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Longitudinal multi-scale mapping of infant cortical folding using spherical wavelets.
This study provides valuable insights into the longitudinal changes of infant cortical folding. PMID: 29098066 [PubMed] (Source: Proceedings - International Symposium on Biomedical Imaging)
Source: Proceedings - International Symposium on Biomedical Imaging - November 4, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Mahalanobis distance for class averaging of cryo-em images.
MAHALANOBIS DISTANCE FOR CLASS AVERAGING OF CRYO-EM IMAGES. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:654-658 Authors: Bhamre T, Zhao Z, Singer A Abstract Single particle reconstruction (SPR) from cryo-electron microscopy (EM) is a technique in which the 3D structure of a molecule needs to be determined from its contrast transfer function (CTF) affected, noisy 2D projection images taken at unknown viewing directions. One of the main challenges in cryo-EM is the typically low signal to noise ratio (SNR) of the acquired images. 2D classification of images, followed by class averaging, improves the...
Source: Proceedings - International Symposium on Biomedical Imaging - October 31, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Segmentation of organs at risk in thoracic ct images using a sharpmask architecture and conditional random fields.
SEGMENTATION OF ORGANS AT RISK IN THORACIC CT IMAGES USING A SHARPMASK ARCHITECTURE AND CONDITIONAL RANDOM FIELDS. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:1003-1006 Authors: Trullo R, Petitjean C, Ruan S, Dubray B, Nie D, Shen D Abstract Cancer is one of the leading causes of death worldwide. Radiotherapy is a standard treatment for this condition and the first step of the radiotherapy process is to identify the target volumes to be targeted and the healthy organs at risk (OAR) to be protected. Unlike previous methods for automatic segmentation of OAR that typically use local information and i...
Source: Proceedings - International Symposium on Biomedical Imaging - October 25, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Generative method to discover emphysema subtypes with unsupervised learning using lung macroscopic patterns (lmps): the mesa copd study.
GENERATIVE METHOD TO DISCOVER EMPHYSEMA SUBTYPES WITH UNSUPERVISED LEARNING USING LUNG MACROSCOPIC PATTERNS (LMPS): THE MESA COPD STUDY. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:375-378 Authors: Song J, Yang J, Smith B, Balte P, Hoffman EA, Barr RG, Laine AF, Angelini ED Abstract Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes: centrilobular emphysema (CLE), panlobular emphysema (PLE) and paraseptal emphysema (PSE). Automated classification methods based on supervised learning are generally base...
Source: Proceedings - International Symposium on Biomedical Imaging - October 11, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Optimal signal recovery from interleaved fmri data.
In this study, we examine the most popular methods of STC, and propose a new optimal method based on the fundamental properties of sampling theory. We evaluate this method using 20 simulated fMRI data and demonstrate the utility of STC in general as well as the superiority of the proposed method in comparison to existing ones. PMID: 28966719 [PubMed] (Source: Proceedings - International Symposium on Biomedical Imaging)
Source: Proceedings - International Symposium on Biomedical Imaging - October 4, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Empowering cortical thickness measures in clinical diagnosis of alzheimer's disease with spherical sparse coding.
EMPOWERING CORTICAL THICKNESS MEASURES IN CLINICAL DIAGNOSIS OF ALZHEIMER'S DISEASE WITH SPHERICAL SPARSE CODING. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:446-450 Authors: Zhang J, Fan Y, Li Q, Thompson PM, Ye J, Wang Y Abstract Cortical thickness estimation performed in vivo via magnetic resonance imaging (MRI) is an important technique for the diagnosis and understanding of the progression of Alzheimer's disease (AD). Directly using raw cortical thickness measures as features with Support Vector Machine (SVM) for clinical group classification only yields modest results since brain areas are n...
Source: Proceedings - International Symposium on Biomedical Imaging - October 1, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Enhancing Diffusion MRI Measures By Integrating Grey and White Matter Morphometry With Hyperbolic Wasserstein Distance.
Authors: Zhang W, Shi J, Yu J, Zhan L, Thompson PM, Wang Y Abstract In order to improve the preclinical diagnose of Alzheimer's disease (AD), there is a great deal of interest in analyzing the AD related brain structural changes with magnetic resonance image (MRI) analyses. As the major features, variation of the structural connectivity and the cortical surface morphometry provide different views of structural changes to determine whether AD is present on presymptomatic patients. However, the large scale tensor-valued information and relatively low imaging resolution in diffusion MRI (dMRI) have created huge challe...
