPD and appears more sensitive in identifying abnormalities amongst smokers with normal pulmonary function (controls). (orig.)

Behaviors of cost functions in image registration between 201Tl brain tumor single-photon emission computed tomography and magnetic resonance images

International Nuclear Information System (INIS)

Soma, Tsutomu; Takaki, Akihiro; Teraoka, Satomi; Ishikawa, Yasushi; Murase, Kenya; Koizumi, Kiyoshi

2008-01-01

We studied the behaviors of cost functions in the registration of thallium-201 ( 201 Tl) brain tumor single-photon emission computed tomography (SPECT) and magnetic resonance (MR) images, as the similarity index of image positioning. A marker for image registration [technetium-99m ( 99m Tc) point source] was attached at three sites on the heads of 13 patients with brain tumor, from whom 42 sets of 99m Tc- 201 Tl SPECT (the dual-isotope acquisition) and MR images were obtained. The 201 Tl SPECT and MR images were manually registered according to the markers. From the positions where the two images were registered, the position of the 201 Tl SPECT was moved to examine the behaviors of the three cost functions, i.e., ratio image uniformity (RIU), mutual information (MI), and normalized MI (NMI). The cost functions MI and NMI reached the maximum at positions adjacent to those where the SPECT and MR images were manually registered. As for the accuracy of image registration in terms of the cost functions MI and NMI, on average, the images were accurately registered within 3 deg of rotation around the X-, Y-, and Z-axes, and within 1.5 mm (within 2 pixels), 3 mm (within 3 pixels), and 4 mm (within 1 slice) of translation to the X-, Y-, and Z-axes, respectively. In terms of rotation around the Z-axis, the cost function RIU reached the minimum at positions where the manual registration of the two images was substantially inadequate. The MI and NMI were suitable cost functions in the registration of 201 Tl SPECT and MR images. The behavior of the RIU, in contrast, was unstable, being unsuitable as an index of image registration. (author)

A Hybrid Soft-computing Method for Image Analysis of Digital Plantar Scanners.

Science.gov (United States)

Razjouyan, Javad; Khayat, Omid; Siahi, Mehdi; Mansouri, Ali Alizadeh

2013-01-01

Digital foot scanners have been developed in recent years to yield anthropometrists digital image of insole with pressure distribution and anthropometric information. In this paper, a hybrid algorithm containing gray level spatial correlation (GLSC) histogram and Shanbag entropy is presented for analysis of scanned foot images. An evolutionary algorithm is also employed to find the optimum parameters of GLSC and transform function of the membership values. Resulting binary images as the thresholded images are undergone anthropometric measurements taking in to account the scale factor of pixel size to metric scale. The proposed method is finally applied to plantar images obtained through scanning feet of randomly selected subjects by a foot scanner system as our experimental setup described in the paper. Running computation time and the effects of GLSC parameters are investigated in the simulation results.

Diffusion-Tensor Imaging Findings and Cognitive Function Following Hospitalized Mixed-Mechanism Mild Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

Science.gov (United States)

Oehr, Lucy; Anderson, Jacqueline

2017-11-01

To undertake a systematic review and meta-analysis of the relationship between microstructural damage and cognitive function after hospitalized mixed-mechanism (HMM) mild traumatic brain injury (mTBI). PsycInfo, EMBASE, and MEDLINE were used to find relevant empirical articles published between January 2002 and January 2016. Studies that examined the specific relationship between diffusion tensor imaging (DTI) and cognitive test performance were included. The final sample comprised previously medically and psychiatrically healthy adults with HMM mTBI. Specific data were extracted including mTBI definitional criteria, descriptive statistics, outcome measures, and specific results of associations between DTI metrics and cognitive test performance. Of the 248 original articles retrieved and reviewed, 8 studies met all inclusion criteria and were included in the meta-analysis. The meta-analysis revealed statistically significant associations between reduced white matter integrity and poor performance on measures of attention (fractional anisotropy [FA]: d=.413, Pmemory (FA: d=.347, Pattention, memory, and executive function. These findings provide an avenue for future research to examine the causal relationship between mTBI-related neuropathology and cognitive dysfunction. Furthermore, they have important implications for clinical management of patients with mTBI because they provide a more comprehensive understanding of factors that are associated with cognitive dysfunction after mTBI. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Functional magnetic resonance imaging of the primary motor cortex

Indian Academy of Sciences (India)

Functional magnetic resonance imaging (fMRI) studies have been performed on 20 right handed volunteers at 1.5 Tesla using echo planar imaging (EPI) protocol. Index finger tapping invoked localized activation in the primary motor area. Consistent and highly reproducible activation in the primary motor area was observed ...

