An efficient hybrid approach for medical images enhancement
Saroj, Sushil Kumar (Madan Mohan Malaviya University of Technology)
Kumar, Rakesh (Madan Mohan Malaviya University of Technology)
Singh, Nagendra Pratap (National Institute of Technology)

Date:	2022
Abstract:	Medical images have various critical usages in the field of medical science and healthcare engineering. These images contain information about many severe diseases. Health professionals identify various diseases by observing the medical images. Quality of medical images directly affects the accuracy of detection and diagnosis of various diseases. Therefore, quality of images must be as good as possible. Different approaches are existing today for enhancement of medical images, but quality of images is not good. In this literature, we have proposed a novel approach that uses principal component analysis (PCA), multi-scale switching morphological operator (MSMO) and contrast limited adaptive histogram equalization (CLAHE) methods in a unique sequence for this purpose. We have conducted exhaustive experiments on large number of images of various modalities such as MRI, ultrasound, and retina. Obtained results demonstrate that quality of medical images processed by proposed approach has significantly improved and better than other existing methods of this field.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Medical image ; Image enhancement ; MSMO ; SNR ; CNR
Published in:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, Vol. 21 Núm. 2 (2022) , p. 62-76 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1574
DOI: 10.5565/rev/elcvia.1574

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