Computational Diffusion MRI

16th International Workshop, CDMRI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

AvMaxime Chamberland,Yuqian Chen

Häftad, Engelska, 2026

Del i serien Lecture Notes in Computer Science

638 kr

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Beskrivning

This book constitutes the proceedings of the 16th International Workshop, CDMRI 2025, held in conjunction with MICCAI 2025, the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention. The workshop took place in Daejeon, South Korea, on September 27, 2025.The 8 full papers presented in this book were carefully reviewed and selected from 10 submissions. They focus on all aspects of diffusion MRI acquisition, analysis, and application, bringing us closer to reliable clinical tools.

Produktinformation

Utgivningsdatum:2026-01-03
Mått:155 x 235 x 7 mm
Vikt:172 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:94
Förlag:Springer Nature Switzerland AG
ISBN:9783032128362

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Medicinsk bildbehandling inom Medicin

Innehållsförteckning

.- From Fiber Tracts to Tumor Spread: Biophysical Modeling of Butterfly Glioma Growth Using Diffusion Tensor Imaging..- Biophysical modeling of Intra-Voxel Incoherent Motion (IVIM) MRI based on realistic cerebral microvascular anatomy and dynamics in mouse and human brain..- Progressive axonal degeneration in white matter pathways traversing peritumoral penumbra in frontotemporal glioma..- Streamline Signature Net (SSN): Efficient White Matter Pathway Recognition for Bundles Parcellation Using Path Signature..- Streamline Density Normalization: A Robust Approach to Mitigate Bundle Variability in Multi-Site Diffusion MRI..- Quantifying Parameter Estimation Difficulty of dMRI Models by Submanifold Geometry in Signal Space..- Susceptibility Distortion Correction of Diffusion MRI with a single Phase-Encoding Direction..- Fully Automated Segmentation of Fiber Bundles in Anatomic Tracing Data.

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