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Pelvis segmentation using multi-pass U-Net and iterative shape estimation
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging. (medicinsk bildbehandling och visualisering)ORCID iD: 0000-0002-0442-3524
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2018 (English)In: Computational Methods and Clinical Applications in Musculoskeletal Imaging, Springer, 2018, Vol. 11404, p. 49-57Conference paper, Published paper (Refereed)
Abstract [en]

In this report, an automatic method for segmentation of the pelvis in three-dimensional (3D) computed tomography (CT) images is proposed. The method is based on a 3D U-net which has as input the 3D CT image and estimated volumetric shape models of the targeted structures and which returns the probability maps of each structure. During training, the 3D U-net is initially trained using blank shape context inputs to generate the segmentation masks, i.e. relying only on the image channel of the input. The preliminary segmentation results are used to estimate a new shape model, which is then fed to the same network again, with the input images. With the additional shape context information, the U-net is trained again to generate better segmentation results. During the testing phase, the input image is fed through the same 3D U-net multiple times, first with blank shape context channels and then with iteratively re-estimated shape models. Preliminary results show that the proposed multi-pass U-net with iterative shape estimation outperforms both 2D and 3D conventional U-nets without the shape model.

Place, publisher, year, edition, pages
Springer, 2018. Vol. 11404, p. 49-57
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 11404
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:kth:diva-258890DOI: 10.1007/978-3-030-11166-3_5Scopus ID: 2-s2.0-85060256089ISBN: 9783030111656 (print)OAI: oai:DiVA.org:kth-258890DiVA, id: diva2:1350236
Conference
6th International Workshop on Computational Methods and Clinical Applications in Musculoskeletal Imaging, MSKI 2018 was held in conjunction with Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018; Granada; Spain; 16 September 2018 through 20 September 2018
Note

QC 20190913

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-09-16Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Output format
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