A DBMS-Based Framework for Content-Based Retrieval and Analysis of Skin Ulcer Images in Medical Practice

  • Mirela T. Cazzolato USP
  • Lucas S. Rodrigues USP
  • Lucas C. Scabora USP
  • Guilherme F. Zaboti USP
  • Guilherme Q. Vasconcelos USP
  • Daniel Y. T. Chino USP
  • Ana E. S. Jorge UFSCar
  • Robson L. F. Cordeiro USP
  • Caetano Traina-Jr USP
  • Agma J. M. Traina USP


Bedridden patients with skin lesions (ulcers) often do not have access to specialized clinic equipment. It is important to allow healthcare practitioners to use their smartphones to leverage information regarding the proper treatment to be carried. Existing applications require special equipment, such as heat sensors, or focus only on general information. To fulfill this gap, we propose ULEARn, a DBMS-based framework for the processing of ulcer images, providing tools to store and retrieve similar images of past cases. The proposed mobile application ULEARn-App allows healthcare practitioners to send a photo from a patient to ULEARn, and obtain a timely feedback that allows the improvement of procedures on therapeutic interventions. Experimental results of ULEARn and ULEARn-App using a real-world dataset showed that our tool can quickly respond to the required analysis and retrieval tasks, being up to 4.6 times faster than the specialist’ expected execution time.

Palavras-chave: A DBMS-Based Framework, Image Content-Based Retrieval, mobile application, image retrieval tasks, image retrieval analysis


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CAZZOLATO, Mirela T. et al. A DBMS-Based Framework for Content-Based Retrieval and Analysis of Skin Ulcer Images in Medical Practice. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 34. , 2019, Fortaleza. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 109-120. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2019.8812.