Efficient segmentation of ultrasound images of abnormal kidney

Author

Ismail, Haydar J.

Source

ZANCO Journal of Pure and Applied Sciences

Publisher

Salahaddin University-Erbil Department of Scientific Publications

Publication Date

2017-08-31

Country of Publication

Iraq

No. of Pages

6

Main Subjects

Physics

English Abstract

Image processing has large applications in the medical diagnosing, especially in Ultrasound Imaging (UI) that for its' safety.

UI suffer from low resolution and noises, so, became a target for a lot of investigations.

Three US images which represent Cyst, Benign, and Stone used in this study.

Five contrast enhancement techniques and three denoising filter applied on them and best of them chose according to their PSNR and MSE values.

It's found that best contrast enhancement methods were Contrast adjustment, for Benign and Cyst images, and sharpening for the Stone image.

Then, the images denoised by Median filtering due to found it as better denoising filter than others studied here.

Three segmenting methods (one ordinary and two hybrid techniques) were used here: thresholding, kmean with intensity selector, and bilateral filter with intensity selector.

All techniques were segmented nearly same area of the cases.

But thresholding needs a large of trial and error to obtain their segmenting.

The kmean with intensity selector method was found better for the Benign case than other for its higher PSNR (16.68), lower MSE (1394.1), and small time of running (22.1 sec).

But for Cyst and Stone images, Bilateral filter with intensity selector was found better than other according to same parameters.

So, techniques of hybrid segmentation provided more efficient segmenting.

Data Type

Conference Papers

Record ID

BIM-1389149

• APA
• MLA
• AMA