Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II

This two volume-set LNCS 13769 and LNCS 14092 constitutes the refereed proceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022, as well as the Brain Tumor Segmentation (BraTS) Challenge, the Brain Tumor Sequence Registration (BraTS-Reg) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the Federated Tumor Segmentation (FeTS) Challenge. These were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2022, in September 2022. The 46 revised full papers presented in these volumes were selected form 65 submissions.The presented contributions describe the research of computational scientists and clinical researchers working on brain lesions - specifically glioma, multiple sclerosis, cerebral stroke, traumatic brain injuries, vestibular schwannoma, and white matter hyper-intensities of presumed vascular origin. 

Product details

• Assisted by: Spyridon Bakas (Editor), Alessandro Crimi (Editor), Ujjwal Baid et al (Editor), Ujjwal Baid (Editor), Sylwia Malec (Editor), Monika Pytlarz (Editor), Bhakti Baheti (Editor), Maximilian Zenk (Editor), Reuben Dorent (Editor)
• Publisher: Springer, Berlin
• Content: Book
• Product form: Paperback / Softback
• Publication date: 05.02.2024
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > Application software
• EAN: 9783031441523
• ISBN: 978-3-0-3144152-3
• Pages: 243
• Illustrations: XIX, 243 p. 75 illus., 59 illus. in color.
• Dimensions (packing): 15.5 x 1.4 x 23.5 cm
• Series: Lecture Notes in Computer Science > 14092
• Subjects: Lehrmittel, Lerntechnologien, E-Learning, Brain, Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften, Computeranwendungen in Industrie und Technologie, CAD, glioblastoma, glioma, Segmentation, DeepLearning, machinelearning, MultipleSclerosis, traumaticbraininjury, brainlesion