Format:
Online-Ressource (XXI, 477 p. 238 illus., 186 illus. in color, online resource)
Edition:
Springer eBook Collection. Computer Science
ISBN:
9783030117238
Series Statement:
Image Processing, Computer Vision, Pattern Recognition, and Graphics 11383
Content:
This two-volume set LNCS 11383 and 11384 constitutes revised selected papers from the 4th International MICCAI Brainlesion Workshop, BrainLes 2018, as well as the International Multimodal Brain Tumor Segmentation, BraTS, Ischemic Stroke Lesion Segmentation, ISLES, MR Brain Image Segmentation, MRBrainS18, Computational Precision Medicine, CPM, and Stroke Workshop on Imaging and Treatment Challenges, SWITCH, which were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI, in Granada, Spain, in September 2018. The 92 papers presented in this volume were carefully reviewed and selected from 95 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; ischemic stroke lesion image segmentation; grand challenge on MR brain segmentation; computational precision medicine; stroke workshop on imaging and treatment challenges
Content:
Brain lesion image analysis.-Brain tumor image segmentation -- Ischemic stroke lesion image segmentation -- Grand challenge on MR brain segmentation -- Computational precision medicine -- Stroke workshop on imaging and treatment challenges
Additional Edition:
ISBN 9783030117221
Additional Edition:
ISBN 9783030117245
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 978-3-030-11722-1
Additional Edition:
Printed edition ISBN 9783030117221
Additional Edition:
Printed edition ISBN 9783030117245
Additional Edition:
Erscheint auch als Druck-Ausgabe BrainLes (4. : 2018 : Granada) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ; Part I Cham : Springer, 2019 ISBN 9783030117221
Language:
English
Keywords:
Maschinelles Sehen
;
Elektronische Patientenakte
;
Maschinelles Lernen
;
Bioinformatik
;
Konferenzschrift
DOI:
10.1007/978-3-030-11723-8
URL:
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