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Proceedings Paper

Definition and automatic anatomy recognition of lymph node zones in the pelvis on CT images
Author(s): Yu Liu; Jayaram K. Udupa; Dewey Odhner; Yubing Tong; Shuxu Guo; Rosemary Attor; Danica Reinicke; Drew A. Torigian
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Paper Abstract

Currently, unlike IALSC-defined thoracic lymph node zones, no explicitly provided definitions for lymph nodes in other body regions are available. Yet, definitions are critical for standardizing the recognition, delineation, quantification, and reporting of lymphadenopathy in other body regions. Continuing from our previous work in the thorax, this paper proposes a standardized definition of the grouping of pelvic lymph nodes into 10 zones. We subsequently employ our earlier Automatic Anatomy Recognition (AAR) framework designed for body-wide organ modeling, recognition, and delineation to actually implement these zonal definitions where the zones are treated as anatomic objects. First, all 10 zones and key anatomic organs used as anchors are manually delineated under expert supervision for constructing fuzzy anatomy models of the assembly of organs together with the zones. Then, optimal hierarchical arrangement of these objects is constructed for the purpose of achieving the best zonal recognition. For actual localization of the objects, two strategies are used — optimal thresholded search for organs and one-shot method for the zones where the known relationship of the zones to key organs is exploited. Based on 50 computed tomography (CT) image data sets for the pelvic body region and an equal division into training and test subsets, automatic zonal localization within 1–3 voxels is achieved.

Paper Details

Date Published: 29 March 2016
PDF: 6 pages
Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97881J (29 March 2016); doi: 10.1117/12.2217672
Show Author Affiliations
Yu Liu, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Jilin Univ. (China)
Jayaram K. Udupa, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Dewey Odhner, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Yubing Tong, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Shuxu Guo, Jilin Univ. (China)
Rosemary Attor, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Danica Reinicke, Medical Image Processing Group, Univ. of Pennsylvania (United States)
Drew A. Torigian, Medical Image Processing Group, Univ. of Pennsylvania (United States)


Published in SPIE Proceedings Vol. 9788:
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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