Speckle Noise Removal by SORAMA Segmentation in Digital Image Processing to Facilitate Precise Robotic Surgery

Roopa Jayasingh J., Jeba Kumar R. J. S., Deepika Blessy Telagathoti, K. Martin Sagayam, K. Martin Sagayam, Sabyasachi Pramanik, Om Prakash Jena and Samir Kumar Bandyopadhyay
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Roopa Jayasingh J.: Karunya Institute of Technology and Sciences, India
Jeba Kumar R. J. S.: Karunya Institute of Technology and Sciences, India
Deepika Blessy Telagathoti: Karunya Institute of Technology and Sciences, India
K. Martin Sagayam: Karunya Institute of Technology and Sciences, India
K. Martin Sagayam: Karunya Institute of Technology and Sciences, India
Sabyasachi Pramanik: Haldia Institute of Technology, India
Om Prakash Jena: Ravenshaw University, India
Samir Kumar Bandyopadhyay: The Bhawanipore Education Society, India

International Journal of Reliable and Quality E-Healthcare (IJRQEH), 2022, vol. 11, issue 1, 1-19

Abstract: Kidney stones are renal calculi that are formed due to the collection of calcium and uric acid. The major symptom for the existence of these renal calculi is severe pain, especially when it travels down the urethras To detect these renal calculi, ultrasound images are preferable. But these images have speckle noise which makes the detection of stone challenge. To obtain better results, Semantic Object Region and Morphological Analysis (SORAMA) found to be productive. First scanned image undergoes noise removal process Later the image is enhanced. Detection of Region of interest (ROI) in the image is done. Later it undergoes Dilation and Erosion were a part of Morphological analysis which produces a smoothening effect on the image. From the smoothened image, the stone is detected. If the stone is not detected then it again undergoes noise removal technique and the whole process is repeated until the smoothened image with the stone is detected. This novel research paper will be a boon to medical patients suffering from this disease to be detected and diagnose at a very early stage.

Date: 2022
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