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Graphical methods for quantifying macromolecules through bright field imaging

BIOINFORMATICS 2009年第8期25卷 1070-1075页

作者： Chang, Hang DeFilippis, Rosa Anna Tlsty, Thea D. Parvin, Bahram Univ Calif Berkeley Lawrence Berkeley Lab Berkeley CA 94720 USA Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Calif San Francisco Dept Pathol San Francisco CA USA Univ Calif Riverside Dept Elect Engn Riverside CA 92521 USA

Bright field imaging of biological samples stained with antibodies and/or special stains provides a rapid protocol for visualizing various macromolecules. However, this method of sample staining and imaging is rarely employed for direct quantitative analysis due to variations in sample fixations, ambiguities introduced by color composition and the limited dynamic range of imaging instruments. We demonstrate that, through the decomposition of color signals, staining can be scored on a cell-by-cell basis. We have applied our method to fibroblasts grown from histologically normal breast tissue biopsies obtained from two distinct populations. Initially, nuclear regions are segmented through conversion of color images into gray scale, and detection of dark elliptic features. Subsequently, the strength of staining is quantified by a color decomposition model that is optimized by a graph cut algorithm. In rare cases where nuclear signal is significantly altered as a result of sample preparation, nuclear segmentation can be validated and corrected. Finally, segmented stained patterns are associated with each nuclear region following region-based tessellation. Compared to classical non-negative matrix factorization, proposed method: (i) improves color decomposition, (ii) has a better noise immunity, (iii) is more invariant to initial conditions and (iv) has a superior computing performance.

关键词： Algorithms Animals Humans image Enhancement/methods image processing, computer-assisted/methods Pattern Recognition, Automated/methods

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Magnetization transfer contrast imaging reveals amyloid pathology in Alzheimer's disease transgenic mice

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NEUROimage 2014年 87卷 111-119页

作者： Bigot, Christian Vanhoutte, Greetje Verhoye, Marleen Van der Linden, Annemie Univ Antwerp Bioimaging Lab B-2610 Antwerp Belgium

The presence of amyloid plaques in the brain is one of the pathological hallmarks of Alzheimer's disease, which might already be present in the early stage of the disease. Therefore it is important to track amyloid plaques as early as possible. In this paper, we report magnetization transfer contrast magnetic resonance imaging (MTC MRI) as a novel approach to detect amyloid plaques in vivo. Two mice models, APP/PSI and BRI, developing amyloid pathology were investigated with MTC MB], T-2 relaxation measurements and immunohistochemistry (IHC). MT-ratios of several brain regions were compared to T-2-values and correlated with quantitative IHC, revealing amyloid load and gliosis in different brain regions. APP/PS1 mice develop large compact plaques, resembling late stage Alzheimer's disease, while rather small and diffuse plaques are deposited in BRI mice, reflecting early stage of Alzheimer's disease. We found significantly higher MT-ratio's in the brain of APP/PSI mice as compared to their controls and similar trends in BR! mice. A region based MT-ratio and IHC analysis and correlations between MT-ratios and quantitative IHC indicate amyloid plaques as the main substrate for altered MT-ratios in transgenic animals. We additionally demonstrated the improved sensitivity of MTC MB] to amyloid pathology as compared to traditional T-2 relaxation measurements. Our results suggest that MTC MRI reveals extensive, and potentially even early amyloid pathology. Further unraveling the MT-effect of each pathological feature during each stage of AD might indicate MTC MB] as a useful diagnostic technique. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Alzheimer Disease/pathology Animals Brain/pathology Contrast Media Contrast Media Disease Models, Animal Female image processing, computer-assisted/methods Immunohistochemistry Immunohistochemistry Magnetic Resonance Imaging/methods Male Mice Mice, Transgenic Mice, Transgenic Plaque, Amyloid/pathology

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Imagine that! ERPs provide evidence for distinct hemispheric contributions to the processing of concrete and abstract concepts

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NEUROimage 2010年第1期49卷 1116-1123页

作者： Huang, Hsu-Wen Lee, Chia-Lin Federmeier, Kara D. Univ Illinois Dept Psychol Champaign IL 61820 USA Univ Illinois Program Neurosci Champaign IL 61820 USA Univ Illinois Beckman Inst Adv Sci & Technol Champaign IL 61820 USA

Although abstract and concrete concepts are processed and remembered differently, the underlying nature of those differences remains in dispute. The current study used visual half-field (VF) presentation methods and event-related potential (ERP) measures to examine how the left (LH) and right (RH) cerebral hemispheres process concrete and abstract meanings of polysemous nouns (e.g., "green book," referring to the concrete, physical object that is a book, versus "engaging book," referring to the abstract information that a book conveys). With presentation to the right VF, nouns preceded by concrete modifiers were associated with more positivity on the P2 and N400, suggesting that concrete concepts were easier for the LH to process perceptually and semantically. In contrast, with presentation to the left VF (RH), nouns used in a concrete sense elicited a sustained frontal negativity (500-900 ms) that has been previously linked to imagery. The results thus reveal multiple, distinct neural and cognitive sources for concreteness effects and point to a critical role for the RH in linking language input to sensory imagery. (C) 2009 Elsevier Inc. All Fights reserved.

