Development of Algorithms for Automated Detection of Cervical Pre-Cancers With a Low-Cost, Point-of-Care, Pocket Colposcope.

Journal Article (Journal Article)

GOAL: In this paper, we propose methods for (1) automatic feature extraction and classification for acetic acid and Lugol's iodine cervigrams and (2) methods for combining features/diagnosis of different contrasts in cervigrams for improved performance. METHODS: We developed algorithms to pre-process pathology-labeled cervigrams and extract simple but powerful color and textural-based features. The features were used to train a support vector machine model to classify cervigrams based on corresponding pathology for visual inspection with acetic acid, visual inspection with Lugol's iodine, and a combination of the two contrasts. RESULTS: The proposed framework achieved a sensitivity, specificity, and accuracy of 81.3%, 78.6%, and 80.0%, respectively, when used to distinguish cervical intraepithelial neoplasia (CIN+) relative to normal and benign tissues. This is superior to the average values achieved by three expert physicians on the same data set for discriminating normal/benign cases from CIN+ (77% sensitivity, 51% specificity, and 63% accuracy). CONCLUSION: The results suggest that utilizing simple color- and textural-based features from visual inspection with acetic acid and visual inspection with Lugol's iodine images may provide unbiased automation of cervigrams. SIGNIFICANCE: This would enable automated, expert-level diagnosis of cervical pre-cancer at the point of care.

Full Text

Duke Authors

Cited Authors

  • Asiedu, MN; Simhal, A; Chaudhary, U; Mueller, JL; Lam, CT; Schmitt, JW; Venegas, G; Sapiro, G; Ramanujam, N

Published Date

  • August 2019

Published In

Volume / Issue

  • 66 / 8

Start / End Page

  • 2306 - 2318

PubMed ID

  • 30575526

Pubmed Central ID

  • PMC6581620

Electronic International Standard Serial Number (EISSN)

  • 1558-2531

Digital Object Identifier (DOI)

  • 10.1109/TBME.2018.2887208


  • eng

Conference Location

  • United States