Paper
9 March 2010 Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods
Oscar A. Debats, Nico Karssemeijer, Jelle O. Barentsz, Henkjan Huisman
Author Affiliations +
Abstract
Computer assisted detection (CAD) of lymph node metastases may help reduce reading time and improve interpretation of the large amount of image data in an MR-lymphography exam. We compared the influence of using different segmentation methods on the performance of a CAD system for classification of normal and metastasized lymph nodes. Our database consisted of T1 and T2*-weighted pelvic MR images of 603 lymph nodes, enhanced by USPIO contrast medium. For each lymph node, one seed point was manually defined Three automated segmentation methods were compared: 1. Confidence Connected segmentation, extended with automated Bandwidth Factor selection; 2. Conventional Graph Cut segmentation; 3. Pseudo-segmentation by selecting a sphere around the seed point. All lymph nodes were also manually segmented by a radiologist. The resulting segmentations were used to calculate 2 features (mean T1 and T2* signal intensity). Linear discriminant analysis was used for classification. The diagnostic accuracy (AUC at ROC-analysis) was: 0.95 (Confidence- Connected); 0.95 (Graph-Cut); 0.85 (spheres); and 0.95 (manual segmentations). The CAD performance of both the Confidence Connected and Graph Cut methods was as good as the manual segmentation. The substantially lower performance of the sphere segmentations demonstrates the need for accurate segmentations, even in USPIOenhanced images.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Oscar A. Debats, Nico Karssemeijer, Jelle O. Barentsz, and Henkjan Huisman "Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76240Q (9 March 2010); https://doi.org/10.1117/12.845640
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Lymphatic system

Magnetic resonance imaging

Optical spheres

Computer aided diagnosis and therapy

Tissues

CAD systems

Back to Top