关键词： Adolescent Adult Brain/physiology Brain Mapping Brain Mapping Electroencephalography Evoked Potentials/physiology Executive Function/physiology Female Functional Laterality/physiology Humans image processing, computer-assisted/methods Imagination/physiology Male Mental Processes/physiology Photic Stimulation Psycholinguistics Psychomotor Performance/physiology Reading Visual Fields/physiology Young Adult

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Virtual definition of neuronal tissue by cluster analysis of multi-parametric imaging (virtual-dot-com imaging)

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NEUROimage 2007年第1期35卷 58-69页

作者： Yovel, Yssi Assaf, Yaniv Tel Aviv Univ Fac Life Sci Dept Neurobiochem IL-69978 Tel Aviv Israel Tel Aviv Sourasky Med Ctr Levie Edersheim Gitter Inst Funct Brain Imaging Tel Aviv Israel

Individual mapping of cerebral, morphological, functionally related structures using MRI was carried, out using a, new multi-contrast acquisition and analysis framework, called virtual-dot-com imaging. So far, conventional anatomical MRI has been able to proyide gross segmentation of gray/white matter boundaries and a few sub-cortical structures. By combining a, handful of imaging contrasts mechanisms (T1, T2, magnetization transfer, T2* and proton density), we were able to further segment sub-cortical tissue to its sub-nuclei arrangement, a segmentation that is difficult based on conventional, single-contrast MRI. Using an automatic four-step image and signal processing algorithm, we segmented the thalamus to at least 7 subnuclei with high similarity across subjects and high statistical significance within subjects (p < 0.0001). The identified sub-nuclei resembled the known anatomical arrangement of the thalamus given in various atlases. Each cluster was characterized by a unique MRI contrast fingerprint. With this procedure, the weighted proportions of the different cellular compartments could be estimated, a property available to date only by histological analysis. Each sub-nucleus could be characterized in terms of normalized MRI contrast and compared to other sub-nuclei. The different weights of the contrasts (T1/T2/T2*/ PD/MT, etc.) for each sub-nuclei cluster might indicate the intracluster morphological arrangement of the tissue that it represents. The implications of this methodology are far-ranging, from non-invasive, in vivo, individual mapping of histologically distinct brain areas to automatic identification of pathological processes. (c) 2006 Elsevier Inc. All rights reserved.

关键词： Adult Algorithms Animals Cluster Analysis computer Graphics Humans image processing, computer-assisted/methods image processing, computer-assisted/statistics & numerical data Individuality Magnetic Resonance Imaging/methods Magnetic Resonance Imaging/statistics & numerical data Male Nerve Tissue/anatomy & histology Rats Thalamic Nuclei/anatomy & histology Thalamus/anatomy & histology

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Imaging cortical dynamics at high spatial and temporal resolution with novel blue voltage-sensitive dyes

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NEURON 1999年第4期24卷 791-802页

作者： Shoham, D Glaser, DE Arieli, A Kenet, T Wijnbergen, C Toledo, Y Hildesheim, R Grinvald, A Weizmann Inst Sci Dept Neurobiol IL-76100 Rehovot Israel

Conventional imaging techniques have provided high-resolution imaging either in the spatial domain or in the temporal domain. Optical imaging utilizing voltage-sensitive dyes has long had the unrealized potential to achieve high resolution in both domains simultaneously, providing subcolumnar spatial detail with millisecond precision. Here, we present a series of developments in voltage-sensitive dyes and instrumentation that make functional imaging of cortical dynamics practical, in both anesthetized and awake behaving preparations, greatly facilitating exploration of the cortex. We illustrate this advance by analyzing the millisecond-by-millisecond emergence of orientation maps in cat visual cortex.