Source: Proceedings - International Symposium on Biomedical Imaging - September 24, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Ct and mri fusion for postimplant prostate brachytherapy evaluation.
CT AND MRI FUSION FOR POSTIMPLANT PROSTATE BRACHYTHERAPY EVALUATION. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:625-628 Authors: Dehghan E, Le Y, Lee J, Song DY, Fichtinger G, Prince JL Abstract Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a nee...
Source: Proceedings - International Symposium on Biomedical Imaging - September 14, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Architectural patterns for differential diagnosis of proliferative breast lesions from histopathological images.
ARCHITECTURAL PATTERNS FOR DIFFERENTIAL DIAGNOSIS OF PROLIFERATIVE BREAST LESIONS FROM HISTOPATHOLOGICAL IMAGES. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:152-155 Authors: Nguyen L, Tosun AB, Fine JL, Taylor DL, Chennubhotla SC Abstract The differential diagnosis of proliferative breast lesions, benign usual ductal hyperplasia (UDH) versus malignant ductal carcinoma in situ (DCIS) is challenging. This involves a pathologist examining histopathologic sections of a biopsy using a light microscope, evaluating tissue structures for their architecture or size, and assessing individual cell nuclei for...
Source: Proceedings - International Symposium on Biomedical Imaging - September 13, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Dynamic registration for gigapixel serial whole slide images.
DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:424-428 Authors: Rossetti BJ, Wang F, Zhang P, Teodoro G, Brat DJ, Kong J Abstract High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the direct application of conventional registration techniques. In this paper, we develop a three-stage registration with multi-resolution mapping and propag...
Source: Proceedings - International Symposium on Biomedical Imaging - August 15, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Automated level set segmentation of histopathologic cells with sparse shape prior support and dynamic occlusion constraint.
AUTOMATED LEVEL SET SEGMENTATION OF HISTOPATHOLOGIC CELLS WITH SPARSE SHAPE PRIOR SUPPORT AND DYNAMIC OCCLUSION CONSTRAINT. Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:718-722 Authors: Zhang P, Wang F, Teodoro G, Liang Y, Brat D, Kong J Abstract In this paper, we propose a novel segmentation method for cells in histopathologic images based on a sparse shape prior guided variational level set framework. We automate the cell contour initialization by detecting seeds and deform contours by minimizing a new energy functional that incorporates a shape term involving sparse shape priors, an adaptive con...
Source: Proceedings - International Symposium on Biomedical Imaging - August 8, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Lars network filtration in the study of eeg brain connectivity.
LARS NETWORK FILTRATION IN THE STUDY OF EEG BRAIN CONNECTIVITY. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:30-33 Authors: Wang Y, Chung MK, Bachhuber DRW, Schaefer SM, van Reekum CM, Davidson RJ Abstract In a brain network, weak and non-significant edge weights between nodes signal spurious connections and are often discarded by thresholding the weights. Traditional practice of thresholding edge weights at an arbitrary value can be problematic. Network filtration provides an alternative by summarizing the changes in the network topology with respect to a broad range of thresholds. A well establis...
Source: Proceedings - International Symposium on Biomedical Imaging - July 29, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Topological epilepsy seizure detection in electroencephalographic signals.
TOPOLOGICAL EPILEPSY SEIZURE DETECTION IN ELECTROENCEPHALOGRAPHIC SIGNALS. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:351-354 Authors: Wang Y, Ombao H, Chung MK Abstract We propose a seizure detection method for electroencephalographic (EEG) epilepsy data based on a novel multi-scale topological technique called persistent homology (PH). Among several PH descriptors, persistence landscape (PL) possesses many desirable properties for rigorous statistical inference. By building PLs on EEG epilepsy signals smoothed by a weighted Fourier series (WFS) expansion, we compared the before and during phase...
Source: Proceedings - International Symposium on Biomedical Imaging - July 29, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Non-rigid registration guided by landmarks and learning.
