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Whole brain neuroanatomy using tera-voxel light-microscopic data sets is of much current interest. A fundamental problem in this field is the mapping of individual brain data sets to a reference space. Previous work has not rigorously…

Neurons and Cognition · Quantitative Biology 2019-04-18 Brian C. Lee , Meng Kuan Lin , Yan Fu , Junichi Hata , Michael I. Miller , Partha P. Mitra

Ultrasound (US) can be used to assess brain development in newborns, as MRI is challenging due to immobilization issues, and may require sedation. Dilatation of the lateral ventricles in the brain is a risk factor for poorer…

Computer Vision and Pattern Recognition · Computer Science 2018-06-07 Marc-Antoine Boucher , Sarah Lippe , Amelie Damphousse , Ramy El-Jalbout , Samuel Kadoury

Mapping white matter tracts is an essential step towards understanding brain function. Diffusion Magnetic Resonance Imaging (dMRI) is the only noninvasive technique which can detect in vivo anisotropies in the 3-dimensional diffusion of…

Computation · Statistics 2014-03-21 Dario Gasbarra , Jia Liu , Juha Railavo

Functional magnetic resonance imaging (fMRI) is an emerging neuroimaging modality that is commonly modeled as networks of Regions of Interest (ROIs) and their connections, named functional connectivity, for understanding the brain functions…

Neurons and Cognition · Quantitative Biology 2024-10-01 Haokai Zhao , Haowei Lou , Lina Yao , Yu Zhang

Diffusion-weighted magnetic resonance imaging (dMRI) allows non-invasive investigation of whole-brain connectivity, which can potentially help to reveal the brain's global network architecture and abnormalities involved in neurological and…

Dementia disorders are increasingly becoming sources of a broad range of problems, strongly interfering with normal daily tasks of a growing number of individuals. Such neurodegenerative diseases are often accompanied with progressive brain…

Deep learning models for MRI classification face two recurring problems: they are typically limited by low sample size, and are abstracted by their own complexity (the "black box problem"). In this paper, we train a convolutional neural…

Quantitative Methods · Quantitative Biology 2020-05-28 Matthew Leming , Juan Manuel Górriz , John Suckling

Purpose: Proton vertebral body sparing craniospinal irradiation (VBS CSI) treats the thecal sac while avoiding the anterior vertebral bodies in effort to reduce myelosuppression and growth inhibition. However, robust treatment planning…

Background: A noninvasive and sensitive imaging tool is needed to assess the fast-evolving baby brain. However, using MRI to study non-sedated babies faces roadblocks, including high scan failure rates due to subjects motion and the lack of…

The human brain undergoes dynamic, potentially pathology-driven, structural changes throughout a lifespan. Longitudinal Magnetic Resonance Imaging (MRI) and other neuroimaging data are valuable for characterizing trajectories of change…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Agampreet Aulakh , Nils D. Forkert , Matthias Wilms

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis…

Computer Vision and Pattern Recognition · Computer Science 2024-03-06 Camilo Calixto , Camilo Jaimes , Matheus D. Soldatelli , Simon K. Warfield , Ali Gholipour , Davood Karimi

Brain tumors are abnormal cell growths in the central nervous system (CNS), and their timely detection is critical for improving patient outcomes. This paper proposes an automatic and efficient deep-learning framework for brain tumor…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Ahta-Shamul Hoque Emran , Hafija Akter , Abdullah Al Shiam , Abu Saleh Musa Miah , Anichur Rahman , Fahmid Al Farid , Hezerul Abdul Karim

Fetal brain imaging is a cornerstone of prenatal screening and early diagnosis of congenital anomalies. Knowledge of fetal gestational age is the key to the accurate assessment of brain development. This study develops an attention-based…

Computer Vision and Pattern Recognition · Computer Science 2018-12-19 Liyue Shen , Katie Shpanskaya , Edward Lee , Emily McKenna , Maryam Maleki , Quin Lu , Safwan Halabi , John Pauly , Kristen Yeom

Purpose: Microscopic fractional anisotropy ({\mu}FA) can disentangle microstructural information from orientation dispersion. While double diffusion encoding (DDE) MRI methods are widely used to extract accurate {\mu}FA, it has only…

Medical Physics · Physics 2019-03-21 Rafael Neto Henriques , Sune N Jespersen , Noam Shemesh

We present long-term (~10^4 M) axisymmetric simulations of differentially rotating, magnetized neutron stars in the slow-rotation, weak magnetic field limit using a perturbative metric evolution technique. Although this approach yields…

Astrophysics · Physics 2009-11-11 Zachariah B. Etienne , Yuk Tung Liu , Stuart L. Shapiro

Quantifying muscle tissue properties is crucial for understanding pathophysiological changes occurring in skeletal muscle (SM). In particular, T2 relaxation and diffusion MRI (dMRI) are promising techniques. However, typical methods measure…

Brain aging is a widely studied longitudinal process throughout which the brain undergoes considerable morphological changes and various machine learning approaches have been proposed to analyze it. Within this context, brain age prediction…

Computer Vision and Pattern Recognition · Computer Science 2020-11-30 Matthias Wilms , Jordan J. Bannister , Pauline Mouches , M. Ethan MacDonald , Deepthi Rajashekar , Sönke Langner , Nils D. Forkert

The human brain can be conceptualized as a dynamical system. Utilizing resting state fMRI time series imaging, we can study the underlying dynamics at ear-marked Regions of Interest (ROIs) to understand structure or lack thereof. This…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Ninad Aithal , Chakka Sai Pradeep , Neelam Sinha

Alzheimer's disease (AD) is a progressive neurological disorder, meaning that the symptoms develop gradually throughout the years. It is also the main cause of dementia, which affects memory, thinking skills, and mental abilities. Nowadays,…

Computation and Language · Computer Science 2022-11-09 Loukas Ilias , Dimitris Askounis , John Psarras

Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) marks a critical transition between aging and dementia. Neuroimaging modalities, such as structural MRI, provide biomarkers of this…

Machine Learning · Computer Science 2026-03-02 Vrushank Ahire , Yogesh Kumar , Anouck Girard , M. A. Ganaie