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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 I /

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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Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Greenspan, Hayit (Editor), Madabhushi, Anant (Editor), Mousavi, Parvin (Editor), Salcudean, Septimiu (Editor), Duncan, James (Editor), Syeda-Mahmood, Tanveer (Editor), Taylor, Russell (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Udgivelse:1st ed. 2023.
Serier:Lecture Notes in Computer Science, 14220
Fag:
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 adgang:https://doi.org/10.1007/978-3-031-43907-0
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Beskrivelse
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; clinical applications – 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.
Fysisk beskrivelse:1 online resource (XXXVIII, 785 p. 240 illus.). 227 illus. in color.
ISBN:9783031439070
ISSN:1611-3349 ;
DOI:10.1007/978-3-031-43907-0

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