Mueller matrix polarimetry imaging for breast cancer analysis (Conference Presentation)

Science.gov (United States)

Gribble, Adam; Vitkin, Alex

2017-02-01

Polarized light has many applications in biomedical imaging. The interaction of a biological sample with polarized light reveals information about its biological composition, both structural and functional. The most comprehensive type of polarimetry analysis is to measure the Mueller matrix, a polarization transfer function that completely describes how a sample interacts with polarized light. However, determination of the Mueller matrix requires tissue analysis under many different states of polarized light; a time consuming and measurement intensive process. Here we address this limitation with a new rapid polarimetry system, and use this polarimetry platform to investigate a variety of tissue changes associated with breast cancer. We have recently developed a rapid polarimetry imaging platform based on four photoelastic modulators (PEMs). The PEMs generate fast polarization modulations that allow the complete sample Mueller matrix to be imaged over a large field of view, with no moving parts. This polarimetry system is then demonstrated to be sensitive to a variety of tissue changes that are relevant to breast cancer. Specifically, we show that changes in depolarization can reveal tumor margins, and can differentiate between viable and necrotic breast cancer metastasized to the lymph nodes. Furthermore, the polarimetric property of linear retardance (related to birefringence) is dependent on collagen organization in the extracellular matrix. These findings indicate that our polarimetry platform may have future applications in fields such as breast cancer diagnosis, improving the speed and efficacy of intraoperative pathology, and providing prognostic information that may be beneficial for guiding treatment.

Statistical Analysis of Compression Methods for Storing Binary Image for Low-Memory Systems

Directory of Open Access Journals (Sweden)

Roman Slaby

2013-01-01

Full Text Available The paper is focused on the statistical comparison of the selected compression methods which are used for compression of the binary images. The aim is to asses, which of presented compression method for low-memory system requires less number of bytes of memory. For assessment of the success rates of the input image to binary image the correlation functions are used. Correlation function is one of the methods of OCR algorithm used for the digitization of printed symbols. Using of compression methods is necessary for systems based on low-power micro-controllers. The data stream saving is very important for such systems with limited memory as well as the time required for decoding the compressed data. The success rate of the selected compression algorithms is evaluated using the basic characteristics of the exploratory analysis. The searched samples represent the amount of bytes needed to compress the test images, representing alphanumeric characters.

An analysis of 99mTc-DTPA renal dynamic imaging in patients with diabetes mellitus

International Nuclear Information System (INIS)

Cao Guoxiang; Zhang Yongxue

2000-01-01

To investigate the regularity of renal dynamic imaging in the various courses of diabetes mellitus, and then to provide the important evidence variety for diagnosis and treatment. The data of renal dynamic imaging was analyzed on 276 kidneys of 40 normal and 98 diabetic patients, and according to course of disease, the diabetic patients was divided into three groups: ≤1 year, 1-5 year and ≥5 year respectively. Based upon was grouped 99m Tc-DTPA renal dynamic imaging and others, the renal functions into normal, approximately normal, I, II and III injury respectively, and the statistics and analysis of these data were carried out. The extent of renal function injury was related to the course of disease significantly, and it showed that the longer the course, the heavier the damage of renal function, and there was a significant difference between them (P 99m Tc-DTPA renal dynamic imaging can effectively evaluate the extent of renal functions injury and was also valuable for the clinical. Also, the study indicated that in diabetic patients susceptible to urinary tract infection could aggravate the injury of renal function

Precise localization of dysfunctional areas in vertebro-basilar infarction by FDG- and 0-15-H2O-PET using standardized image analysis and image registration to 3-D MR

International Nuclear Information System (INIS)

Juengling, F.D.; Moser, E.; Nitzsche, E.U.; Kassubek, J.

