18 March 2014 Mediastinal lymph node detection on thoracic CT scans using spatial prior from multi-atlas label fusion
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Abstract
Lymph nodes play an important role in clinical practice but detection is challenging due to low contrast surrounding structures and variable size and shape. We propose a fully automatic method for mediastinal lymph node detection on thoracic CT scans. First, lungs are automatically segmented to locate the mediastinum region. Shape features by Hessian analysis, local scale, and circular transformation are computed at each voxel. Spatial prior distribution is determined based on the identification of multiple anatomical structures (esophagus, aortic arch, heart, etc.) by using multi-atlas label fusion. Shape features and spatial prior are then integrated for lymph node detection. The detected candidates are segmented by curve evolution. Characteristic features are calculated on the segmented lymph nodes and support vector machine is utilized for classification and false positive reduction. We applied our method to 20 patients with 62 enlarged mediastinal lymph nodes. The system achieved a significant improvement with 80% sensitivity at 8 false positives per patient with spatial prior compared to 45% sensitivity at 8 false positives per patient without a spatial prior.
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Jiamin Liu, Jocelyn Zhao, Joanne Hoffman, Jianhua Yao, Weidong Zhang, Evrim B. Turkbey, Shijun Wang, Christine Kim, Ronald M. Summers, "Mediastinal lymph node detection on thoracic CT scans using spatial prior from multi-atlas label fusion", Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90350M (18 March 2014); doi: 10.1117/12.2043737; https://doi.org/10.1117/12.2043737
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