NON-RIGID REGISTRATION GUIDED BY LANDMARKS AND LEARNING. Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:704-707 Authors: Eckl J, Daum V, Hornegger J, Pohl KM Abstract Registration methods frequently rely on prior information in order to generate anatomical meaningful transformations between medical scans. In this paper, we propose a novel intensity based non-rigid registration framework, which is guided by landmarks and a regularizer based on Principle Component Analysis (PCA). Unlike existing methods in this domain, the computational complexity of our approach reduces with the number of landmarks. F...
Source: Proceedings - International Symposium on Biomedical Imaging - June 22, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Nonrigid volume registration using second-order mrf model.
NONRIGID VOLUME REGISTRATION USING SECOND-ORDER MRF MODEL. Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:708-711 Authors: Kwon D, Yun ID, Pohl KM, Davatzikos C, Lee SU Abstract In this paper, we introduce a nonrigid registration method using a Markov Random Field (MRF) energy model with second-order smoothness priors. The registration determines an optimal labeling of the MRF energy model where the label corresponds to a 3D displacement vector. In the MRF energy model, spatial relationships are constructed between nodes using second-order smoothness priors. This model improves limitations of first-o...
Source: Proceedings - International Symposium on Biomedical Imaging - June 22, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Disease classification and prediction via semi-supervised dimensionality reduction.
We present a new semi-supervised algorithm for dimensionality reduction which exploits information of unlabeled data in order to improve the accuracy of image-based disease classification based on medical images. We perform dimensionality reduction by adopting the formalism of constrained matrix decomposition of [1] to semi-supervised learning. In addition, we add a new regularization term to the objective function to better captur the affinity between labeled and unlabeled data. We apply our method to a data set consisting of medical scans of subjects classified as Normal Control (CN) and Alzheimer (AD). The unlabeled dat...
Source: Proceedings - International Symposium on Biomedical Imaging - June 15, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Automatic Segmentation of Breast Carcinomas from DCE-MRI using a Statistical Learning Algorithm.
Authors: Jayender J, Vosburgh KG, Gombos E, Ashraf A, Kontos D, Gavenonis SC, Jolesz FA, Pohl K Abstract Segmenting regions of high angiogenic activity corresponding to malignant tumors from DCE-MRI is a time-consuming task requiring processing of data in 4 dimensions. Quantitative analyses developed thus far are highly sensitive to external factors and are valid only under certain operating assumptions, which need not be valid for breast carcinomas. In this paper, we have developed a novel Statistical Learning Algorithm for Tumor Segmentation (SLATS) for automatically segmenting cancer from a region selected by th...
Source: Proceedings - International Symposium on Biomedical Imaging - June 15, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Segmentation of myocardium using deformable regions and graph cuts.
SEGMENTATION OF MYOCARDIUM USING DEFORMABLE REGIONS AND GRAPH CUTS. Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:254-257 Authors: UzunbaĊŸ MG, Zhang S, Pohl KM, Metaxas D, Axel L Abstract Deformable models and graph cuts are two standard image segmentation techniques. Combining some of their benefits, we introduce a new segmentation system for (semi-) automatic delineation of epicardium and endocardium of Left Ventricle of the heart in Magnetic Resonance Images (MRI). Specifically, a temporal information among consecutive phases is exploited via a coupling between deformable models and graph cuts w...
Source: Proceedings - International Symposium on Biomedical Imaging - June 15, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Anatomical guided segmentation with non-stationary tissue class distributions in an expectation-maximization framework.
ANATOMICAL GUIDED SEGMENTATION WITH NON-STATIONARY TISSUE CLASS DISTRIBUTIONS IN AN EXPECTATION-MAXIMIZATION FRAMEWORK. Proc IEEE Int Symp Biomed Imaging. 2004 Apr;2004:81-84 Authors: Pohl KM, Bouix S, Kikinis R, Grimson WEL Abstract High quality segmentation of brain MR images is a challenging task. To deal with this problem many automatic segmentation methods rely on atlas information of anatomical structures. We further investigate this line of research by introducing hierarchical representations of anatomical structures in an Expectation-Maximization framework. This new approach enables us to divid...
Source: Proceedings - International Symposium on Biomedical Imaging - June 10, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Monitoring slowly evolving tumors.
