Joint learning of motion estimation and segmentation for cardiac MR image sequences

Chen Qin, Wenjia Bai, Jo Schlemper, Steffen E. Petersen, Stefan K. Piechnik, Stefan Neubauer, Daniel Rueckert

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

94 Zitate (Scopus)

Abstract

Cardiac motion estimation and segmentation play important roles in quantitatively assessing cardiac function and diagnosing cardiovascular diseases. In this paper, we propose a novel deep learning method for joint estimation of motion and segmentation from cardiac MR image sequences. The proposed network consists of two branches: a cardiac motion estimation branch which is built on a novel unsupervised Siamese style recurrent spatial transformer network, and a cardiac segmentation branch that is based on a fully convolutional network. In particular, a joint multi-scale feature encoder is learned by optimizing the segmentation branch and the motion estimation branch simultaneously. This enables the weakly-supervised segmentation by taking advantage of features that are unsupervisedly learned in the motion estimation branch from a large amount of unannotated data. Experimental results using cardiac MlRI images from 220 subjects show that the joint learning of both tasks is complementary and the proposed models outperform the competing methods significantly in terms of accuracy and speed.

OriginalspracheEnglisch
TitelMedical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
Redakteure/-innenGabor Fichtinger, Christos Davatzikos, Carlos Alberola-López, Alejandro F. Frangi, Julia A. Schnabel
Herausgeber (Verlag)Springer Verlag
Seiten472-480
Seitenumfang9
ISBN (Print)9783030009335
DOIs
PublikationsstatusVeröffentlicht - 2018
Extern publiziertJa
Veranstaltung21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spanien
Dauer: 16 Sept. 201820 Sept. 2018

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band11071 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

Konferenz

Konferenz21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
Land/GebietSpanien
OrtGranada
Zeitraum16/09/1820/09/18

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