Wir verwenden Cookies und Analyse-Tools, um die Nutzerfreundlichkeit der Internet-Seite zu verbessern und für Marketingzwecke. Wenn Sie fortfahren, diese Seite zu verwenden, nehmen wir an, dass Sie damit einverstanden sind. Zur Datenschutzerklärung.
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
Details
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.
The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;
Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;
Part III: Breast imaging; colonoscopy; computer aided diagnosis;
Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;
Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;
Part VI: Image registration; image reconstruction;
Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning domain adaptation and generalization;
Part VIII: Machine learning weakly-supervised learning; machine learning model interpretation; machine learning uncertainty; machine learning theory and methodologies.
Klappentext
Machine learning - weakly-supervised learning.- machine learning - model interpretation.- machine learning - uncertainty.- machine learning theory and methodologies.
Inhalt
Machine learning weakly-supervised learning.- machine learning model interpretation.- machine learning uncertainty.- machine learning theory and methodologies.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031164514
- Lesemotiv Verstehen
- Genre Electrical Engineering
- Auflage 1st edition 2022
- Editor Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
- Sprache Englisch
- Anzahl Seiten 784
- Herausgeber Springer
- Größe H235mm x B155mm x T42mm
- Jahr 2022
- EAN 9783031164514
- Format Kartonierter Einband
- ISBN 3031164512
- Veröffentlichung 16.09.2022
- Titel Medical Image Computing and Computer Assisted Intervention - MICCAI 2022
- Untertitel 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part VIII
- Gewicht 1165g