Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges : 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers / edited by Mihaela Pop, Maxime Sermesant, Jichao Zhao, Shuo Li, Kristin McLeod, Alistair Young, Kawal Rhode, Tommaso Mansi.

Format:

Book

Contributor:

Pop, Mihaela, editor.

Sermesant, Maxime, editor.

Zhao, Jichao, editor.

Li, Shuo, editor.

McLeod, Kristin, editor.

Young, Alistair, editor.

Rhode, Kawal, editor.

Mansi, Tommaso, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11395.

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11395

Language:

English

Subjects (All):

Optical data processing.

Artificial intelligence.

Computer networks.

Data mining.

Image Processing and Computer Vision.

Artificial Intelligence.

Computer Communication Networks.

Data Mining and Knowledge Discovery.

Local Subjects:

Image Processing and Computer Vision.

Artificial Intelligence.

Computer Communication Networks.

Data Mining and Knowledge Discovery.

Physical Description:

1 online resource (XIV, 487 pages) : 216 illustrations, 192 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Contents:

Cardiac imaging and image processing

Machine learning applied to cardiac imaging and image analysis

Atlas construction

Statistical modelling of cardiac function across different patient populations

Cardiac computational physiology

Model customization

Atlas based functional analysis

Ontological schemata for data and results

Integrated functional and structural analyses

Pre-clinical and clinical applicability of these methods.

Other Format:

Printed edition:

ISBN:

978-3-030-12029-0

9783030120290

Access Restriction:

Restricted for use by site license.