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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.
Nakamura et al. (Mon,) studied this question.