1999-01-01

The advantages of standardized multimodal image analysis are demonstrated in a case of symptomatic tremor after basilar thrombosis. Functionally and structurally lesioned areas were mapped in Talairach space using 3-D MRI, cerebral FDG-PET and O-15-H 2 O-PET. Structural lesions were found in the left midbrain, thalamus, putamen and cerebellar areas. Voxel-based statistics in comparison to a normal data base revealed hypometabolism in the left thalamus, left red nucleus, left cerebellar hemisphere including dentate nucleus and in the left interior olivary nucleus. The O-15-H 2 O-PET investigation revealed metabolic uncoupling along the rubroolivocerebellar loop. Given the delicate anatomy of the structures involved, image registration and standardized image analysis techniques are essential for a synoptic multimodality analysis of morphological and functional pathology and should generally be used for cerebral PET investigations. (orig.) [de

Convolutional Sparse Coding for Static and Dynamic Images Analysis

Directory of Open Access Journals (Sweden)

B. A. Knyazev

2014-01-01

Full Text Available The objective of this work is to improve performance of static and dynamic objects recognition. For this purpose a new image representation model and a transformation algorithm are proposed. It is examined and illustrated that limitations of previous methods make it difficult to achieve this objective. Static images, specifically handwritten digits of the widely used MNIST dataset, are the primary focus of this work. Nevertheless, preliminary qualitative results of image sequences analysis based on the suggested model are presented.A general analytical form of the Gabor function, often employed to generate filters, is described and discussed. In this research, this description is required for computing parameters of responses returned by our algorithm. The recursive convolution operator is introduced, which allows extracting free shape features of visual objects. The developed parametric representation model is compared with sparse coding based on energy function minimization.In the experimental part of this work, errors of estimating the parameters of responses are determined. Also, parameters statistics and their correlation coefficients for more than 106 responses extracted from the MNIST dataset are calculated. It is demonstrated that these data correspond well with previous research studies on Gabor filters as well as with works on visual cortex primary cells of mammals, in which similar responses were observed. A comparative test of the developed model with three other approaches is conducted; speed and accuracy scores of handwritten digits classification are presented. A support vector machine with a linear or radial basic function is used for classification of images and their representations while principal component analysis is used in some cases to prepare data beforehand. High accuracy is not attained due to the specific difficulties of combining our model with a support vector machine (a 3.99% error rate. However, another method is

A hybrid correlation analysis with application to imaging genetics

Science.gov (United States)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

Pre-clinical functional magnetic resonance imaging. Pt. I. The kidney

Energy Technology Data Exchange (ETDEWEB)

Zoellner, Frank G.; Kalayciyan, Raffi; Chacon-Caldera, Jorge; Zimmer, Fabian; Schad, Lothar R. [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine

2014-07-01

The prevalence of chronic kidney disease (CKD) is increasing worldwide. In Europe alone, at least 8% of the population currently has some degree of CKD. CKD is associated with serious comorbidity, reduced life expectancy, and high economic costs; hence, the early detection and adequate treatment of kidney disease is important. Pre-clinical research can not only give insights into the mechanisms of the various kidney diseases but it also allows for investigating the outcome of new drugs developed to treat kidney disease. Functional magnetic resonance imaging provides non-invasive access to tissue and organ function in animal models. Advantages over classical animal research approaches are numerous: the same animal might be repeatedly imaged to investigate a progress or a treatment of disease over time. This has also a direct impact on animal welfare and the refinement of classical animal experiments as the number of animals in the studies might be reduced. In this paper, we review current state of the art in functional magnetic resonance imaging with a focus on pre-clinical kidney imaging.

Pre-clinical functional magnetic resonance imaging. Pt. I. The kidney

International Nuclear Information System (INIS)

Zoellner, Frank G.; Kalayciyan, Raffi; Chacon-Caldera, Jorge; Zimmer, Fabian; Schad, Lothar R.

