An Improved Approach for Contrast Enhancement of Spinal Cord Images based on Multiscale Retinex Algorithm

TL;DR

This paper introduces a multiscale Retinex-based contrast enhancement method for spinal cord images that improves visual quality, detail visibility, and noise reduction, aiding medical diagnosis.

Contribution

It proposes a novel multirate scheme integrated with multiscale Retinex in HSV space, enhancing spinal cord images at multiple scales for better diagnostic clarity.

Findings

Enhanced edges and tissues in spinal cord images

Reduced Gaussian and Speckle noise effectively

Outperforms existing methods in visual quality

Abstract

This paper presents a new approach for contrast enhancement of spinal cord medical images based on multirate scheme incorporated into multiscale retinex algorithm. The proposed work here uses HSV color space, since HSV color space separates color details from intensity. The enhancement of medical image is achieved by down sampling the original image into five versions, namely, tiny, small, medium, fine, and normal scale. This is due to the fact that the each versions of the image when independently enhanced and reconstructed results in enormous improvement in the visual quality. Further, the contrast stretching and MultiScale Retinex (MSR) techniques are exploited in order to enhance each of the scaled version of the image. Finally, the enhanced image is obtained by combining each of these scales in an efficient way to obtain the composite enhanced image. The efficiency of the proposed algorithm is validated by using a wavelet energy metric in the wavelet domain. Reconstructed image using proposed method highlights the details (edges and tissues), reduces image noise (Gaussian and Speckle) and improves the overall contrast. The proposed algorithm also enhances sharp edges of the tissue surrounding the spinal cord regions which is useful for diagnosis of spinal cord lesions. Elaborated experiments are conducted on several medical images and results presented show that the enhanced medical pictures are of good quality and is found to be better compared with other researcher methods.