Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation

Hongwei Li, Jianguo Zhang (Lead / Corresponding author), Mark Muehlau, Jan Kirschke, Bjoern Menze

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Abstract

Segmentation of both large and small white matter hyperintensities/lesions in brain MR images is a challenging task which has drawn much attention in recent years. We propose a multi-scale aggregation model framework to deal with volume-varied lesions. Firstly, we present a specifically-designed network for small lesion segmentation called Stack-Net, in which multiple convolutional layers are ‘one-by-one’ connected, aiming to preserve rich local spatial information of small lesions before the sub-sampling layer. Secondly, we aggregate multi-scale Stack-Nets with different receptive fields to learn multi-scale contextual information of both large and small lesions. Our model is evaluated on recent MICCAI WMH Challenge Dataset and outperforms the state-of-the-art on lesion recall and lesion F1-score under 5-fold cross validation. It claimed the first place on the hidden test set after independent evaluation by the challenge organizer. In addition, we further test our pre-trained models on a Multiple Sclerosis lesion dataset with 30 subjects under cross-center evaluation. Results show that the aggregation model is effective in learning multi-scale spatial information.

Original languageEnglish
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
EditorsAlessandro Crimi, Spyridon Bakas, Hugo Kuijf, Farahani Keyvan, Mauricio Reyes, Theo van Walsum
Place of PublicationSwitzerland
PublisherSpringer Verlag
Pages199-207
Number of pages9
Volume11393
ISBN (Electronic)9783030117238
ISBN (Print)9783030117221
DOIs
Publication statusE-pub ahead of print - 26 Jan 2019
EventMICCAI 2018: 21st International Conference on Medical Image Computing & Computer Assisted Intervention - Granada Conference Centre, Granada, Spain
Duration: 16 Sep 201820 Sep 2018
Conference number: 21
https://www.miccai2018.org/en/Default.asp?

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
Volume11383
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceMICCAI 2018
CountrySpain
CityGranada
Period16/09/1820/09/18
Internet address

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Keywords

  • Deep learning
  • White matter hyperintensities

Cite this

Li, H., Zhang, J., Muehlau, M., Kirschke, J., & Menze, B. (2019). Multi-Scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation. In A. Crimi, S. Bakas, H. Kuijf, F. Keyvan, M. Reyes, & T. van Walsum (Eds.), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (Vol. 11393, pp. 199-207). (Lecture Notes in Computer Science; Vol. 11383). Springer Verlag. https://doi.org/10.1007/978-3-030-11723-8_20