MONITORING SLOWLY EVOLVING TUMORS. Proc IEEE Int Symp Biomed Imaging. 2008 May;2008:812-815 Authors: Konukoglu E, Wells WM, Novellas S, Ayache N, Kikinis R, Black PM, Pohl KM Abstract Change detection is a critical task in the diagnosis of many slowly evolving pathologies. This paper describes an approach that semi-automatically performs this task using longitudinal medical images. We are specifically interested in meningiomas, which experts often find difficult to monitor as the tumor evolution can be obscured by image artifacts. We test the method on synthetic data with known tumor growth as well as ...
Source: Proceedings - International Symposium on Biomedical Imaging - June 10, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Combining regional metrics for disease-related brain population analysis.
COMBINING REGIONAL METRICS FOR DISEASE-RELATED BRAIN POPULATION ANALYSIS. Proc IEEE Int Symp Biomed Imaging. 2012 May;2012:1515-1518 Authors: Ye DH, Hamm J, Pohl KM Abstract In this paper, we present a new metric combining regional measurements to improve image based population studies that use manifold learning techniques. These studies currently rely on a single score over the whole brain image domain. Thus, they require large amount of training data to uncover spatially complex variation in the whole brain impacted by diseases. We reduce the impact of this issue by first computing pairwise measureme...
Source: Proceedings - International Symposium on Biomedical Imaging - June 10, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Auto-encoding of discriminating morphometry from cardiac mri.
AUTO-ENCODING OF DISCRIMINATING MORPHOMETRY FROM CARDIAC MRI. Proc IEEE Int Symp Biomed Imaging. 2014 Apr-May;2014:217-221 Authors: Ye DH, Desjardins B, Ferrari V, Metaxas D, Pohl KM Abstract We propose a fully-automatic morphometric encoding targeted towards differentiating diseased from healthy cardiac MRI. Existing encodings rely on accurate segmentations of each scan. Segmentation generally includes labour-intensive editing and increases the risk associated with intra- and inter-rater variability. Our morphometric framework only requires the segmentation of a template scan. This template is non-rig...
Source: Proceedings - International Symposium on Biomedical Imaging - June 10, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Optimizing Stimulus Patterns for Dense Array tDCS With Fewer Sources Than Electrodes Using A branch and Bound Algorithm.
We present simulation results for both focal and spatially extended cortical ROIs. Our results suggest that only a few (2-3) independently controlled current sources can achieve comparable results to a full set (125 sources) to a tolerance of 5%. BB is computationally 3-5 orders of magnitude less demanding than exhaustive search. PMID: 28479959 [PubMed - in process] (Source: Proceedings - International Symposium on Biomedical Imaging)
Source: Proceedings - International Symposium on Biomedical Imaging - May 11, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Evaluation of Numerical Techniques for Solving the Current Injection Problem in Biological Tissues.
Authors: Hyde DE, Dannhauer M, Warfield SK, MacLeod R, Brooks DH Abstract Accurate computational modeling of electric fields in the human head has become important in clinical research to study or influence brain functionality. While existing numerical approaches have been evaluated against simple geometries with known closed form solutions, the relationship between these approaches in more complex geometries has not been studied. Here, we compare the three most commonly used approaches for bioelectric modeling: the finite element method (FEM), the finite difference method (FDM), and the boundary element method (BE...
Source: Proceedings - International Symposium on Biomedical Imaging - May 11, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Automatic muscle perimysium annotation using deep convolutional neural network.
AUTOMATIC MUSCLE PERIMYSIUM ANNOTATION USING DEEP CONVOLUTIONAL NEURAL NETWORK. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:205-208 Authors: Sapkota M, Xing F, Su H, Yang L Abstract Diseased skeletal muscle expresses mononuclear cell infiltration in the regions of perimysium. Accurate annotation or segmentation of perimysium can help biologists and clinicians to determine individualized patient treatment and allow for reasonable prognostication. However, manual perimysium annotation is time consuming and prone to inter-observer variations. Meanwhile, the presence of ambiguous patterns in muscle im...
Source: Proceedings - International Symposium on Biomedical Imaging - April 27, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Automated cell counting and cluster segmentation using concavity detection and ellipse fitting techniques.
