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Related papers: Diffusion MRI with Machine Learning

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Discovering a new field is not usually an easy process, especially when you choose magnetic resonance imaging (MRI). MRI is one of the few non-invasive medical procedures, if not the only one, that someone can receive in modern day…

Medical Physics · Physics 2019-08-20 Alexis Reymbaut , Maxime Descoteaux

Estimating intra- and extra-axonal microstructure parameters, such as volume fractions and diffusivities, has been one of the major efforts in brain microstructure imaging with MRI. The Standard Model (SM) of diffusion in white matter has…

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and…

Diffusion magnetic resonance imaging (dMRI) provides a unique tool for noninvasively probing the microstructure of the neuronal tissue. The NODDI model has been a popular approach to the estimation of tissue microstructure in many…

Computer Vision and Pattern Recognition · Computer Science 2017-04-06 Chuyang Ye

Segmentation of focal (localized) brain pathologies such as brain tumors and brain lesions caused by multiple sclerosis and ischemic strokes are necessary for medical diagnosis, surgical planning and disease development as well as other…

Computer Vision and Pattern Recognition · Computer Science 2017-01-25 Mohammad Havaei , Nicolas Guizard , Hugo Larochelle , Pierre-Marc Jodoin

Diffusion MRI (dMRI) is a valuable tool in the assessment of tissue microstructure. By fitting a model to the dMRI signal it is possible to derive various quantitative features. Several of the most popular dMRI signal models are expansions…

Alzheimer's disease (AD) is a progressive neurodegenerative disorder in which pathological changes begin many years before the onset of clinical symptoms, making early detection essential for timely intervention. T1-weighted (T1w) Magnetic…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Jason Qiu

The use of supervised deep learning techniques to detect pathologies in brain MRI scans can be challenging due to the diversity of brain anatomy and the need for annotated data sets. An alternative approach is to use unsupervised anomaly…

Image and Video Processing · Electrical Eng. & Systems 2023-03-08 Finn Behrendt , Debayan Bhattacharya , Julia Krüger , Roland Opfer , Alexander Schlaefer

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…

Most existing MRI reconstruction methods perform tar-geted reconstruction of the entire MR image without tak-ing specific tissue regions into consideration. This may fail to emphasize the reconstruction accuracy on im-portant tissues for…

Image and Video Processing · Electrical Eng. & Systems 2023-09-06 Yu Guan , Chuanming Yu , Shiyu Lu , Zhuoxu Cui , Dong Liang , Qiegen Liu

Recently, diffusion models (DM) have been applied in magnetic resonance imaging (MRI) super-resolution (SR) reconstruction, exhibiting impressive performance, especially with regard to detailed reconstruction. However, the current DM-based…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Guangyuan Li , Chen Rao , Juncheng Mo , Zhanjie Zhang , Wei Xing , Lei Zhao

Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific…

Quantitative Methods · Quantitative Biology 2019-06-21 Samuel St-Jean , Maxime Chamberland , Max A. Viergever , Alexander Leemans

Cortical thickness measurements from magnetic resonance imaging, an important biomarker in many neurodegenerative and neurological disorders, are derived by many tools from an initial voxel-wise tissue segmentation. White matter (WM)…

Image and Video Processing · Electrical Eng. & Systems 2025-03-27 Vinzenz Uhr , Ivan Diaz , Christian Rummel , Richard McKinley

Diffusion-weighted magnetic resonance imaging (DW-MRI) derived scalar maps are effective for assessing neurodegenerative diseases and microstructural properties of white matter in large number of brain conditions. However, DW-MRI inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Gabriel Girard , Manon Edde , Félix Dumais , Yoan David , Matthieu Dumont , Guillaume Theaud , Jean-Christophe Houde , Arnaud Boré , Maxime Descoteaux , Pierre-Marc Jodoin

Computational models of biophysical tissue properties have been widely used in diffusion MRI (dMRI) research to elucidate the link between microstructural properties and MR signal formation. For brain tissue, the research community has…

Medical Physics · Physics 2019-07-16 Santiago Coelho , Jose M. Pozo , Sune N. Jespersen , Alejandro F. Frangi

Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human heart. Current research in DT-CMR aims to improve the understanding of how the cardiac microstructure…

Image and Video Processing · Electrical Eng. & Systems 2026-05-19 Yinzhe Wu , Jiahao Huang , Fanwen Wang , Pedro Ferreira , Andrew Scott , Sonia Nielles-Vallespin , Guang Yang

Diffusion MRI (dMRI) is a valuable tool to map brain microstructure and connectivity by analyzing water molecule diffusion in tissue. However, acquiring dMRI data requires to capture multiple 3D brain volumes in a short time, often leading…

Image and Video Processing · Electrical Eng. & Systems 2025-08-29 Sedigheh Dargahi , Sylvain Bouix , Christian Desrosiers

Diffusion-weighted imaging (DWI) is a powerful non-invasive tool which is widely used in clinical routine. Mostly, apparent diffusion coefficient maps are acquired, which cannot be directly related to cellular structure. More recently it…

Recent innovations in Magnetic Resonance Imaging (MRI) hardware and software have reignited interest in low-field ($<1\,\mathrm{T}$) and ultra-low-field MRI ($<0.1\,\mathrm{T}$). These technologies offer advantages such as lower power…

Image and Video Processing · Electrical Eng. & Systems 2025-01-30 Andreas Kofler , Dongyue Si , David Schote , Rene M Botnar , Christoph Kolbitsch , Claudia Prieto

Decoding visual stimuli from neural responses recorded by functional Magnetic Resonance Imaging (fMRI) presents an intriguing intersection between cognitive neuroscience and machine learning, promising advancements in understanding human…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Jingyuan Sun , Mingxiao Li , Zijiao Chen , Yunhao Zhang , Shaonan Wang , Marie-Francine Moens
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