Deep learning for multi-task medical image segmentation in multiple modalities

Pim Moeskops*, Jelmer M. Wolterink, Bas H.M. van der Velden, Kenneth G.A. Gilhuijs, Tim Leiner, Max A. Viergever, Ivana Išgum

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

145 Citations (Scopus)

Abstract

Automatic segmentation of medical images is an important task for many clinical applications. In practice,a wide range of anatomical structures are visualised using different imaging modalities. In this paper,we investigate whether a single convolutional neural network (CNN) can be trained to perform different segmentation tasks. A single CNN is trained to segment six tissues in MR brain images,the pectoral muscle in MR breast images,and the coronary arteries in cardiac CTA. The CNN therefore learns to identify the imaging modality,the visualised anatomical structures,and the tissue classes. For each of the three tasks (brain MRI,breast MRI and cardiac CTA),this combined training procedure resulted in a segmentation performance equivalent to that of a CNN trained specifically for that task,demonstrating the high capacity of CNN architectures. Hence,a single system could be used in clinical practice to automatically perform diverse segmentation tasks without task-specific training.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016
Subtitle of host publication19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings
EditorsGozde Unal, Sebastian Ourselin, Leo Joskowicz, Mert R. Sabuncu, William Wells
Place of PublicationCham
PublisherSpringer
Pages478-486
Number of pages9
VolumeII
ISBN (Electronic)978-3-319-46723-8
ISBN (Print)978-3-319-46722-1
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: 17 Oct 201621 Oct 2016
Conference number: 19

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9901
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameImage Processing, Computer Vision, Pattern Recognition, and Graphics
PublisherSpringer

Conference

Conference19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Abbreviated titleMICCAI
CountryGreece
CityAthens
Period17/10/1621/10/16

Keywords

  • Brain MRI
  • Breast MRI
  • Cardiac CTA
  • Convolutional neural networks
  • Deep learning
  • Medical image segmentation

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