AUTOMATED CELL COUNTING AND CLUSTER SEGMENTATION USING CONCAVITY DETECTION AND ELLIPSE FITTING TECHNIQUES. Proc IEEE Int Symp Biomed Imaging. 2009 Jun-Jul;2009:795-798 Authors: Kothari S, Chaudry Q, Wang MD Abstract This paper presents a novel, fast and semi-automatic method for accurate cell cluster segmentation and cell counting of digital tissue image samples. In pathological conditions, complex cell clusters are a prominent feature in tissue samples. Segmentation of these clusters is a major challenge for development of an accurate cell counting methodology. We address the issue of cluster segmenta...
Source: Proceedings - International Symposium on Biomedical Imaging - April 13, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Development of a novel 2D color map for interactive segmentation of histological images.
We present a color segmentation approach based on a two-dimensional color map derived from the input image. Pathologists stain tissue biopsies with various colored dyes to see the expression of biomarkers. In these images, because of color variation due to inconsistencies in experimental procedures and lighting conditions, the segmentation used to analyze biological features is usually ad-hoc. Many algorithms like K-means use a single metric to segment the image into different color classes and rarely provide users with powerful color control. Our 2D color map interactive segmentation technique based on human color percept...
Source: Proceedings - International Symposium on Biomedical Imaging - April 13, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Robust Cell Segmentation for Histological Images of Glioblastoma.
Authors: Kong J, Zhang P, Liang Y, Teodoro G, Brat DJ, Wang F Abstract Glioblastoma (GBM) is a malignant brain tumor with uniformly dismal prognosis. Quantitative analysis of GBM cells is an important avenue to extract latent histologic disease signatures to correlate with molecular underpinnings and clinical outcomes. As a prerequisite, a robust and accurate cell segmentation is required. In this paper, we present an automated cell segmentation method that can satisfactorily address segmentation of overlapped cells commonly seen in GBM histology specimens. This method first detects cells with seed connectivity, di...
Source: Proceedings - International Symposium on Biomedical Imaging - April 11, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Ventricular maps in 804 subjects correlate with cognitive decline, csf pathology, and imminent alzheimer's disease.
VENTRICULAR MAPS IN 804 SUBJECTS CORRELATE WITH COGNITIVE DECLINE, CSF PATHOLOGY, AND IMMINENT ALZHEIMER'S DISEASE. Proc IEEE Int Symp Biomed Imaging. 2010 Apr;2010:241-244 Authors: Chou YY, Leporé N, Madsen SK, Saharan P, Hua X, Jack CR, Shaw LM, Trojanowski JQ, Weiner MW, Toga AW, Thompson PM, Alzheimer’s Disease Neuroimaging Initiative (ADNI) Abstract There is an urgent need for neuroimaging biomarkers of Alzheimer's disease (AD) that correlate with cognitive decline, and with accepted measures of pathology detectable in cerebrospinal fluid (CSF). Ideal biomarkers should also be able to...
Source: Proceedings - International Symposium on Biomedical Imaging - March 24, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Nuclei segmentation via sparsity constrained convolutional regression.
NUCLEI SEGMENTATION VIA SPARSITY CONSTRAINED CONVOLUTIONAL REGRESSION. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1284-1287 Authors: Zhou Y, Chang H, Barner KE, Parvin B Abstract Automated profiling of nuclear architecture, in histology sections, can potentially help predict the clinical outcomes. However, the task is challenging as a result of nuclear pleomorphism and cellular states (e.g., cell fate, cell cycle), which are compounded by the batch effect (e.g., variations in fixation and staining). Present methods, for nuclear segmentation, are based on human-designed features that may not effec...
Source: Proceedings - International Symposium on Biomedical Imaging - January 22, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Bayesian Covariate Selection in Mixed-Effects Models For Longitudinal Shape Analysis.
Authors: Muralidharan P, Fishbaugh J, Kim EY, Johnson HJ, Paulsen JS, Gerig G, Fletcher PT Abstract The goal of longitudinal shape analysis is to understand how anatomical shape changes over time, in response to biological processes, including growth, aging, or disease. In many imaging studies, it is also critical to understand how these shape changes are affected by other factors, such as sex, disease diagnosis, IQ, etc. Current approaches to longitudinal shape analysis have focused on modeling age-related shape changes, but have not included the ability to handle covariates. In this paper, we present a novel Baye...
Source: Proceedings - International Symposium on Biomedical Imaging - January 18, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Optimal parameter map estimation for shape representation: a generative approach.
