The main objective of this project is to detect the stones in the kidney by using image processing techniques.
Ultrasound imaging is one of the available imaging techniques used for the diagnosis of kidney abnormalities. The detection of kidney stones using ultrasound imaging is a highly challenging task as they are of low contrast and contain speckle noise. This challenge is overcome by employing suitable image processing techniques. This paper presents a technique for the detection of kidney stones through different steps of image processing. The first step is image pre-processing. Image enhancement is a part of preprocessing which is used to enhance the image. Next, the image segmentation is performed on the preprocessed image using the thresholding technique. Finally, the segmented images are analyzed to detect the location of the stone.
Keywords: Ultrasound Imaging, Imaging Techniques, kidney stones, Image Processing.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Software Requirements:
MATLAB R2018a or above
Hardware Requirements:
Operating Systems:
• Windows 10
• Windows 7 Service Pack 1
• Windows Server 2019
• Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB