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Proceedings Paper

Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT images
Author(s): Hirohisa Oda; Holger R. Roth; Kanwal K. Bhatia; Masahiro Oda; Takayuki Kitasaka; Shingo Iwano; Hirotoshi Homma; Hirotsugu Takabatake; Masaki Mori; Hiroshi Natori; Julia A. Schnabel; Kensaku Mori
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Paper Abstract

We propose a novel mediastinal lymph node detection and segmentation method from chest CT volumes based on fully convolutional networks (FCNs). Most lymph node detection methods are based on filters for blob-like structures, which are not specific for lymph nodes. The 3D U-Net is a recent example of the state-of-the-art 3D FCNs. The 3D U-Net can be trained to learn appearances of lymph nodes in order to output lymph node likelihood maps on input CT volumes. However, it is prone to oversegmentation of each lymph node due to the strong data imbalance between lymph nodes and the remaining part of the CT volumes. To moderate the balance of sizes between the target classes, we train the 3D U-Net using not only lymph node annotations but also other anatomical structures (lungs, airways, aortic arches, and pulmonary arteries) that can be extracted robustly in an automated fashion. We applied the proposed method to 45 cases of contrast-enhanced chest CT volumes. Experimental results showed that 95.5% of lymph nodes were detected with 16.3 false positives per CT volume. The segmentation results showed that the proposed method can prevent oversegmentation, achieving an average Dice score of 52.3 ± 23.1%, compared to the baseline method with 49.2 ± 23.8%, respectively.

Paper Details

Date Published: 27 February 2018
PDF: 6 pages
Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 1057502 (27 February 2018); doi: 10.1117/12.2287066
Show Author Affiliations
Hirohisa Oda, Nagoya Univ. (Japan)
Holger R. Roth, Nagoya Univ. (Japan)
Kanwal K. Bhatia, King's College London (United Kingdom)
Masahiro Oda, Nagoya Univ. (Japan)
Takayuki Kitasaka, Aichi Institute of Technology (Japan)
Shingo Iwano, Nagoya Univ. Graduate School of Medicine (Japan)
Hirotoshi Homma, Sapporo-Kosei General Hospital (Japan)
Hirotsugu Takabatake, Sapporo Minami-Sanjo Hospital (Japan)
Masaki Mori, Sapporo-Kosei General Hospital (Japan)
Hiroshi Natori, Keiwakai Nishioka Hospital (Japan)
Julia A. Schnabel, King's College London (United Kingdom)
Kensaku Mori, Nagoya Univ. (Japan)

Published in SPIE Proceedings Vol. 10575:
Medical Imaging 2018: Computer-Aided Diagnosis
Nicholas Petrick; Kensaku Mori, Editor(s)

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