Paper
18 March 2013 Automatic abdominal lymph node detection method based on local intensity structure analysis from 3D x-ray CT images
Yoshihiko Nakamura, Yukitaka Nimura, Takayuki Kitasaka, Shinji Mizuno, Kazuhiro Furukawa, Hidemi Goto, Michitaka Fujiwara, Kazunari Misawa, Masaaki Ito, Shigeru Nawano, Kensaku Mori
Author Affiliations +
Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86701K (2013) https://doi.org/10.1117/12.2008282
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
This paper presents an automated method of abdominal lymph node detection to aid the preoperative diagnosis of abdominal cancer surgery. In abdominal cancer surgery, surgeons must resect not only tumors and metastases but also lymph nodes that might have a metastasis. This procedure is called lymphadenectomy or lymph node dissection. Insufficient lymphadenectomy carries a high risk for relapse. However, excessive resection decreases a patient's quality of life. Therefore, it is important to identify the location and the structure of lymph nodes to make a suitable surgical plan. The proposed method consists of candidate lymph node detection and false positive reduction. Candidate lymph nodes are detected using a multi-scale blob-like enhancement filter based on local intensity structure analysis. To reduce false positives, the proposed method uses a classifier based on support vector machine with the texture and shape information. The experimental results reveal that it detects 70.5% of the lymph nodes with 13.0 false positives per case.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yoshihiko Nakamura, Yukitaka Nimura, Takayuki Kitasaka, Shinji Mizuno, Kazuhiro Furukawa, Hidemi Goto, Michitaka Fujiwara, Kazunari Misawa, Masaaki Ito, Shigeru Nawano, and Kensaku Mori "Automatic abdominal lymph node detection method based on local intensity structure analysis from 3D x-ray CT images", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86701K (18 March 2013); https://doi.org/10.1117/12.2008282
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Cited by 8 scholarly publications.
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KEYWORDS
Lymphatic system

Surgery

Cancer

Computed tomography

3D image processing

X-ray computed tomography

Spherical lenses

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