Improving the segmentation of anatomical structures in chest radiographs using U-net with an imagenet pre-trained encoder

Maayan Frid-Adar, Avi Ben-Cohen, Rula Amer, Hayit Greenspan

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

Abstract

Accurate segmentation of anatomical structures in chest radiographs is essential for many computer-aided diagnosis tasks. In this paper we investigate the latest fully-convolutional architectures for the task of multi-class segmentation of the lungs field, heart and clavicles in a chest radiograph. In addition, we explore the influence of using different loss functions in the training process of a neural network for semantic segmentation. We evaluate all models on a common benchmark of 247 X-ray images from the JSRT database and ground-truth segmentation masks from the SCR dataset. Our best performing architecture, is a modified U-Net that benefits from pre-trained encoder weights. This model outperformed the current state-of-the-art methods tested on the same benchmark, with Jaccard overlap scores of 96.1% for lung fields, 90.6% for heart and 85.5% for clavicles.

Original languageEnglish
Title of host publicationImage Analysis for Moving Organ, Breast, and Thoracic Images - Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Proceedings
EditorsDavid Snead, Emanuele Trucco, Danail Stoyanov, Zeike Taylor, Lena Maier-Hein, Nasir Rajpoot, Hrvoje Bogunovic, Francesco Ciompi, Mitko Veta, Mona K. Garvin, Xin Jan Chen, Anne Martel, Jeroen van der Laak, Yanwu Xu, Stephen McKenna
PublisherSpringer Verlag
Pages159-168
Number of pages10
ISBN (Print)9783030009458
DOIs
StatePublished - 2018
Event3rd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2018, 4th International Workshop on Breast Image Analysis, BIA 2018, and 1st International Workshop on Thoracic Image Analysis, TIA 2018, held in conjunction with 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 16 Sep 201820 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11040 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2018, 4th International Workshop on Breast Image Analysis, BIA 2018, and 1st International Workshop on Thoracic Image Analysis, TIA 2018, held in conjunction with 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018
Country/TerritorySpain
CityGranada
Period16/09/1820/09/18

Keywords

  • Chest radiographs
  • Clavicle segmentation
  • Fully convolutional networks
  • Heart segmentation
  • Lung segmentation

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