关键词： Animals Brain Mapping Brain Mapping Cats Cerebral Cortex/anatomy & histology Cerebral Cortex/physiology Coloring Agents/diagnostic use Electrophysiology Haplorhini Heart Rate/physiology image processing, computer-assisted/methods Orientation/physiology Photic Stimulation Rats

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Self responses along cingulate cortex reveal quantitative neural phenotype for high-functioning autism

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NEURON 2008年第3期57卷 463-473页

作者： Chiu, Pearl H. Kayali, M. Amin Kishida, Kenneth T. Tomlin, Damon Klinger, Laura G. Klinger, Mark R. Montague, P. Read Baylor Coll Med Comp Psychiat Unit Houston TX 77030 USA Baylor Coll Med Div Neurosci Houston TX 77030 USA Baylor Coll Med Menninger Dept Psychiat & Behav Sci Houston TX 77030 USA Univ Alabama Dept Psychol Tuscaloosa AL 35487 USA

Attributing behavioral outcomes correctly to oneself or to other agents is essential for all productive social exchange. We approach this issue in high-functioning males with autism spectrum disorder (ASD) using two separate fMRI paradigms. First, using a visual imagery task, we extract a basis set for responses along the cingulate cortex of control subjects that reveals an agent-specific eigenvector (self eigenmode) associated with imagining oneself executing a specific motor act. Second, we show that the same self eigenmode arises during one's own decision (the self phase) in an interpersonal exchange game (iterated trust game). Third, using this exchange game, we show that ASD males exhibit a severely diminished cingulate self response when playing the game with a human partner. This diminishment covaries parametrically with their behaviorally assessed symptom severity, suggesting its value as an objective endophenotype. These findings may provide a quantitative assessment tool for high-functioning ASD.

关键词： Adolescent Adult Autistic Disorder/pathology Autistic Disorder/physiopathology Autistic Disorder/psychology Brain Mapping Brain Mapping Case-Control Studies Gyrus Cinguli/blood supply Gyrus Cinguli/physiopathology Humans image processing, computer-assisted/methods Imitative Behavior/physiology Magnetic Resonance Imaging/methods Male Mental Processes/physiology Neuropsychological Tests Oxygen/blood Phenotype Photic Stimulation/methods Principal Component Analysis Self Concept

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Decoding fMRI brain states in real-time

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NEUROimage 2011年第2期56卷 440-454页

作者： LaConte, Stephen M. Baylor Coll Med Dept Neurosci Houston TX 77030 USA

This article reviews a technological advance that originates from two areas of ongoing neuroimaging innovation-(1) the use of multivariate supervised learning to decode brain states and (2) real-time functional magnetic resonance imaging (rtfMRI). The approach uses multivariate methods to train a model capable of decoding a subject's brain state from fMRI images. The decoded brain states can be used as a control signal for a brain computer interface (BCI) or to provide neurofeedback to the subject. The ability to adapt the stimulus during the fMRI experiment adds a new level of flexibility for task paradigms and has potential applications in a number of areas, including performance enhancement, rehabilitation, and therapy. Multivariate approaches to real-time fMRI are complementary to region-of-interest (ROI)-based methods and provide a principled method for dealing with distributed patterns of brain responses. Specifically, a multivariate approach is advantageous when network activity is expected, when mental strategies could vary from individual to individual, or when one or a few ROIs are not unequivocally the most appropriate for the investigation. Beyond highlighting important developments in rtfMRI and supervised learning, the article discusses important practical issues, including implementation considerations, existing resources, and future challenges and opportunities. Some possible future directions are described, calling for advances arising from increased experimental flexibility, improvements in predictive modeling, better comparisons across rtfMRI and other BCI implementations, and further investigation of the types of feedback and degree to which interface modulation is obtainable for various tasks. (C) 2010 Published by Elsevier Inc.

关键词： Artificial Intelligence Brain/physiology Brain Mapping/methods Brain Mapping/methods Humans image processing, computer-assisted/methods Magnetic Resonance Imaging Neurofeedback

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Spatial HARDI: Improved visualization of complex white matter architecture with Bayesian spatial regularization

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NEUROimage 2011年第1期54卷 396-409页

作者： Raj, Ashish Hess, Christopher Mukherjee, Pratik Cornell Univ Weill Med Coll Dept Radiol New York NY 10044 USA Univ Calif San Francisco Dept Radiol & Bioengn San Francisco CA 94143 USA Univ Calif San Francisco Dept Bioengn & Therapeut Sci San Francisco CA 94143 USA

Imaging of water diffusion using magnetic resonance imaging has become an important noninvasive method for probing the white matter connectivity of the human brain for scientific and clinical studies. Current methods, such as diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI) such as q-ball imaging, and diffusion spectrum imaging (DSI), are limited by low spatial resolution, long scan times, and low signal-to-noise ratio (SNR). These methods fundamentally perform reconstruction on a voxel-by-voxel level, effectively discarding the natural coherence of the data at different points in space. This paper attempts to overcome these tradeoffs by using spatial information to constrain the reconstruction from raw diffusion MRI data, and thereby improve angular resolution and noise tolerance. Spatial constraints are specified in terms of a prior probability distribution, which is then incorporated in a Bayesian reconstruction formulation. By taking the log of the resulting posterior distribution, optimal Bayesian reconstruction is reduced to a cost minimization problem. The minimization is solved using a new iterative algorithm based on successive least squares quadratic descent. Simulation studies and in vivo results are presented which indicate significant gains in terms of higher angular resolution of diffusion orientation distribution functions, better separation of crossing fibers, and improved reconstruction SNR over the same HARDI method, spherical harmonic q-ball imaging, without spatial regularization. Preliminary data also indicate that the proposed method might be better at maintaining accurate ODFs for smaller numbers of diffusion-weighted acquisition directions (hence faster scans) compared to conventional methods. Possible impacts of this work include improved evaluation of white matter microstructural integrity in regions of crossing fibers and higher spatial and angular resolution for more accurate tractography. (C) 2010 Elsevie

