000 05643nam a22006615i 4500
001 978-3-031-44858-4
003 DE-He213
005 20240730201031.0
007 cr nn 008mamaa
008 231007s2023 sz | s |||| 0|eng d
020 _a9783031448584
_9978-3-031-44858-4
024 7 _a10.1007/978-3-031-44858-4
_2doi
050 4 _aTA1634
072 7 _aUYQV
_2bicssc
072 7 _aCOM016000
_2bisacsh
072 7 _aUYQV
_2thema
082 0 4 _a006.37
_223
245 1 0 _aMachine Learning in Clinical Neuroimaging
_h[electronic resource] :
_b6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings /
_cedited by Ahmed Abdulkadir, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja T. Govindarajan, Mohamad Habes, Vinod Kumar, Esten Leonardsen, Thomas Wolfers, Yiming Xiao.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aX, 174 p. 52 illus., 47 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v14312
505 0 _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.
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.
650 0 _aComputer vision.
_9165814
650 0 _aMachine learning.
_91831
650 0 _aComputers.
_98172
650 0 _aSocial sciences
_xData processing.
_983360
650 1 4 _aComputer Vision.
_9165815
650 2 4 _aMachine Learning.
_91831
650 2 4 _aComputing Milieux.
_955441
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
700 1 _aAbdulkadir, Ahmed.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165816
700 1 _aBathula, Deepti R.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165817
700 1 _aDvornek, Nicha C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165818
700 1 _aGovindarajan, Sindhuja T.
_eeditor.
_0(orcid)
_10000-0003-1741-0906
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165819
700 1 _aHabes, Mohamad.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165820
700 1 _aKumar, Vinod.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165821
700 1 _aLeonardsen, Esten.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165822
700 1 _aWolfers, Thomas.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165823
700 1 _aXiao, Yiming.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9165824
710 2 _aSpringerLink (Online service)
_9165825
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031448577
776 0 8 _iPrinted edition:
_z9783031448591
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v14312
_923263
856 4 0 _uhttps://doi.org/10.1007/978-3-031-44858-4
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c96352
_d96352