Title:
Semi-Automatic Lymph Node Segmentation in LN-MRI
Semi-Automatic Lymph Node Segmentation in LN-MRI
Author(s)
Unal, Gozde
Slabaugh, Gregory G.
Ess, Andreas
Yezzi, Anthony
Tong, Fang
Tyan, Jason
Requardt, Martin
Krieg, Robert
Seethamraju, Ravi T.
Harisinghani, Mukesh
Weissleder, Ralph
Slabaugh, Gregory G.
Ess, Andreas
Yezzi, Anthony
Tong, Fang
Tyan, Jason
Requardt, Martin
Krieg, Robert
Seethamraju, Ravi T.
Harisinghani, Mukesh
Weissleder, Ralph
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Abstract
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
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Date Issued
2006-10
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Text
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Proceedings