LEADER 05150nam 22007095 450 001 9910747590803321 005 20231007061654.0 010 $a3-031-44858-8 024 7 $a10.1007/978-3-031-44858-4 035 $a(MiAaPQ)EBC30775398 035 $a(Au-PeEL)EBL30775398 035 $a(DE-He213)978-3-031-44858-4 035 $a(PPN)272913758 035 $a(EXLCZ)9928477900900041 100 $a20231007d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Clinical Neuroimaging$b[electronic resource] $e6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings /$fedited by Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja T. Govindarajan, Mohamad Habes, Vinod Kumar, Esten Leonardsen, Thomas Wolfers, Yiming Xiao 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (183 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14312 311 08$aPrint version: Abdulkadir, Ahmed Machine Learning in Clinical Neuroimaging Cham : Springer,c2023 9783031448577 327 $aMachine 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. 330 $aThis book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14312 606 $aComputer vision 606 $aMachine learning 606 $aComputers 606 $aSocial sciences$xData processing 606 $aComputer Vision 606 $aMachine Learning 606 $aComputing Milieux 606 $aComputer Application in Social and Behavioral Sciences 615 0$aComputer vision. 615 0$aMachine learning. 615 0$aComputers. 615 0$aSocial sciences$xData processing. 615 14$aComputer Vision. 615 24$aMachine Learning. 615 24$aComputing Milieux. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a006.37 700 $aAbdulkadir$b Ahmed$01431707 701 $aBathula$b Deepti R$01431708 701 $aDvornek$b Nicha C$01431709 701 $aGovindarajan$b Sindhuja T$01431710 701 $aHabes$b Mohamad$01431711 701 $aKumar$b Vinod$0767644 701 $aLeonardsen$b Esten$01431712 701 $aWolfers$b Thomas$01431713 701 $aXiao$b Yiming$01431714 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910747590803321 996 $aMachine Learning in Clinical Neuroimaging$93574622 997 $aUNINA