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Proceedings Paper

Automatic detection of pelvic lymph nodes using multiple MR sequences
Author(s): Michelle Yan; Yue Lu; Renzhi Lu; Martin Requardt; Thomas Moeller; Satoru Takahashi; Jelle Barentsz
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Paper Abstract

A system for automatic detection of pelvic lymph nodes is developed by incorporating complementary information extracted from multiple MR sequences. A single MR sequence lacks sufficient diagnostic information for lymph node localization and staging. Correct diagnosis often requires input from multiple complementary sequences which makes manual detection of lymph nodes very labor intensive. Small lymph nodes are often missed even by highly-trained radiologists. The proposed system is aimed at assisting radiologists in finding lymph nodes faster and more accurately. To the best of our knowledge, this is the first such system reported in the literature. A 3-dimensional (3D) MR angiography (MRA) image is employed for extracting blood vessels that serve as a guide in searching for pelvic lymph nodes. Segmentation, shape and location analysis of potential lymph nodes are then performed using a high resolution 3D T1-weighted VIBE (T1-vibe) MR sequence acquired by Siemens 3T scanner. An optional contrast-agent enhanced MR image, such as post ferumoxtran-10 T2*-weighted MEDIC sequence, can also be incorporated to further improve detection accuracy of malignant nodes. The system outputs a list of potential lymph node locations that are overlaid onto the corresponding MR sequences and presents them to users with associated confidence levels as well as their sizes and lengths in each axis. Preliminary studies demonstrates the feasibility of automatic lymph node detection and scenarios in which this system may be used to assist radiologists in diagnosis and reporting.

Paper Details

Date Published: 29 March 2007
PDF: 10 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65140W (29 March 2007); doi: 10.1117/12.709909
Show Author Affiliations
Michelle Yan, Siemens Corp. Research (United States)
Yue Lu, Univ. of Illinois at Urbana-Champaign (United States)
Renzhi Lu, Rensselaer Polytechnic Institute (United States)
Martin Requardt, Siemens Medical AG (Germany)
Thomas Moeller, Siemens Corp. Research (United States)
Satoru Takahashi, Radboud Univ. Medical Ctr. (Netherlands)
Jelle Barentsz, Radboud Univ. Medical Ctr. (Netherlands)


Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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