Towards robust identification and tracking of nevi in sparse photographic time series
Vogel J, Duliu A, Oyamada Y, Gardiazabal J, Lasser T, Ziai M, Hein R, Navab N (2014)
Publication Type: Conference contribution
Publication year: 2014
Journal
Publisher: SPIE
Book Volume: 9035
Conference Proceedings Title: Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Event location: USA
ISBN: 9780819498281
DOI: 10.1117/12.2043788
Abstract
In dermatology, photographic imagery is acquired in large volumes in order to monitor the progress of diseases, especially melanocytic skin cancers. For this purpose, overview (macro) images are taken of the region of interest and used as a reference map to re-localize highly magni ed images of individual lesions. The latter are then used for diagnosis. These pictures are acquired at irregular intervals under only partially constrained circumstances, where patient positions as well as camera positions are not reliable. In the presence of a large number of nevi, correct identi cation of the same nevus in a series of such images is thus a time consuming task with ample chances for error. This paper introduces a method for largely automatic and simultaneous identi cation of nevi in di erent images, thus allowing the tracking of a single nevus over time, as well as pattern evaluation. The method uses a rotation-invariant feature descriptor that uses the local neighborhood of a nevus to describe it. The texture, size and shape of the nevus are not used to describe it, as these can change over time, especially in the case of a malignancy. We then use the Random Walks framework to compute the correspondences based on the probabilities derived from comparing the feature vectors. Evaluation is performed on synthetic and patient data at the university clinic. © 2014 SPIE.
Involved external institutions
Germany (DE)How to cite
APA:
Vogel, J., Duliu, A., Oyamada, Y., Gardiazabal, J., Lasser, T., Ziai, M.,... Navab, N. (2014). Towards robust identification and tracking of nevi in sparse photographic time series. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. USA: SPIE.
MLA:
Vogel, Jakob, et al. "Towards robust identification and tracking of nevi in sparse photographic time series." Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, USA SPIE, 2014.
BibTeX: Download