OPTIMAL PARAMETER MAP ESTIMATION FOR SHAPE REPRESENTATION: A GENERATIVE APPROACH. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:660-663 Authors: Elhabian SY, Agrawal P, Whitaker RT Abstract Probabilistic label maps are a useful tool for important medical image analysis tasks such as segmentation, shape analysis, and atlas building. Existing methods typically rely on blurred signed distance maps or smoothed label maps to model uncertainties and shape variabilities, which do not conform to any generative model or estimation process, and are therefore suboptimal. In this paper, we propose to learn prob...
Source: Proceedings - International Symposium on Biomedical Imaging - January 18, 2017 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Automated agatston score computation in a large dataset of non ecg-gated chest computed tomography.
AUTOMATED AGATSTON SCORE COMPUTATION IN A LARGE DATASET OF NON ECG-GATED CHEST COMPUTED TOMOGRAPHY. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:53-57 Authors: González G, Washko GR, Estépar RS Abstract The Agatston score, computed from ECG-gated computed tomography (CT), is a well established metric of coronary artery disease. It has been recently shown that the Agatston score computed from chest CT (non ECG-gated) studies is highly correlated with the Agatston score computed from cardiac CT scans. In this work we present an automated method to compute the Agatston score from chest C...
Source: Proceedings - International Symposium on Biomedical Imaging - December 17, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Derivation of a test statistic for emphysema quantification.
DERIVATION OF A TEST STATISTIC FOR EMPHYSEMA QUANTIFICATION. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:1269-1273 Authors: Vegas-Sanchez-Ferrero G, Washko G, Rahaghi FN, Ledesma-Carbayo MJ, Estépar RS Abstract Density masking is the de-facto quantitative imaging phenotype for emphysema that is widely used by the clinical community. Density masking defines the burden of emphysema by a fixed threshold, usually between -910 HU and -950 HU, that has been experimentally validated with histology. In this work, we formalized emphysema quantification by means of statistical inference. We show that...
Source: Proceedings - International Symposium on Biomedical Imaging - December 17, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Unsupervised shape prior modeling for cell segmentation in neuroendocrine tumor.
UNSUPERVISED SHAPE PRIOR MODELING FOR CELL SEGMENTATION IN NEUROENDOCRINE TUMOR. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:1443-1446 Authors: Xing F, Yang L Abstract Automated and accurate cell segmentation provides support for many quantitative analyses on digitized neuroendocrine tumor (NET) images. It is a challenging task due to complex variations of cell characteristics. In this paper, we incorporate unsupervised shape priors into an efficient repulsive deformable model for automated cell segmentation on NET images. Unlike other supervised learning based shape models, which usually require ...
Source: Proceedings - International Symposium on Biomedical Imaging - December 10, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Integrative bayesian analysis of neuroimaging-genetic data through hierarchical dimension reduction.
We present a framework for examining the extent to which genetic factors impact imaging phenotypes described by voxel-wise measurements organized into collections of functionally relevant regions of interest (ROIs) that span the entire brain. Statistically, the integration of neuroimaging and genetic data is challenging. Because genetic variants are expected to impact different regions of the brain, an appropriate method of inference must simultaneously account for spatial dependence and model uncertainty. Our proposed framework combines feature extraction using generalized principal component analysis to account for inher...
Source: Proceedings - International Symposium on Biomedical Imaging - December 7, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Simulating convection-enhanced delivery in the putamen using probabilistic tractography.
In this study we describe a modeling and analysis framework based upon probabilistic tractography. This framework was used to compare probabilistic tractography modeling and actual CED infusion measurements in the putamen of non-human primates, as this gray matter structure is proposed as a target for CED treatment of Parkinson's disease. PMID: 27795809 [PubMed - in process] (Source: Proceedings - International Symposium on Biomedical Imaging)
Source: Proceedings - International Symposium on Biomedical Imaging - November 3, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Intensity inhomogeneity correction of macular oct using n3 and retinal flatspace.
INTENSITY INHOMOGENEITY CORRECTION OF MACULAR OCT USING N3 AND RETINAL FLATSPACE. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:197-200 Authors: Lang A, Carass A, Jedynak BM, Solomon SD, Calabresi PA, Prince JL Abstract As optical coherence tomography (OCT) has increasingly become a standard modality for imaging the retina, automated algorithms for processing OCT data have become necessary to do large scale studies looking for changes in specific layers. To provide accurate results, many of these algorithms rely on the consistency of layer intensities within a scan. Unfortunately, OCT data often exh...
