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Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 26th International Conference, Vancouver, BC, Canada, October 8–12, 2023, Proceedings, Part VI /

The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023....

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Greenspan, Hayit (Editor), Madabhushi, Anant (Editor), Mousavi, Parvin (Editor), Salcudean, Septimiu (Editor), Duncan, James (Editor), Syeda-Mahmood, Tanveer (Editor), Taylor, Russell (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:Lecture Notes in Computer Science, 14225
Subjects:
Image processing > Digital techniques.
Computer vision.
Application software.
Machine learning.
Education > Data processing.
Social sciences > Data processing.
Biomedical engineering.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer and Information Systems Applications.
Machine Learning.
Computers and Education.
Computer Application in Social and Behavioral Sciences.
Biomedical Engineering and Bioengineering.
Online Access:https://doi.org/10.1007/978-3-031-43987-2
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Summary:The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinicalapplications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.
Physical Description:1 online resource (XXXIX, 814 p. 259 illus.). 252 illus. in color.
ISBN:9783031439872
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-43987-2

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