Recognition of Protruding Objects in Highly Structured Surroundings by Structural Inference
Recognition of objects in highly structured surroundings is a challenging task, because the appearance of target objects changes due to fluctuations in their surroundings. This makes the problem highly context dependent. Due to the lack of knowledge about the target class, we also encounter a difficulty delimiting the non-target class. Hence, objects can neither be recognized by their similarity to prototypes of the target class, nor by their similarity to the non-target class. We solve this problem by introducing a transformation that will eliminate the objects from the structured surroundings. Now, the dissimilarity between an object and its surrounding (non-target class) is inferred from the difference between the local image before and after transformation. This forms the basis of the detection and classification of polyps in computed tomography colonography. 95% of the polyps are detected at the expense of four false positives per scan.
KeywordsFeature Space Compute Tomography Colonography Dissimilarity Measure Candidate Object Virtual Colonoscopy
- 3.van Wijk, C., van Ravesteijn, V.F., Vos, F.M., Truyen, R., de Vries, A.H., Stoker, J., van Vliet, L.J.: Detection of protrusions in curved folded surfaces applied to automated polyp detection in CT colonography. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 471–478. Springer, Heidelberg (2006)CrossRefGoogle Scholar
- 5.Winawer, S., Fletcher, R., Rex, D., Bond, J., Burt, R., Ferrucci, J., Ganiats, T., Levin, T., Woolf, S., Johnson, D., Kirk, L., Litin, S., Simmang, C.: Colorectal cancer screening and surveillance: Clinical guidelines and rationale – update based on new evidence. Gastroenterology 124, 544–560 (2003)CrossRefGoogle Scholar
- 6.van Wijk, C., van Ravesteijn, V.F., Vos, F.M., van Vliet, L.J.: Detection and segmentation of protruding regions on folded iso-surfaces for the detection of colonic polyps (submitted)Google Scholar
- 8.Pekalska, E., Duin, R.P.W.: Learning with general proximity measures. In: Proc. PRIS 2006, pp. IS15–IS24 (2006)Google Scholar
- 12.van Ravesteijn, V.F., van Wijk, C., Truyen, R., Peters, J.F., Vos, F.M., van Vliet, L.J.: Computer aided detection of polyps in CT colonography: An application of logistic regression in medical imaging (submitted) Google Scholar