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001482328 001__ 1482328
001482328 003__ OCoLC
001482328 005__ 20231128003331.0
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001482328 008__ 231012s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001482328 020__ $$a9783031448584$$q(electronic bk.)
001482328 020__ $$a3031448588$$q(electronic bk.)
001482328 020__ $$z9783031448577
001482328 0247_ $$a10.1007/978-3-031-44858-4$$2doi
001482328 035__ $$aSP(OCoLC)1402285590
001482328 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCF
001482328 049__ $$aISEA
001482328 050_4 $$aQ325.5
001482328 08204 $$a006.3/1$$223/eng/20231012
001482328 1112_ $$aMLCN (Workshop)$$n(6th :$$d2023 :$$cVancouver, B.C.)
001482328 24510 $$aMachine learning in clinical neuroimaging :$$b6th international workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, proceedings /$$cAhmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja T. Govindarajan, Mohamad Habes, Vinod Kumar, Esten Leonardsen, Thomas Wolfers, Yiming Xiao, editors.
001482328 24630 $$aMLCN 2023
001482328 264_1 $$aCham :$$bSpringer,$$c[2023]
001482328 264_4 $$c©2023
001482328 300__ $$a1 online resource (x, 174 pages) :$$billustrations (chiefly color).
001482328 336__ $$atext$$btxt$$2rdacontent
001482328 337__ $$acomputer$$bc$$2rdamedia
001482328 338__ $$aonline resource$$bcr$$2rdacarrier
001482328 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v14312
001482328 500__ $$aInternational conference proceedings.
001482328 500__ $$aIncludes author index.
001482328 5050_ $$aMachine Learning -- Image-to-Image Translation between Tau Pathology and Neuronal Metabolism PET in Alzheimer Disease with Multi-Domain Contrastive Learning -- Multi-Shell dMRI Estimation from Single-Shell Data via Deep Learning -- A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging -- Cross-Attention for Improved Motion Correction in Brain PET -- VesselShot: Few-shot learning for cerebral blood vessel segmentation -- WaveSep: A Flexible Wavelet-based Approach for Source Separation in Susceptibility Imaging -- Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks -- Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation -- Clinical Applications -- Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain -- MixUp brain-cortical augmentations in self-supervised learning -- Brain age prediction based on head computed tomography segmentation -- Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification -- Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder -- Deep attention assisted multi-resolution networks for the segmentation of white matter hyperintensities in postmortem MRI scans -- Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder -- Morphological versus Functional Network Organization: A Comparison Between Structural Covariance Networks and Probabilistic Functional Modes.
001482328 506__ $$aAccess limited to authorized users.
001482328 520__ $$aThis book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions. The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track). The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.
001482328 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 12, 2023).
001482328 650_6 $$aImagerie pour le diagnostic$$xTechniques numériques$$vCongrès.
001482328 650_6 $$aApprentissage automatique$$vCongrès.
001482328 650_6 $$aTraitement réparti$$vCongrès.
001482328 650_0 $$aDiagnostic imaging$$xDigital techniques$$vCongresses.$$0(DLC)sh2007006024
001482328 650_0 $$aMachine learning$$vCongresses.$$vCongresses$$0(DLC)sh2008107143
001482328 650_0 $$aElectronic data processing$$xDistributed processing$$vCongresses.
001482328 655_0 $$aElectronic books.
001482328 655_7 $$aproceedings (reports)$$2aat
001482328 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001482328 655_7 $$aConference papers and proceedings.$$2lcgft
001482328 655_7 $$aActes de congrès.$$2rvmgf
001482328 7001_ $$aAbdulkadir, Ahmed,$$eeditor.
001482328 7001_ $$aBathula, Deepti R.,$$eeditor.
001482328 7001_ $$aDvornek, Nicha C.,$$eeditor.
001482328 7001_ $$aGovindarajan, Sindhuja T.,$$eeditor.
001482328 7001_ $$aHabes, Mohamad,$$eeditor.
001482328 7001_ $$aKumar, Vinod,$$eeditor.$$0(OCoLC)oca04272939
001482328 7001_ $$aLeonardsen, Esten,$$eeditor.
001482328 7001_ $$aWolfers, Thomas,$$eeditor.
001482328 7001_ $$aXiao, Yiming,$$eeditor.
001482328 7112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(26th :$$d2023 :$$cVancouver, B.C.).
001482328 830_0 $$aLecture notes in computer science ;$$v14312.$$x1611-3349
001482328 852__ $$bebk
001482328 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-44858-4$$zOnline Access$$91397441.1
001482328 909CO $$ooai:library.usi.edu:1482328$$pGLOBAL_SET
001482328 980__ $$aBIB
001482328 980__ $$aEBOOK
001482328 982__ $$aEbook
001482328 983__ $$aOnline
001482328 994__ $$a92$$bISE