Ultrasound is the first priority in kidney image processing. Many medical experts use this for initial screening of kidneys’ condition as it does not require any inflammation of body parts or instruments to be inserted into the body. High frequency sound waves are applied to produce recognized images. Ultrasound can be used to calculate the size and appearance of the kidneys, stones present in them, detect congenital abnormalities, swelling and blockage of urine flow. The completely automated and systematic algorithm is given to calibrate the kidney stones by proper analysis. The main theme of the detection is to find renal stones, mark the renal regions and to measure the space occupied by kidney stones. Sometimes the user usually finds difficulty in knowing the boundary of the kidney in the US image even though done by an expertise sonographer. In addition to this human error might also occur during acquisition of ultrasound image by untrained sonographer. So to reduce this distortion and noise, image processing techniques can be used. These techniques also detect the area of the human kidney and stones. US imaging can also be used to scan soft tissues and classify them accordingly find to possible diseases. This paper focuses on the literature review of classification of kidney images using ultrasound.

Medical Ultrasound, Medical Sonography, Morphological-Image Processing, Image Texture Analysis

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