 |
    |
Manifold Diffusion for Exophytic Kidney Lesion Detection on Non-contrast CT Images
Jianfei Liu1, Shijun Wang1, Jianhua Yao1, Marius George Linguraru2, and Ronald M. Summers1
1Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Science, National Institutes of Health Clinical Center, Bethesda, MD 20892, USA
2Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Medical Center, Washington, DC 20010, USA
Abstract. Kidney lesions are important extracolonic findings at computed tomographic colonography (CTC). However, kidney lesion detection on non-contrast CTC images poses significant challenges due to low image contrast with surrounding tissues. In this paper, we treat the kidney surface as manifolds in Riemannian space and present an intrinsic manifold diffusion approach to identify lesion-caused protrusion while simultaneously removing geometrical noise on the manifolds. Exophytic lesions (those that deform the kidney surface) are detected by searching for surface points with local maximum diffusion response and using the normalized cut algorithm to extract them. Moreover, multi-scale diffusion response is a discriminative feature descriptor for the subsequent classification to reduce false positives. We validated the proposed method and compared it with a baseline method using shape index on CTC datasets from 49 patients. Free-response receiver operating characteristic analysis showed that at 7 false positives, the proposed method achieved 87% sensitivity while the baseline method achieved only 22% sensitivity. The proposed method showed far fewer false positives compared with the baseline method which makes it feasible for clinical practice.
Keywords: Kidney lesion detection, computed tomographic colonography, manifold diffusion, extracolonic finding, Riemannian manifold
LNCS 8149, p. 340 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2013