DOI
10.9781/ijimai.2022.12.002
Abstract
Enhancing the visibility of medical images is part of the initial or preprocessing phase within a computer vision system. This image preparation is essential for subsequent system tasks such as segmentation or classification. Therefore, quantitative validation of medical image preprocessing is crucial. In this work, four metrics are studied: Contrast Improvement Index (CII), Enhancement Measurement Estimation (EME), Entropy EME (EMEE), and Entropy. The objective is to find the best parameters for each metric. The study is performed on five medical image datasets, three retinal fundus sets (DRIVE, ROPFI, HRF-POORQ), and two mammography image sets (MIAS, DDSM). Metrics are calculated using a binary mask image to discard the background.
Source Publication
International Journal of Interactive Multimedia and Artificial Intelligence
Recommended Citation
Intriago-Pazmiño, Monserrate; Ibarra-Fiallo, Julio; Guzmán-Castillo, Adán; Alonso-Calvo, Raúl; and Crespo, José
(2023)
"Quantitative Measures for Medical Fundus and Mammography Images Enhancement,"
International Journal of Interactive Multimedia and Artificial Intelligence: Vol. 8:
Iss.
4, Article 16.
DOI: 10.9781/ijimai.2022.12.002
Available at:
https://ijimai.researchcommons.org/ijimai/vol8/iss4/16
