Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

International Research and Innovation Summit 2017

Kairuddin, Wan Nur Hafsha Wan^1 ; Mahmud, Wan Mahani Hafizah Wan^1

Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia^1

关键词: Different resolutions;    Gray level co-occurance matrixes;    Gray level run length;    Image feature extractions;    Intensity histograms;    Inverse differences;    Tissue characteristics;    Ultrasound machines;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/226/1/012136/pdf
DOI  :  10.1088/1757-899X/226/1/012136

来源: IOP

【 摘 要 】

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.