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Magnetic resonance imaging (MRI) is the standard modality to understand human brain structure and function in vivo (antemortem). Decades of research in human neuroimaging has led to the widespread development of methods and tools to provide…

We develop a flexible framework for modeling high-dimensional imaging data observed longitudinally. The approach decomposes the observed variability of repeatedly measured high-dimensional observations into three additive components: a…

Purpose: Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster, et al. showed that complex graph measures of the connectome,…

Brain functional connectivity (FC) extracted from resting-state fMRI (RS-fMRI) has become a popular approach for disease diagnosis, where discriminating subjects with mild cognitive impairment (MCI) from normal controls (NC) is still one of…

Computer Vision and Pattern Recognition · Computer Science 2018-08-31 Weizheng Yan , Han Zhang , Jing Sui , Dinggang Shen

The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool…

The specificty and sensitivity of resting state functional MRI (rs-fMRI) measurements depend on pre-processing choices, such as the parcellation scheme used to define regions of interest (ROIs). In this study, we critically evaluate the…

Computer Vision and Pattern Recognition · Computer Science 2019-06-06 Meenakshi Khosla , Keith Jamison , Amy Kuceyeski , Mert R. Sabuncu

Our understanding of the human connectome is fundamentally limited by the resolution of diffusion MR images. Reconstructing a connectome's constituent neural pathways with tractography requires following a continuous field of fiber…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Tyler Spears , P. Thomas Fletcher

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, which could introduce…

Image and Video Processing · Electrical Eng. & Systems 2023-04-04 Zhangxing Bian , Muhan Shao , Aaron Carass , Jerry L. Prince

The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI) is the unique technique to obtain information about the…

Machine Learning · Computer Science 2012-07-04 Romain Giot , Christophe Charrier , Maxime Descoteaux

We propose an integrated deep-generative framework, that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imaging (DTI) tractography to extract predictive biomarkers of a…

The shape of the brain's white matter connections is relatively unexplored in diffusion MRI tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if the variability in…

Diffusion MRI (dMRI) streamline tractography, the gold standard for in vivo estimation of brain white matter (WM) pathways, has long been considered indicative of macroscopic relationships with WM microstructure. However, recent advances in…

Image and Video Processing · Electrical Eng. & Systems 2024-03-29 Tian Yu , Yunhe Li , Michael E. Kim , Chenyu Gao , Qi Yang , Leon Y. Cai , Susane M. Resnick , Lori L. Beason-Held , Daniel C. Moyer , Kurt G. Schilling , Bennett A. Landman

Understanding the morphological structure of medical images and precisely segmenting the region of interest or abnormality is an important task that can assist in diagnosis. However, the unique properties of medical imaging make clear…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Sungmin Kang , Jaeha Song , Jihie Kim

In increasingly many settings, data sets consist of multiple samples from a population of networks, with vertices aligned across these networks. For example, brain connectivity networks in neuroscience consist of measures of interaction…

Statistics Theory · Mathematics 2021-05-11 Keith Levin , Asad Lodhia , Elizaveta Levina

Emerging brain network studies suggest that interactions between various distributed neuronal populations may be characterized by an organized complex topological structure. Many brain diseases are associated with altered topological…

Neurons and Cognition · Quantitative Biology 2016-03-24 Shuo Chen , F. DuBois Bowman , Yishi Xing

Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has attracted the interest of the research community for a long time because morphological changes in these structures are related to different neurodegenerative…

Computer Vision and Pattern Recognition · Computer Science 2018-11-15 Kaisar Kushibar , Sergi Valverde , Sandra Gonzalez-Villa , Jose Bernal , Mariano Cabezas , Arnau Oliver , Xavier Llado

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more detail, it is highly important that the WM tracts can be accurately and reproducibly…

Image and Video Processing · Electrical Eng. & Systems 2020-05-27 Bo Li , Marius de Groot , Rebecca M. E. Steketee , Rozanna Meijboom , Marion Smits , Meike W. Vernooij , M. Arfan Ikram , Jiren Liu , Wiro J. Niessen , Esther E. Bron

Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft tissue contrast and lack of ionizing radiation. However, quantification of body composition requires an…

Computer Vision and Pattern Recognition · Computer Science 2018-10-16 Ismail Irmakci , Sarfaraz Hussein , Aydogan Savran , Rita R. Kalyani , David Reiter , Chee W. Chia , Kenneth W. Fishbein , Richard G. Spencer , Luigi Ferrucci , Ulas Bagci

We present a method to estimate a multivariate Gaussian distribution of diffusion tensor features in a set of brain regions based on a small sample of healthy individuals, and use this distribution to identify imaging abnormalities in…

Applications · Statistics 2017-04-24 Matineh Shaker , Deniz Erdogmus , Jennifer Dy , Sylvain Bouix

Brain atlases are a ubiquitous tool used for analyzing and interpreting brain imaging datasets. Traditionally, brain atlases divided the brain into regions separated by anatomical landmarks. In the last decade, several attempts have been…

Quantitative Methods · Quantitative Biology 2018-02-08 Pantea Moghimi , Kelvin O. Lim , Theoden I. Netoff