2014-01-01

The prevalence of chronic kidney disease (CKD) is increasing worldwide. In Europe alone, at least 8% of the population currently has some degree of CKD. CKD is associated with serious comorbidity, reduced life expectancy, and high economic costs; hence, the early detection and adequate treatment of kidney disease is important. Pre-clinical research can not only give insights into the mechanisms of the various kidney diseases but it also allows for investigating the outcome of new drugs developed to treat kidney disease. Functional magnetic resonance imaging provides non-invasive access to tissue and organ function in animal models. Advantages over classical animal research approaches are numerous: the same animal might be repeatedly imaged to investigate a progress or a treatment of disease over time. This has also a direct impact on animal welfare and the refinement of classical animal experiments as the number of animals in the studies might be reduced. In this paper, we review current state of the art in functional magnetic resonance imaging with a focus on pre-clinical kidney imaging.

Lung function imaging methods in Cystic Fibrosis pulmonary disease.

Science.gov (United States)

Kołodziej, Magdalena; de Veer, Michael J; Cholewa, Marian; Egan, Gary F; Thompson, Bruce R

2017-05-17

Monitoring of pulmonary physiology is fundamental to the clinical management of patients with Cystic Fibrosis. The current standard clinical practise uses spirometry to assess lung function which delivers a clinically relevant functional readout of total lung function, however does not supply any visible or localised information. High Resolution Computed Tomography (HRCT) is a well-established current 'gold standard' method for monitoring lung anatomical changes in Cystic Fibrosis patients. HRCT provides excellent morphological information, however, the X-ray radiation dose can become significant if multiple scans are required to monitor chronic diseases such as cystic fibrosis. X-ray phase-contrast imaging is another emerging X-ray based methodology for Cystic Fibrosis lung assessment which provides dynamic morphological and functional information, albeit with even higher X-ray doses than HRCT. Magnetic Resonance Imaging (MRI) is a non-ionising radiation imaging method that is garnering growing interest among researchers and clinicians working with Cystic Fibrosis patients. Recent advances in MRI have opened up the possibilities to observe lung function in real time to potentially allow sensitive and accurate assessment of disease progression. The use of hyperpolarized gas or non-contrast enhanced MRI can be tailored to clinical needs. While MRI offers significant promise it still suffers from poor spatial resolution and the development of an objective scoring system especially for ventilation assessment.

Imaging of carotid artery disease: from luminology to function?

Energy Technology Data Exchange (ETDEWEB)

Gillard, J.H. [University Department of Radiology, Addenbrooke' s Hospital, Cambridge (United Kingdom)

2003-10-01

There have been tremendous advances in our ability to image atheromatous disease, particularly in the carotid artery, which is accessible and large enough to image. The repertoire of methodology available is growing, giving anatomical information on luminal narrowing which is approaching the level at which conventional carotid angiography will become very uncommon as CT and contrast-enhanced MR angiographic techniques become the norm. More exciting is the tentative ability to perform functional plaque imaging addressing enhancement patterns and macrophage activity using MR or positron-emission tomography techniques. These techniques, once rigorously evaluated, may, in addition to complex mathematical modelling of plaque, eventually allow us to assess true plaque risk. Time will best judge whether we will be able to move from the use of simple luminology to assessment of plaque function. (orig.)

Imaging of carotid artery disease: from luminology to function?

International Nuclear Information System (INIS)

Gillard, J.H.

2003-01-01

There have been tremendous advances in our ability to image atheromatous disease, particularly in the carotid artery, which is accessible and large enough to image. The repertoire of methodology available is growing, giving anatomical information on luminal narrowing which is approaching the level at which conventional carotid angiography will become very uncommon as CT and contrast-enhanced MR angiographic techniques become the norm. More exciting is the tentative ability to perform functional plaque imaging addressing enhancement patterns and macrophage activity using MR or positron-emission tomography techniques. These techniques, once rigorously evaluated, may, in addition to complex mathematical modelling of plaque, eventually allow us to assess true plaque risk. Time will best judge whether we will be able to move from the use of simple luminology to assessment of plaque function. (orig.)

Functional analysis and applications

CERN Document Server

Siddiqi, Abul Hasan

2018-01-01

This self-contained textbook discusses all major topics in functional analysis. Combining classical materials with new methods, it supplies numerous relevant solved examples and problems and discusses the applications of functional analysis in diverse fields. The book is unique in its scope, and a variety of applications of functional analysis and operator-theoretic methods are devoted to each area of application. Each chapter includes a set of problems, some of which are routine and elementary, and some of which are more advanced. The book is primarily intended as a textbook for graduate and advanced undergraduate students in applied mathematics and engineering. It offers several attractive features making it ideally suited for courses on functional analysis intended to provide a basic introduction to the subject and the impact of functional analysis on applied and computational mathematics, nonlinear functional analysis and optimization. It introduces emerging topics like wavelets, Gabor system, inverse pro...

