Shape in Medical Imaging

This book PDF is perfect for those who love Computers genre, written by Christian Wachinger and published by Springer Nature which was released on 30 October 2023 with total hardcover pages 312. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Shape in Medical Imaging books below.

Shape in Medical Imaging

Author	: Christian Wachinger
File Size	: 45,7 Mb
Publisher	: Springer Nature
Language	: English
Release Date	: 30 October 2023
ISBN	: 9783031469145
Pages	: 312 pages

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Shape in Medical Imaging by Christian Wachinger Book PDF Summary

This volume comprises the proceedings of the International Workshop, ShapeMI 2023, which took place alongside MICCAI 2023 on October 8, 2023, in Vancouver, British Columbia, Canada. The 23 selected full papers deal with all aspects of leading methods and applications for advanced shape analysis and geometric learning in medical imaging.

Shape in Medical Imaging by Christian Wachinger,Beatriz Paniagua,Shireen Elhabian,Jianning Li,Jan Egger

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Shape in Medical Imaging by Martin Reuter,Christian Wachinger,Hervé Lombaert,Beatriz Paniagua,Marcel Lüthi,Bernhard Egger

This book constitutes the proceedings of the Workshop on Shape in Medical Imaging, ShapeMI 2018, held in conjunction with the 21st International Conference on Medical Image Computing, MICCAI 2018, in Granada, Spain, in September 2018. The 26 full papers and 2 short papers presented were carefully reviewed and selected for inclusion in this volume. The

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Shape in Medical Imaging by Martin Reuter,Christian Wachinger,Hervé Lombaert,Beatriz Paniagua,Orcun Goksel,Islem Rekik

This book constitutes the proceedings of the International Workshop on Shape in Medical Imaging, ShapeMI 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assistend Intervention, MICCAI 2020, in October 2020. The conference was planned to take place in Lima, Peru, but changed to a

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Shape Analysis in Medical Image Analysis by Shuo Li,João Manuel R. S. Tavares

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics

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Spectral and Shape Analysis in Medical Imaging by Martin Reuter,Christian Wachinger,Hervé Lombaert

This book constitutes the refereed post-conference proceedings of the First International Workshop on Spectral and Shape Analysis in Medical Imaging, SeSAMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 10 submitted full papers presented in this volume were carefully reviewed. The papers reflect the following topics: spectral methods;

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Information Processing in Medical Imaging by Attila Kuba,Martin Samal,Andrew Todd-Pokropek

The 1999 international conference on Information Processing in Medical Imaging (IPMI ’99) was the sixteenth in the series of biennial meetings and followed the successful meeting in Poultney, Vermont, in 1997. This year, for the rst time, the conference was held in central Europe, in the historical Hungarian town of Visegr ad, one

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Riemannian Geometric Statistics in Medical Image Analysis by Xavier Pennec,Stefan Sommer,Tom Fletcher

Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is

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A Probabilistic Framework for Point Based Shape Modeling in Medical Image Analysis by Heike Hufnagel

Heike Hufnagel develops a mathematically sound statistical shape model. Due to the particular attributes of the model, the challenging integration of explicit and implicit representations can be performed in an elegant mathematical formulation, thus combining the advantages of both explicit model and implicit segmentation method.

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