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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, Samir Kumar Bandyopadhyay

Source Title: International Journal of Reliable and Quality E-Healthcare (IJRQEH)11(1)

ISSN: 2160-9551|EISSN: 2160-956X|EISBN13: 9781683182573|DOI: 10.4018/IJRQEH.295083

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MLA

Roopa Jayasingh J., et al. "Speckle Noise Removal by SORAMA Segmentation in Digital Image Processing to Facilitate Precise Robotic Surgery." IJRQEH vol.11, no.1 2022: pp.1-19. http://doi.org/10.4018/IJRQEH.295083

APA

Roopa Jayasingh J., Jeba Kumar R. J. S., Telagathoti, D. B., Sagayam, K. M., Sagayam, K. M., Pramanik, S., Jena, O. P., & Bandyopadhyay, S. K. (2022). Speckle Noise Removal by SORAMA Segmentation in Digital Image Processing to Facilitate Precise Robotic Surgery. International Journal of Reliable and Quality E-Healthcare (IJRQEH), 11(1), 1-19. http://doi.org/10.4018/IJRQEH.295083

Chicago

Roopa Jayasingh J., et al. "Speckle Noise Removal by SORAMA Segmentation in Digital Image Processing to Facilitate Precise Robotic Surgery," International Journal of Reliable and Quality E-Healthcare (IJRQEH) 11, no.1: 1-19. http://doi.org/10.4018/IJRQEH.295083

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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.