Visual grading of 2D and 3D functional MRI compared with image-based descriptive measures

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Ragnehed, Mattias [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Linkoeping University, Department of Medical and Health Sciences, Division of Radiological Sciences/Radiology, Faculty of Health Sciences, Linkoeping (Sweden); Leinhard, Olof Dahlqvist; Pihlsgaard, Johan; Lundberg, Peter [Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Linkoeping University, Division of Radiological Sciences, Radiation Physics, IMH, Linkoeping (Sweden); Wirell, Staffan [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University Hospital, Department of Radiology, Linkoeping (Sweden); Soekjer, Hannibal; Faegerstam, Patrik [Linkoeping University Hospital, Department of Radiology, Linkoeping (Sweden); Jiang, Bo [Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden); Smedby, Oerjan; Engstroem, Maria [Linkoeping University, Division of Radiological Sciences, Radiology, IMH, Linkoeping (Sweden); Linkoeping University, Center for Medical Image Science and Visualization, CMIV, Linkoeping (Sweden)

2010-03-15

A prerequisite for successful clinical use of functional magnetic resonance imaging (fMRI) is the selection of an appropriate imaging sequence. The aim of this study was to compare 2D and 3D fMRI sequences using different image quality assessment methods. Descriptive image measures, such as activation volume and temporal signal-to-noise ratio (TSNR), were compared with results from visual grading characteristics (VGC) analysis of the fMRI results. Significant differences in activation volume and TSNR were not directly reflected by differences in VGC scores. The results suggest that better performance on descriptive image measures is not always an indicator of improved diagnostic quality of the fMRI results. In addition to descriptive image measures, it is important to include measures of diagnostic quality when comparing different fMRI data acquisition methods. (orig.)

Resting functional imaging tools (MRS, SPECT, PET and PCT).

Science.gov (United States)

Van Der Naalt, J

2015-01-01

Functional imaging includes imaging techniques that provide information about the metabolic and hemodynamic status of the brain. Most commonly applied functional imaging techniques in patients with traumatic brain injury (TBI) include magnetic resonance spectroscopy (MRS), single photon emission computed tomography (SPECT), positron emission tomography (PET) and perfusion CT (PCT). These imaging modalities are used to determine the extent of injury, to provide information for the prediction of outcome, and to assess evidence of cerebral ischemia. In TBI, secondary brain damage mainly comprises ischemia and is present in more than 80% of fatal cases with traumatic brain injury (Graham et al., 1989; Bouma et al., 1991; Coles et al., 2004). In particular, while SPECT measures cerebral perfusion and MRS determines metabolism, PET is able to assess both perfusion and cerebral metabolism. This chapter will describe the application of these techniques in traumatic brain injury separately for the major groups of severity comprising the mild and moderate to severe group. The application in TBI and potential difficulties of each technique is described. The use of imaging techniques in children will be separately outlined. © 2015 Elsevier B.V. All rights reserved.

Use of 4-Dimensional Computed Tomography-Based Ventilation Imaging to Correlate Lung Dose and Function With Clinical Outcomes

International Nuclear Information System (INIS)

Vinogradskiy, Yevgeniy; Castillo, Richard; Castillo, Edward; Tucker, Susan L.; Liao, Zhongxing; Guerrero, Thomas; Martel, Mary K.

2013-01-01

Purpose: Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity. Methods and Materials: Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose–volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose–volume and ventilation-based dose–function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods. Results: A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose–function metrics (range P=.093-.250) than for their dose–volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose–function metrics (range, 0.569-0.620) than for their dose–volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose–function metrics compared to dose–volume metrics that approached significance (range, P=.118-.155). Conclusions: To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests

Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

Science.gov (United States)

Daly, Scott J.

