ICARUS: Retrieving Skin Ulcer Images Through Bag-of-Signatures

Author(s)

Chino, Daniel Y. T. ; Scabora, Lucas C. ; Cazzolato, Mirela T. ; Jorge, Ana E. S. ; Traina, Caetano, Jr. ; Traina, Agma J. M. ; Hollmen, J ; McGregor, C ; Soda, P ; Kane, B

• Document type: Journal article
• Source: 2018 31ST IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS 2018); v. N/A, p. 6-pg., 2018-01-01.

Abstract

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. (AU)

• FAPESP's process: 14/25125-3 - Formalization and management of content-based information retrieval of complex objects with hierarchical and cross-modal data
• Grantee: Daniel Yoshinobu Takada Chino
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD)
• Grantee: Agma Juci Machado Traina
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 16/17330-1 - Storage and Navigation Operations on Graphs in Relational DBMS
• Grantee: Lucas de Carvalho Scabora
• Support Opportunities: Scholarships in Brazil - Doctorate