关键词： Adult Algorithms Bayes Theorem Brain/anatomy & histology Brain Mapping/methods Brain Mapping/methods computer Simulation Humans image processing, computer-assisted/methods Least-Squares Analysis Magnetic Resonance Imaging/methods Male Nerve Fibers/ultrastructure Normal Distribution Sensitivity and Specificity

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Reproducibility of thalamic segmentation based on probabilistic tractography

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NEUROimage 2010年第1期52卷 69-85页

作者： Traynor, Catherine Heckemann, Rolf A. Hammers, Alexander O'Muircheartaigh, Jonathan Crum, William R. Barker, Gareth J. Richardson, Mark P. Kings Coll London Inst Psychiat Dept Clin Neurosci London England Kings Coll London Inst Psychiat Dept Neuroimaging London England Univ London Imperial Coll Sci Technol & Med MRC Clin Sci Ctr Fac Med London SW7 2AZ England Neurodis Fdn Lyon France

Reliable identification of thalamic nuclei is required to improve targeting of electrodes used in Deep Brain Stimulation (DBS), and for exploring the role of thalamus in health and disease A previously described method using probabilistic tractography to segment the thalamus based on connections to cortical target regions was implemented Both within- and between-subject reproducibility were quantitatively assessed by the overlap of the resulting segmentations, the effect of two different numbers of target regions (6 and 31) on reproducibility of the segmentation results was also investigated Very high reproducibility was observed when a single dataset was processed multiple times using different starting conditions Thalamic segmentation was also very reproducible when multiple datasets from the same subject were processed using six cortical target regions Within-subject reproducibility was reduced when the number of target regions was increased, particularly in medial and posterior regions of the thalamus A large degree of overlap in segmentation results from different subjects was obtained, particularly in thalamic regions classified as connecting to frontal, parietal, temporal and pre-central cortical target regions (C) 2010 Elsevier Inc All rights reserved

关键词： Adult Algorithms Cerebral Cortex/anatomy & histology Databases as Topic Female Functional Laterality Fuzzy Logic Humans image processing, computer-assisted/methods Male Middle Aged Neural Pathways/anatomy & histology Organ Size Probability Reproducibility of Results Software Thalamus/anatomy & histology Young Adult

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A robust method for extraction and automatic segmentation of brain images

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NEUROimage 2002年第3期17卷 1087-1100页

作者： Kovacevic, N Lobaugh, NJ Bronskill, MJ Levine, B Feinstein, A Black, SE Sunnybrook & Womens Coll Hlth Sci Ctr Toronto ON Canada Univ Toronto Toronto ON Canada Rotman Res Inst Baycrest Ctr Geriatr Care Toronto ON Canada

A new protocol is introduced for brain extraction and automatic tissue segmentation of MR images. For the brain extraction algorithm, proton density and T2-weighted images are used to generate a brain mask encompassing the full intracranial cavity. Segmentation of brain tissues into gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) is accomplished on a T1-weighted image after applying the brain mask. The fully automatic segmentation algorithm is histogram-based and uses the Expectation Maximization algorithm to model a four-Gaussian mixture for both global and local histograms. The means of the local Gaussians for GM, WM, and CSF are used to set local thresholds for tissue classification. Reproducibility of the extraction procedure was excellent, with average variation in intracranial. capacity (TIC) of 0.13 and 0.66% TIC in 12 healthy normal and 33 Alzheimer brains, respectively. Repeatability of the segmentation algorithm, tested on healthy normal images, indicated scan-rescan differences in global tissue volumes of less than 0.30% TIC. Reproducibility at the regional level was established by comparing segmentation results within the 12 major Talairach subdivisions. Accuracy of the algorithm was tested on a digital brain phantom, and errors were less than 1% of the phantom volume. Maximal Type I and Type II classification errors were low, ranging between 2.2 and 4.3% of phantom volume. The algorithm was also insensitive to variation in parameter initialization values. The protocol is robust, fast, and its success in segmenting normal as well as diseased brains makes it an attractive clinical application. (C) 2002 Elsevier Science (USA).

关键词： Adult Aged Algorithms Alzheimer Disease/diagnosis Brain/pathology Humans image processing, computer-assisted/methods Magnetic Resonance Imaging/methods Normal Distribution Phantoms, Imaging Reference Values

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