1989-08-01

The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

Implementation of digital image encryption algorithm using logistic function and DNA encoding

Science.gov (United States)

Suryadi, MT; Satria, Yudi; Fauzi, Muhammad

2018-03-01

Cryptography is a method to secure information that might be in form of digital image. Based on past research, in order to increase security level of chaos based encryption algorithm and DNA based encryption algorithm, encryption algorithm using logistic function and DNA encoding was proposed. Digital image encryption algorithm using logistic function and DNA encoding use DNA encoding to scramble the pixel values into DNA base and scramble it in DNA addition, DNA complement, and XOR operation. The logistic function in this algorithm used as random number generator needed in DNA complement and XOR operation. The result of the test show that the PSNR values of cipher images are 7.98-7.99 bits, the entropy values are close to 8, the histogram of cipher images are uniformly distributed and the correlation coefficient of cipher images are near 0. Thus, the cipher image can be decrypted perfectly and the encryption algorithm has good resistance to entropy attack and statistical attack.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

Science.gov (United States)

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Content-addressable read/write memories for image analysis

Science.gov (United States)

Snyder, W. E.; Savage, C. D.

1982-01-01

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

Automated image analysis of atomic force microscopy images of rotavirus particles

International Nuclear Information System (INIS)

Venkataraman, S.; Allison, D.P.; Qi, H.; Morrell-Falvey, J.L.; Kallewaard, N.L.; Crowe, J.E.; Doktycz, M.J.

2006-01-01

A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM

Automated image analysis of atomic force microscopy images of rotavirus particles

Energy Technology Data Exchange (ETDEWEB)

Venkataraman, S. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Allison, D.P. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Department of Biochemistry, Cellular, and Molecular Biology, University of Tennessee, Knoxville, TN 37996 (United States); Molecular Imaging Inc. Tempe, AZ, 85282 (United States); Qi, H. [Department of Electrical and Computer Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Morrell-Falvey, J.L. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Kallewaard, N.L. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Crowe, J.E. [Vanderbilt University Medical Center, Nashville, TN 37232-2905 (United States); Doktycz, M.J. [Life Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States)]. E-mail: doktyczmj@ornl.gov

2006-06-15

A variety of biological samples can be imaged by the atomic force microscope (AFM) under environments that range from vacuum to ambient to liquid. Generally imaging is pursued to evaluate structural features of the sample or perhaps identify some structural changes in the sample that are induced by the investigator. In many cases, AFM images of sample features and induced structural changes are interpreted in general qualitative terms such as markedly smaller or larger, rougher, highly irregular, or smooth. Various manual tools can be used to analyze images and extract more quantitative data, but this is usually a cumbersome process. To facilitate quantitative AFM imaging, automated image analysis routines are being developed. Viral particles imaged in water were used as a test case to develop an algorithm that automatically extracts average dimensional information from a large set of individual particles. The extracted information allows statistical analyses of the dimensional characteristics of the particles and facilitates interpretation related to the binding of the particles to the surface. This algorithm is being extended for analysis of other biological samples and physical objects that are imaged by AFM.

Image analysis for ophthalmological diagnosis image processing of Corvis ST images using Matlab

CERN Document Server

Koprowski, Robert

2016-01-01

This monograph focuses on the use of analysis and processing methods for images from the Corvis® ST tonometer. The presented analysis is associated with the quantitative, repeatable and fully automatic evaluation of the response of the eye, eyeball and cornea to an air-puff. All the described algorithms were practically implemented in MATLAB®. The monograph also describes and provides the full source code designed to perform the discussed calculations. As a result, this monograph is intended for scientists, graduate students and students of computer science and bioengineering as well as doctors wishing to expand their knowledge of modern diagnostic methods assisted by various image analysis and processing methods.

Imaging insights into basal ganglia function, Parkinson’s disease, and dystonia

Science.gov (United States)

Stoessl, A. Jon; Lehericy, Stephane; Strafella, Antonio P.

