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Machine Learning in Medical Imaging [electronic resource] : 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / edited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu.

Contributor(s): Shi, Yinghuan [editor.] | Suk, Heung-Il [editor.] | Liu, Mingxia [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics: 11046Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XII, 409 p. 154 illus., 138 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030009199.Subject(s): Computer vision | Artificial intelligence | Medical informatics | Data mining | Computer Vision | Artificial Intelligence | Health Informatics | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.37 Online resources: Click here to access online In: Springer Nature eBookSummary: This book constitutes the proceedings of the 9th International Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
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This book constitutes the proceedings of the 9th International Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

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