Simplifying Medical Ultrasound
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Simplifying Medical Ultrasound

Third International Workshop, ASMUS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
 EPUB
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ISBN-13:
9783031169021
Veröffentl:
2022
Einband:
EPUB
Seiten:
194
Autor:
Stephen Aylward
Serie:
Lecture Notes in Computer Science
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

This book constitutes the proceedings of the Third International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2022, held on September 18, 2022, in conjunction with MICCAI 2022, the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Singapore.The 18 papers presented in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: classification and detection; Segmentation and Reconstruction; and Assessment, Guidance and Robotics.Chapters "e;Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography"e; and "e;3D Cardiac Anatomy Reconstruction from 2D Segmentations: a Study using Synthetic Data"e; are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
This book constitutes the proceedings of the Third International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2022, held on September 18, 2022, in conjunction with MICCAI 2022, the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference took place in Singapore.The 18 papers presented in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: classification and detection; Segmentation and Reconstruction; and Assessment, Guidance and Robotics.Chapters "e;Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography"e; and "e;3D Cardiac Anatomy Reconstruction from 2D Segmentations: a Study using Synthetic Data"e; are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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