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03342nmm a2200421 u 4500 |
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221201 ||| eng |
| 020 |
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|a 9783031212062
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| 100 |
1 |
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|a Cetin-Karayumak, Suheyla
|e [editor]
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| 245 |
0 |
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|a Computational Diffusion MRI
|h Elektronische Ressource
|b 13th International Workshop, CDMRI 2022, Held in Conjunction with MICCAI 2022, Singapore, Singapore, September 22, 2022, Proceedings
|c edited by Suheyla Cetin-Karayumak, Daan Christiaens, Matteo Figini, Pamela Guevara, Tomasz Pieciak, Elizabeth Powell, Francois Rheault
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| 250 |
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|a 1st ed. 2022
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| 260 |
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|a Cham
|b Springer Nature Switzerland
|c 2022, 2022
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| 300 |
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|a X, 149 p. 56 illus., 53 illus. in color
|b online resource
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| 505 |
0 |
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|a Data preprocessing -- Slice estimation in diffusion MRI of neonatal and fetal brains in image and spherical harmonics domains using autoencoders -- Super-resolution of manifold-valued diffusion MRI refined by multi-modal imaging -- Lossy compression of multidimensional medical images using sinusoidal activation networks: an evaluation study -- Correction of susceptibility distortion in EPI: a semi-supervised approach with deep learning -- The impact of susceptibility distortion correction protocols on adolescent diffusion MRI measures -- Signal representations -- Diffusion MRI Fibre Orientation Distribution Inpainting -- Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning -- Stepwise Stochastic Dictionary Adaptation Improves Microstructure Reconstruction with Orientation Distribution Function Fingerprinting -- How can spherical CNNs benefit ML-based diffusion MRI parameter estimation? -- Tractography and WM pathways -- DC2U-Net: Tract Segmentation in Brain White Matter Using Dense Criss-Cross U-Net -- Clustering in Tractography using Autoencoders (CINTA) -- Tractometric Coherence of Fiber Bundles in DTI.
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| 653 |
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|a Image processing / Digital techniques
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| 653 |
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|a Education / Data processing
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| 653 |
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|a Mathematics of Computing
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| 653 |
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|a Computer science / Mathematics
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| 653 |
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|a Computer vision
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| 653 |
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|a Computer Application in Social and Behavioral Sciences
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Social sciences / Data processing
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| 653 |
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|a Computers and Education
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| 653 |
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|a Computer Imaging, Vision, Pattern Recognition and Graphics
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| 653 |
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|a Artificial intelligence
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| 700 |
1 |
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|a Christiaens, Daan
|e [editor]
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| 700 |
1 |
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|a Figini, Matteo
|e [editor]
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| 700 |
1 |
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|a Guevara, Pamela
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Computer Science
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| 028 |
5 |
0 |
|a 10.1007/978-3-031-21206-2
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-031-21206-2?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006
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| 520 |
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|a This book constitutes the proceedings of the International Workshop on Computational Diffusion MRI, CDMRI 2022, which was held 22 September 2022, in conjunction with MICCAI 2022. The 12 full papers included were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: Data processing, Signal representations, Tractography and WM pathways
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