2015-01-01

Recent advances in structural and functional imaging have greatly improved our ability to assess normal functions of the basal ganglia, diagnose parkinsonian syndromes, understand the pathophysiology of parkinsonism and other movement disorders, and detect and monitor disease progression. Radionuclide imaging is the best way to detect and monitor dopamine deficiency, and will probably continue to be the best biomarker for assessment of the effects of disease-modifying therapies. However, advances in magnetic resonance enable the separation of patients with Parkinson’s disease from healthy controls, and show great promise for differentiation between Parkinson’s disease and other akinetic-rigid syndromes. Radionuclide imaging is useful to show the dopaminergic basis for both motor and behavioural complications of Parkinson’s disease and its treatment, and alterations in non-dopaminergic systems. Both PET and MRI can be used to study patterns of functional connectivity in the brain, which is disrupted in Parkinson’s disease and in association with its complications, and in other basal-ganglia disorders such as dystonia, in which an anatomical substrate is not otherwise apparent. Functional imaging is increasingly used to assess underlying pathological processes such as neuroinflammation and abnormal protein deposition. This imaging is another promising approach to assess the effects of treatments designed to slow disease progression. PMID:24954673

Correlative studies of structural and functional imaging in primary progressive aphasia.

Science.gov (United States)

Panegyres, P K; McCarthy, M; Campbell, A; Lenzo, N; Fallon, M; Thompson, J

2008-01-01

To compare and contrast structural and functional imaging in primary progressive aphasia (PPA). A cohort of 8 patients diagnosed with PPA presenting with nonfluency were prospectively evaluated. All patients had structural imaging in the form of MRI and in 1 patient CAT scanning on account of a cardiac pacemaker. All patients had single-photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging. SPECT and PET imaging had 100% correlation. Anatomical imaging was abnormal in only 6 of the 8 patients. Wernicke's area showed greater peak Z score reduction and extent of area affected than Broca's area (McNemar paired test: P = .008 for Z score reduction; P = .0003 for extent). PET scanning revealed significant involvement of the anterior cingulum. Functional imaging in PPA: (a) identified more patients correctly than anatomic imaging highlighting the importance of SPECT and PET in the diagnosis; and (b) demonstrated the heterogeneous involvement of disordered linguistic networks in PPA suggesting its syndromic nature.

Cerebral Small Vessel Disease: Cognition, Mood, Daily Functioning, and Imaging Findings from a Small Pilot Sample

Directory of Open Access Journals (Sweden)

John G. Baker

2012-04-01

Full Text Available Cerebral small vessel disease, a leading cause of cognitive decline, is considered a relatively homogeneous disease process, and it can co-occur with Alzheimer’s disease. Clinical reports of magnetic resonance imaging (MRI/computed tomography and single photon emission computed tomography (SPECT imaging and neuropsychology testing for a small pilot sample of 14 patients are presented to illustrate disease characteristics through findings from structural and functional imaging and cognitive assessment. Participants showed some decreases in executive functioning, attention, processing speed, and memory retrieval, consistent with previous literature. An older subgroup showed lower age-corrected scores at a single time point compared to younger participants. Performance on a computer-administered cognitive measure showed a slight overall decline over a period of 8–28 months. For a case study with mild neuropsychology findings, the MRI report was normal while the SPECT report identified perfusion abnormalities. Future research can test whether advances in imaging analysis allow for identification of cerebral small vessel disease before changes are detected in cognition.

NEPHRUS: model of intelligent multilayers expert system for evaluation of the renal system based on scintigraphic images analysis

International Nuclear Information System (INIS)

Silva, Jose W.E. da; Schirru, Roberto; Boasquevisque, Edson M.

1997-01-01

This work develops a prototype for the system model based on Artificial Intelligence devices able to perform functions related to scintigraphic image analysis of the urinary system. Criteria used by medical experts for analysis images obtained with 99m Tc+DTPA and/or 99m Tc+DMSA were modeled and a multi resolution diagnosis technique was implemented. Special attention was given to the programs user interface design. Human Factor Engineering techniques were considered so as to ally friendliness and robustness. Results obtained using Artificial Neural Networks for the qualitative image analysis and the knowledge model constructed shows the feasibility of Artificial Intelligence implementation that use 'inherent' abilities of each technique in the resolution of diagnosis image analysis problems. (author). 12 refs., 2 figs., 2 tabs

Use of digital image analysis to estimate fluid permeability of porous materials: Application of two-point correlation functions

International Nuclear Information System (INIS)

Berryman, J.G.; Blair, S.C.

