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Diffusion Tensor Imaging (DTI) provides the possibility of estimating the location and course of eloquent structures in the human brain. Knowledge about this is of high importance for preoperative planning of neurosurgical interventions and…

Computer Vision and Pattern Recognition · Computer Science 2011-03-11 Miriam H. A. Bauer , Jan Egger , Daniela Kuhnt , Sebastiano Barbieri , Jan Klein , Horst K. Hahn , Bernd Freisleben , Christopher Nimsky

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. One of the most common computations in dMRI involves cross-subject tract-specific analysis, whereby dMRI-derived biomarkers are compared…

Image and Video Processing · Electrical Eng. & Systems 2023-07-12 Davood Karimi , Hamza Kebiri , Ali Gholipour

Dynamic functional connectivity (dFC) using resting-state functional magnetic resonance imaging (rs-fMRI) is an advanced technique for capturing the dynamic changes of neural activities, and can be very useful in the studies of brain…

Image and Video Processing · Electrical Eng. & Systems 2025-01-29 Jing Zhang , Yanjun Lyu , Xiaowei Yu , Lu Zhang , Chao Cao , Tong Chen , Minheng Chen , Yan Zhuang , Tianming Liu , Dajiang Zhu

Diffusion tensor imaging (DTI) holds significant importance in clinical diagnosis and neuroscience research. However, conventional model-based fitting methods often suffer from sensitivity to noise, leading to decreased accuracy in…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Jialong Li , Zhicheng Zhang , Yunwei Chen , Qiqi Lu , Ye Wu , Xiaoming Liu , QianJin Feng , Yanqiu Feng , Xinyuan Zhang

Diffusion Tensor Imaging (DTI) allows estimating the position, orientation and dimension of bundles of nerve pathways. This non-invasive imaging technique takes advantage of the diffusion of water molecules and determines the diffusion…

Computer Vision and Pattern Recognition · Computer Science 2011-03-09 Miriam H. A. Bauer , Jan Egger , Daniela Kuhnt , Sebastiano Barbieri , Jan Klein , Horst K. Hahn , Bernd Freisleben , Christopher Nimsky

Generating realistic MRIs to accurately predict future changes in the structure of brain is an invaluable tool for clinicians in assessing clinical outcomes and analysing the disease progression at the patient level. However, current…

Computer Vision and Pattern Recognition · Computer Science 2025-09-04 Mattia Litrico , Francesco Guarnera , Mario Valerio Giuffrida , Daniele Ravì , Sebastiano Battiato

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…

Brain age prediction using neuroimaging data has shown great potential as an indicator of overall brain health and successful aging, as well as a disease biomarker. Deep learning models have been established as reliable and efficient brain…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Bruno Machado Pacheco , Victor Hugo Rocha de Oliveira , Augusto Braga Fernandes Antunes , Saulo Domingos de Souza Pedro , Danilo Silva

The deviation between chronological age and biological age is a well-recognized biomarker associated with cognitive decline and neurodegeneration. Age-related and pathology-driven changes to brain structure are captured by various…

Machine Learning · Computer Science 2022-11-01 Saurabh Sihag , Gonzalo Mateos , Corey McMillan , Alejandro Ribeiro

Tractography is typically performed for each subject using the diffusion tensor imaging (DTI) data in its native subject space rather than in some space common to the entire study cohort. Despite performing tractography on a population…

Age prediction using brain imaging, such as MRIs, has achieved promising results, with several studies identifying the model's residual as a potential biomarker for chronic disease states. In this study, we developed a brain age predictive…

Machine Learning · Computer Science 2025-04-22 Shahrzad Jamshidi , Arthur Bousquet , Sugata Banerji , Mark F. Conneely , Bita Aslrousta

Demographic attributes such as age, sex, and race can be predicted from medical images, raising concerns about bias in clinical AI systems. In brain MRI, this signal may arise from anatomical variation, acquisition-dependent contrast…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Mehmet Yigit Avci , Akshit Achara , Andrew King , Jorge Cardoso

Human face aging is irreversible process causing changes in human face characteristics such us hair whitening, muscles drop and wrinkles. Due to the importance of human face aging in biometrics systems, age estimation became an attractive…

Computer Vision and Pattern Recognition · Computer Science 2016-01-11 Salah Eddine Bekhouche , Abdelkrim Ouafi , Abdelmalik Taleb-Ahmed , Abdenour Hadid , Azeddine Benlamoudi

Bone age is an important measure for assessing the skeletal and biological maturity of children. Delayed or increased bone age is a serious concern for pediatricians, and needs to be accurately assessed in a bid to determine whether bone…

Computer Vision and Pattern Recognition · Computer Science 2021-04-19 Ibrahim Salim , A. Ben Hamza

Background: The relative contribution of different aging-associated processes to the age phenotype may differ among individuals, creating variability in aging manifestations among age-peers. Capturing this variability can significantly…

Populations and Evolution · Quantitative Biology 2007-05-23 A. Kulminski , A. Yashin , S. Ukraintseva , I. Akushevich , K. Arbeev , K. Land , K. Manton

Multivariate regression models for age estimation are a powerful tool for assessing abnormal brain morphology associated to neuropathology. Age prediction models are built on cohorts of healthy subjects and are built to reflect normal aging…

Computer Vision and Pattern Recognition · Computer Science 2018-04-05 Benjamin Gutierrez Becker , Tassilo Klein , Christian Wachinger

Purpose: To propose a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography. Methods: We propose SuperDTI to learn the nonlinear relationship between diffusion-weighted images…

Image and Video Processing · Electrical Eng. & Systems 2021-07-27 Hongyu Li , Zifei Liang , Chaoyi Zhang , Ruiying Liu , Jing Li , Weihong Zhang , Dong Liang , Bowen Shen , Xiaoliang Zhang , Yulin Ge , Jiangyang Zhang , Leslie Ying

Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional…

Neurons and Cognition · Quantitative Biology 2025-02-25 Bishal Thapaliya , Robyn Miller , Jiayu Chen , Yu-Ping Wang , Esra Akbas , Ram Sapkota , Bhaskar Ray , Pranav Suresh , Santosh Ghimire , Vince Calhoun , Jingyu Liu

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

Age is one of the major known risk factors for Alzheimer's Disease (AD). Detecting AD early is crucial for effective treatment and preventing irreversible brain damage. Brain age, a measure derived from brain imaging reflecting structural…

Image and Video Processing · Electrical Eng. & Systems 2024-05-07 Jay Shah , Md Mahfuzur Rahman Siddiquee , Yi Su , Teresa Wu , Baoxin Li