2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS) (2018)
Jun 18, 2018 to Jun 21, 2018
The images collected during medical exams are a strong asset for diagnosing and decision making. One scenario where clinical images are especially useful is the analysis of chronic lesions on the skin (skin ulcers). The visual appearance of these wounds may provide meaningful clues that may help physicians in the diagnosis. In this context, we propose ICARUS, an image retrieval system for dermatological ulcer images based on Bag-of-Visual-Words of color and texture signatures. ICARUS analyzes the image and extracts only the relevant signatures. The results show that ICARUS achieves improvement of up to 7% in image retrieval precision whereas being up to 5 orders of magnitude faster when compared to the state-of-the-art methods. Our results showed that ICARUS is effective and fast, and successfully adds semantic to the image representation.
biomedical optical imaging, content-based retrieval, diseases, feature extraction, image classification, image colour analysis, image representation, image retrieval, image texture, medical image processing, skin
D. Y. Chino, L. C. Scabora, M. T. Cazzolato, A. E. Jorge, C. Traina and A. J. Traina, "ICARUS: Retrieving Skin Ulcer Images through Bag-of-Signatures," 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, Sweden, 2018, pp. 82-87.