Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year :

Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net

Abstract

Segmentation of the myocardium is a key step for image guided diagnosis in many cardiac diseases. In this article, we propose an automatic multi-atlas segmentation framework which relies on a very fast registration algorithm trained with convolutional neural networks. The speed of this registration method allows us to use a high number of templates in the multi-atlas segmentation while remaining computation-ally tractable. The performance of the propose approach is evaluated on a dataset of 100 end-diastolic and end-systolic MRI images of the STACOM 2017 Automated Cardiac Diagnosis Challenge (ACDC).

Domains

Medical Imaging
Fichier principal
Vignette du fichier
stacom_seg_v2.pdf (1.52 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01575297 , version 1 (18-08-2017)

Identifiers

Cite

Marc-Michel Rohé, Maxime Sermesant, Xavier Pennec. Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net. STACOM: Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, Sep 2017, Québec, Canada. pp.170-177, ⟨10.1007/978-3-319-75541-0_18⟩. ⟨hal-01575297⟩

Collections

INRIA INRIA2
302 View
414 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More