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A novel technique for contrast enhancement of chest x-ray images based on bio-inspired meta-heuristics
J MUKHERJEE, B SIKDAR, M KAR, S DAS,
Published in Springer Verlag
2018
Volume: 666
   
Pages: 71 - 93
Abstract
Chest radiography is considered as one of the most important radiological tools in pulmonary disease diagnosis. Due to the generation of low contrast images of X-ray machines, the detection of the lesions is a difficult issue and prone to error for a radiologist. Hence, a contrast enhancement algorithm is an obvious choice to enhance the contrast of the image, thus increasing the accuracy of detection of the lesions. This paper not only proposes a new algorithm for contrast enhancement of digital chest X-ray images using particle swarm optimization (PSO), but it also introduces a benchmark dataset of digital chest radiographs to justify the supremacy of our proposed algorithm over that of state-of-the-art contrast enhancement algorithms. © 2018, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Verlag
ISSN2194-5357