This study presents a sharpening image enhancement technique based on the Laplacian pyramid (LP) and singular value decomposition (SVD) to improve the visibility and segmentation of subtle organs. The technique utilizes the shape-invariant properties of LP and the SVD techniques to enhance the perceptual sharpness of an image. The sharpening enhancement of magnetic resonance images not only sharpens the edges, but also reduces the noise effect. The results are compared with state-of-art enhancement techniques. The performance measures like peak-signal-to noise (PSNR), mean structural similarity index (MSSIM), and absolute mean brightness error (AMBE) evaluates the improved performance of the proposed technique. © 2017 Elsevier Ltd

Brintha Therese A

Electronics

School of Electronics Engineering

Chennai Campus

Jeevakala S

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Biomedical Signal Processing and Control

Sensorineural hearing loss is a hearing impairment which occurs when there is damage to the inner ear, or to the nerve pathways from the inner ear to the brain. Cochlear implants have been developed to benefit children with bilateral or unilateral Sensorineural hearing loss. A very small or absence of cochlear nerve precludes successful outcome of cochlear implant surgery. Hence, segmentation and measurement of the cochlear nerve support the surgeon's decision to predict a normal or poor outcome of the cochlear implant. For this purpose, a modified region growing segmentation algorithm is proposed that segments the cochlear nerve region accurately. The segmentation accuracy is evaluated using parameters like Jaccard, Dice, False Positive Dice, and False Negative Dice. The segmented region is measured and evaluated using long diameter, short diameter, and cross-sectional area. The statistical analyses of intra/inter-observer correlation and limits of agreement are performed on a cross-sectional area of the cochlear nerve to investigate the reproducibility of the automated measurement. © 2017 Elsevier Ltd

A novel segmentation of cochlear nerve using region growing algorithm

2016 24th Signal Processing and Communication Application Conference (SIU)

Medical image illumination enhancement and sharpening by using stationary wavelet transform

Journal of Medical and Biological Engineering

Automatic Contrast Enhancement of Brain MR Images Using Hierarchical Correlation Histogram Analysis

Signal Processing

Dual-tree complex wavelet transform and SVD based medical image resolution enhancement

2014 World Congress on Computing and Communication Technologies

Histogram Equalization for Image Enhancement Using MRI Brain Images

Sharpening enhancement technique for MR images to enhance the segmentation

Journal	Data powered by TypesetBiomedical Signal Processing and Control
Publisher	Data powered by TypesetElsevier BV
ISSN	1746-8094
Open Access	No