1986-01-01

Scanning electron microscope images of cross sections of several porous specimens have been digitized and analyzed using image processing techniques. The porosity and specific surface area may be estimated directly from measured two-point spatial correlation functions. The measured values of porosity and image specific surface were combined with known values of electrical formation factors to estimate fluid permeability using one version of the Kozeny-Carman empirical relation. For glass bead samples with measured permeability values in the range of a few darcies, our estimates agree well ( +- 10--20%) with the measurements. For samples of Ironton-Galesville sandstone with a permeability in the range of hundreds of millidarcies, our best results agree with the laboratory measurements again within about 20%. For Berea sandstone with still lower permeability (tens of millidarcies), our predictions from the images agree within 10--30%. Best results for the sandstones were obtained by using the porosities obtained at magnifications of about 100 x (since less resolution and better statistics are required) and the image specific surface obtained at magnifications of about 500 x (since greater resolution is required)

Computer image analysis of etched tracks from ionizing radiation

Science.gov (United States)

Blanford, George E.

1994-01-01

I proposed to continue a cooperative research project with Dr. David S. McKay concerning image analysis of tracks. Last summer we showed that we could measure track densities using the Oxford Instruments eXL computer and software that is attached to an ISI scanning electron microscope (SEM) located in building 31 at JSC. To reduce the dependence on JSC equipment, we proposed to transfer the SEM images to UHCL for analysis. Last summer we developed techniques to use digitized scanning electron micrographs and computer image analysis programs to measure track densities in lunar soil grains. Tracks were formed by highly ionizing solar energetic particles and cosmic rays during near surface exposure on the Moon. The track densities are related to the exposure conditions (depth and time). Distributions of the number of grains as a function of their track densities can reveal the modality of soil maturation. As part of a consortium effort to better understand the maturation of lunar soil and its relation to its infrared reflectance properties, we worked on lunar samples 67701,205 and 61221,134. These samples were etched for a shorter time (6 hours) than last summer's sample and this difference has presented problems for establishing the correct analysis conditions. We used computer counting and measurement of area to obtain preliminary track densities and a track density distribution that we could interpret for sample 67701,205. This sample is a submature soil consisting of approximately 85 percent mature soil mixed with approximately 15 percent immature, but not pristine, soil.

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

International Nuclear Information System (INIS)

Kotasidis, Fotis A.; Zaidi, Habib

2014-01-01

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis function

Experimental evaluation and basis function optimization of the spatially variant image-space PSF on the Ingenuity PET/MR scanner

Energy Technology Data Exchange (ETDEWEB)

Kotasidis, Fotis A., E-mail: Fotis.Kotasidis@unige.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland and Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland); Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, 9700 RB (Netherlands)

2014-06-15

Purpose: The Ingenuity time-of-flight (TF) PET/MR is a recently developed hybrid scanner combining the molecular imaging capabilities of PET with the excellent soft tissue contrast of MRI. It is becoming common practice to characterize the system's point spread function (PSF) and understand its variation under spatial transformations to guide clinical studies and potentially use it within resolution recovery image reconstruction algorithms. Furthermore, due to the system's utilization of overlapping and spherical symmetric Kaiser-Bessel basis functions during image reconstruction, its image space PSF and reconstructed spatial resolution could be affected by the selection of the basis function parameters. Hence, a detailed investigation into the multidimensional basis function parameter space is needed to evaluate the impact of these parameters on spatial resolution. Methods: Using an array of 12 × 7 printed point sources, along with a custom made phantom, and with the MR magnet on, the system's spatially variant image-based PSF was characterized in detail. Moreover, basis function parameters were systematically varied during reconstruction (list-mode TF OSEM) to evaluate their impact on the reconstructed resolution and the image space PSF. Following the spatial resolution optimization, phantom, and clinical studies were subsequently reconstructed using representative basis function parameters. Results: Based on the analysis and under standard basis function parameters, the axial and tangential components of the PSF were found to be almost invariant under spatial transformations (∼4 mm) while the radial component varied modestly from 4 to 6.7 mm. Using a systematic investigation into the basis function parameter space, the spatial resolution was found to degrade for basis functions with a large radius and small shape parameter. However, it was found that optimizing the spatial resolution in the reconstructed PET images, while having a good basis