Automated Detection and Categorization of Genital Injuries Using Digital Colposcopy

• Type: Article in International Conference Proceedings Book
• Date: 2017

Authors

Fernandes, K (Author) Other; Jaime S Cardoso (Author) FEUP; Astrup, BS (Author) Other

Conference proceedings International

Title: PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2017)

Pages: 251-258

8th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Univ Algarve, Faro, PORTUGAL, JUN 20-23, 2017

Indexing

ISI Web of Knowledge - 6 Citations

Scopus - 2 Citations

Other information

Authenticus ID: P-00N-9XS

DOI: 10.1007/978-3-319-58838-4_28

Abstract (EN): Despite the existence of patterns able to discriminate between consensual and non-consensual intercourse, the relevance of genital lesions in the corroboration of a legal rape complaint is currently under debate in many countries. The testimony of the physicians when assessing these lesions has been questioned in court due to several factors (e.g. a lack of comprehensive knowledge of lesions, wide spectrum of background area, among others). Thereby, it is relevant to provide automated tools to support the decision process in an objective manner. In this work, we compare traditional handcrafted features and deep learning techniques in the automated processing of colposcopic images for genital injury detection. Positive results where achieved by both paradigms in segmentation and classification subtasks, being traditional and deep models the best strategy for each subtask type respectively.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8