X-ray Image Enhancement - A Technique Combination Approach

Abstract

Medical X-ray images are an important and valuable source of studies and diagnoses for diseases with low cost besides its high availability. However, radiological images are subject to degradations related to low contrast and presence of noise. Based on this finding, this article presents a simple but efficient enhancement method for these images with the objective of contrast gain and noise removal. The proposed method (MP) consists of a sequence of interactive steps. Start from the step of double precision conversion and end with removing impulsive noises. An evaluation with the PSNR, Entropy, AMBE, and IQR indicators was performed, besides gain check on the thresholding process and the histogram characterization. The evaluation was conducted on three different datasets in a total of 1409 images chest X-rays. The results compared to others known in the literature proved to be promising and put it as an interesting alternative in the process of enhancement medical X-ray images.

Publication
In Proceedings of IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI 2019)
Afonso Fonseca
Afonso Fonseca
PhD Student
and former (Co-advised) Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.

Cristiane Ferreira
Cristiane Ferreira
PhD Student

Fabrizzio Soares is bla bla bla.

William Ferreira
William Ferreira
(Co-advised) Ph.D Student

Fabrizzio Soares is bla bla bla.

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