Source: Proceedings - International Symposium on Biomedical Imaging - October 4, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Fully convolutional networks for multi-modality isointense infant brain image segmentation.
FULLY CONVOLUTIONAL NETWORKS FOR MULTI-MODALITY ISOINTENSE INFANT BRAIN IMAGE SEGMENTATION. Proc IEEE Int Symp Biomed Imaging. 2016;2016:1342-1345 Authors: Nie D, Wang L, Gao Y, Shen D Abstract The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development. In the isointense phase (approximately 6-8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, resulting in extremely low tissue contrast and thus making the tissue segmentation very challenging. ...
Source: Proceedings - International Symposium on Biomedical Imaging - September 27, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Morphometric analysis of hippocampus and lateral ventricle reveals regional difference between cognitively stable and declining persons.
In this study, we employed a morphometric analysis in the hippocampus and lateral ventricle. A novel group-wise template-based segmentation algorithm was developed for ventricular segmentation. Further, surface multivariate tensor-based morphometry and radial distance on each surface point were computed. Using Hotellings T (2) test, we found significant morphometric differences in both hippocampus and lateral ventricle between stable and clinically declining subjects. The left hemisphere was more severely affected than the right during this early disease stage. Hippocampal and ventricular morphometry has significant potent...
Source: Proceedings - International Symposium on Biomedical Imaging - August 10, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Applying sparse coding to surface multivariate tensor-based morphometry to predict future cognitive decline.
APPLYING SPARSE CODING TO SURFACE MULTIVARIATE TENSOR-BASED MORPHOMETRY TO PREDICT FUTURE COGNITIVE DECLINE. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:646-650 Authors: Zhang J, Stonnington C, Li Q, Shi J, Bauer RJ, Gutman BA, Chen K, Reiman EM, Thompson PM, Ye J, Wang Y Abstract Alzheimer's disease (AD) is a progressive brain disease. Accurate diagnosis of AD and its prodromal stage, mild cognitive impairment, is crucial for clinical trial design. There is also growing interests in identifying brain imaging biomarkers that help evaluate AD risk presymptomatically. Here, we applied a recently dev...
Source: Proceedings - International Symposium on Biomedical Imaging - August 10, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Phenotypic characterization of breast invasive carcinoma via transferable tissue morphometric patterns learned from glioblastoma multiforme.
PHENOTYPIC CHARACTERIZATION OF BREAST INVASIVE CARCINOMA VIA TRANSFERABLE TISSUE MORPHOMETRIC PATTERNS LEARNED FROM GLIOBLASTOMA MULTIFORME. Proc IEEE Int Symp Biomed Imaging. 2016 Apr;2016:1025-1028 Authors: Han J, Fontenay GV, Wang Y, Mao JH, Chang H Abstract Quantitative analysis of whole slide images (WSIs) in a large cohort may provide predictive models of clinical outcome. However, the performance of the existing techniques is hindered as a result of large technical variations (e.g., fixation, staining) and biological heterogeneities (e.g., cell type, cell state) that are always present in a larg...
Source: Proceedings - International Symposium on Biomedical Imaging - July 9, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Multiscale tensor anisotropic filtering of fluorescence microscopy for denoising microvasculature.
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:540-543 Authors: Prasath VB, Pelapur R, Glinskii OV, Glinsky VV, Huxley VH, Palaniappan K Abstract Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy....
Source: Proceedings - International Symposium on Biomedical Imaging - January 16, 2016 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Orthogonal Matrix Retrieval In Cryo-Electron Microscopy.
Authors: Bhamre T, Zhang T, Singer A Abstract In single particle reconstruction (SPR) from cryo-electron microscopy (EM), the 3D structure of a molecule needs to be determined from its 2D projection images taken at unknown viewing directions. Zvi Kam showed already in 1980 that the autocorrelation function of the 3D molecule over the rotation group SO(3) can be estimated from 2D projection images whose viewing directions are uniformly distributed over the sphere. The autocorrelation function determines the expansion coefficients of the 3D molecule in spherical harmonics up to an orthogonal matrix of size (2l + 1) &...
