Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images

Nicola K. Dinsdale, Mark Jenkinson, Ana I.L. Namburete

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

15 Citations (Scopus)

Abstract

Accurate segmentations of neuroanatomical structures are essential for volumetric and morphological assessment, but manual segmentation is time-consuming and error-prone. We propose a convolutional neural network for structural segmentation based on deformation of an example mask that is disease-state agnostic, which we apply to the hippocampus. The hippocampus is one of the first subcortical structures affected by Alzheimer’s disease, atrophying as the disease progresses. As the disease state may be unknown, and due to the varying degrees of atrophy, an accurate shape prior is not always available. The proposed network is based on an adapted spatial transformer network that learns a deformation field to resample an initial binary mask, to create an output segmentation. This segmentation is learnt by the network from the input T1-weighted MRI in an end-to-end manner. Experiments on the HarP dataset show that the network outperforms other segmentation methods and is consistent across disease states, independent of the degree of disease-related atrophy. We also explore the effect of the initial binary mask on the segmentation, showing that the it is insensitive to the size and initial location of the binary mask.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings
EditorsDinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou
PublisherSpringer Science and Business Media Deutschland GmbH
Pages284-291
Number of pages8
ISBN (Print)9783030322472
DOIs
Publication statusPublished or Issued - 2019
Externally publishedYes
Event22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 13 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11766 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019
Country/TerritoryChina
CityShenzhen
Period13/10/1917/10/19

Keywords

  • Hippocampus
  • Segmentation
  • Spatial transformer

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this