Fully automatic segmentation of coronary arteries based on deep neural network in intravascular ultrasound images

Sekeun Kim, Yeonggul Jang, Byunghwan Jeon, Youngtaek Hong, Hackjoon Shim, Hyukjae Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Accurate segmentation of coronary arteries is important for the diagnosis of cardiovascular diseases. In this paper, we propose a fully convolutional neural network to efficiently delineate the boundaries of the wall and lumen of the coronary arteries using intravascular ultrasound (IVUS) images. Our network addresses multi-label segmentation of the wall and lumen areas at the same time. The primary body of the proposed network is U-shaped which contains the encoding and decoding paths to learn rich hierarchical representations. The multi-scale input layer is adapted to take a multi-scale input. We deploy a multi-label loss function with weighted pixel-wise cross-entropy to alleviate imbalance of the rate of background, wall, and lumen. The proposed method is compared with three existing methods and the segmentation results are measured on four metrics, dice similarity coefficient, Jaccard index, percentage of area difference, and Hausdorff distance on totally 38,478 IVUS images from 35 subjects.

Original languageEnglish
Title of host publicationIntravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis - 7th Joint International Workshop, CVII-STENT 2018 and Third International Workshop, LABELS 2018 Held in Conjunction with MICCAI 2018
EditorsSu-Lin Lee, Emanuele Trucco, Lena Maier-Hein, Stefano Moriconi, Shadi Albarqouni, Pierre Jannin, Simone Balocco, Guillaume Zahnd, Diana Mateus, Zeike Taylor, Stefanie Demirci, Danail Stoyanov, Raphael Sznitman, Anne Martel, Veronika Cheplygina, Eric Granger, Luc Duong
PublisherSpringer Verlag
Pages161-168
Number of pages8
ISBN (Print)9783030013639
DOIs
Publication statusPublished - 2018
Event7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the 3rd International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 2018 Sep 162018 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11043 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the 3rd International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018
Country/TerritorySpain
CityGranada
Period18/9/1618/9/16

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2018.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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