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Machine Learning in Clinical Neuroimaging : 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings / edited by Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja T. Govindarajan, Mohamad Habes, Vinod Kumar, Esten Leonardsen, Thomas Wolfers, Yiming Xiao
(Lecture Notes in Computer Science. ISSN:16113349 ; 14312)
| データ種別 | 電子ブック |
|---|---|
| 版 | 1st ed. 2023. |
| 出版者 | (Cham : Springer Nature Switzerland : Imprint: Springer) |
| 出版年 | 2023 |
| 大きさ | X, 174 p. 52 illus., 47 illus. in color : online resource |
| 著者標目 | Abdulkadir, Ahmed editor Bathula, Deepti R editor Dvornek, Nicha C editor Govindarajan, Sindhuja T editor Habes, Mohamad editor Kumar, Vinod editor Leonardsen, Esten editor Wolfers, Thomas editor Xiao, Yiming editor SpringerLink (Online service) |
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| 一般注記 | Machine Learning -- Image-to-Image Translation between Tau Pathology and Neuronal Metabolism PET in Alzheimer Disease with Multi-Domain Contrastive Learning -- Multi-Shell dMRI Estimation from Single-Shell Data via Deep Learning -- A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging -- Cross-Attention for Improved Motion Correction in Brain PET -- VesselShot: Few-shot learning for cerebral blood vessel segmentation -- WaveSep: A Flexible Wavelet-based Approach for Source Separation in Susceptibility Imaging -- Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks -- Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation -- Clinical Applications -- Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain -- MixUp brain-cortical augmentations in self-supervised learning -- Brain age prediction based on head computed tomography segmentation -- Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification -- Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder -- Deep attention assisted multi-resolution networks for the segmentation of white matter hyperintensities in postmortem MRI scans -- Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder -- Morphological versus Functional Network Organization: A Comparison Between Structural Covariance Networks and Probabilistic Functional Modes This book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications HTTP:URL=https://doi.org/10.1007/978-3-031-44858-4 |
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| 件 名 | LCSH:Computer vision LCSH:Machine learning LCSH:Computers LCSH:Social sciences -- Data processing 全ての件名で検索 FREE:Computer Vision FREE:Machine Learning FREE:Computing Milieux FREE:Computer Application in Social and Behavioral Sciences |
| 分 類 | LCC:TA1634 DC23:006.37 |
| 書誌ID | EB00004011 |
| ISBN | 9783031448584 |
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