Semi-Automatic Lymph Node Segmentation in LN-MRI

Accurate staging of nodal cancer still relies on surgical exploration because many primary malignancies spread via lymphatic dissemination. The purpose of this study was to utilize nanoparticle-enhanced lymphotropic magnetic resonance imaging (LN-MRI) to explore semi-automated noninvasive nodal cancer staging. We present a joint image segmentation and registration approach, which makes use of the problem specific information to increase the robustness of the algorithm to noise and weak contrast often observed in medical imaging applications. The effectiveness of the approach is demonstrated with a given lymph node segmentation problem in post-contrast pelvic MRI sequences.

• Type: Conference
• Year: 2006
• Where: ICIP
• Authors: Gozde B. Unal, Gregory G. Slabaugh, Andreas Ess, Anthony J. Yezzi, Tong Fang, Jason Tyan, Martin Requardt, Robert Krieg, Ravi T. Seethamraju, Mukesh Harisinghani, Ralph Weissleder
• Keywords: ICIP 2006, Image Processing, Joint Image Segmentation, Magnetic Resonance Imaging, Nodal Cancer Staging, Node Segmentation Problem, Pelvic Mri Sequences