Source: Proceedings - International Symposium on Biomedical Imaging - December 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Covariance estimation using conjugate gradient for 3d classification in cryo-em.
COVARIANCE ESTIMATION USING CONJUGATE GRADIENT FOR 3D CLASSIFICATION IN CRYO-EM. Proc IEEE Int Symp Biomed Imaging. 2015 Apr;2015:200-204 Authors: Andén J, Katsevich E, Singer A Abstract Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suit...
Source: Proceedings - International Symposium on Biomedical Imaging - December 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Correcting inhomogeneity-induced distortion in fmri using non-rigid registration.
We describe a constrained non-linear registration method for correcting fMRI distortion that uses T 1-weighted images and does not require field maps. We compared resting state results from uncorrected fMRI, fMRI data corrected with field maps, and fMRI data corrected with our proposed method in data from 20 subjects. The results show that the estimated field maps were similar to the acquired field maps and that the proposed method reduces the overall error in independent component location. PMID: 26617955 [PubMed - as supplied by publisher] (Source: Proceedings - International Symposium on Biomedical Imaging)
Source: Proceedings - International Symposium on Biomedical Imaging - December 4, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Discovery of genes that affect human brain connectivity: a genome-wide analysis of the connectome.
DISCOVERY OF GENES THAT AFFECT HUMAN BRAIN CONNECTIVITY: A GENOME-WIDE ANALYSIS OF THE CONNECTOME. Proc IEEE Int Symp Biomed Imaging. 2012;:542-545 Authors: Jahanshad N, Hibar DP, Ryles A, Toga AW, McMahon KL, de Zubicaray GI, Hansell NK, Montgomery GW, Martin NG, Wright MJ, Thompson PM Abstract Human brain connectivity is disrupted in a wide range of disorders - from Alzheimer's disease to autism - but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain ...
Source: Proceedings - International Symposium on Biomedical Imaging - November 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Vessel centerline tracking and boundary segmentation in coronary mra with minimal manual interaction.
VESSEL CENTERLINE TRACKING AND BOUNDARY SEGMENTATION IN CORONARY MRA WITH MINIMAL MANUAL INTERACTION. Proc IEEE Int Symp Biomed Imaging. 2012;:1417-1420 Authors: Soleimanifard S, Schär M, Hays AG, Weiss RG, Stuber M, Prince JL Abstract Magnetic resonance angiography (MRA) provides a noninvasive means to detect the presence, location and severity of atherosclerosis throughout the vascular system. In such studies, and especially those in the coronary arteries, the vessel luminal area is typically measured at multiple cross-sectional locations along the course of the artery. The advent of fast volume...
Source: Proceedings - International Symposium on Biomedical Imaging - November 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

Manifold learning for analysis of low-order nonlinear dynamics in high-dimensional electrocardiographic signals.
MANIFOLD LEARNING FOR ANALYSIS OF LOW-ORDER NONLINEAR DYNAMICS IN HIGH-DIMENSIONAL ELECTROCARDIOGRAPHIC SIGNALS. Proc IEEE Int Symp Biomed Imaging. 2012 Jul 12;2012:844-847 Authors: Erem B, Stovicek P, Brooks DH Abstract The dynamical structure of electrical recordings from the heart or torso surface is a valuable source of information about cardiac physiological behavior. In this paper, we use an existing data-driven technique for manifold identification to reveal electrophysiologically significant changes in the underlying dynamical structure of these signals. Our results suggest that this analysis t...
Source: Proceedings - International Symposium on Biomedical Imaging - November 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research

An over-complete dictionary based regularized reconstruction of a field of ensemble average propagators.
We present a dictionary learning framework for achieving a smooth EAP reconstruction across the field wherein, the dictionary atoms are learned from the data via an initial regression using adaptive spline kernels. The formulation involves a two stage optimization where the first stage involves optimizing for a sparse dictionary using a K-SVD based updating and the second stage involves a quadratic cost function optimization with a non-local means based regularization across the field. The novelty lies in a dictionary based reconstruction as well as an NLM-based regularization that helps preserving features in the reconstr...
Source: Proceedings - International Symposium on Biomedical Imaging - November 19, 2015 Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research