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Kidneys are a vital organ that is bean-shaped, about 12 centimeters (4.7 in) in length in the average human adult. They are located at the right and left in the retroperitoneal space. The kidney's primary function is to receive the blood from the paired renal arteries and purify it; later, the blood exits through paired veins. They also clean up the chemical waste, control and balance the pH of homeostasis fluids in the body. Finally, the waste removed from the blood is transformed into urine and is ejaculated. According to Tilahun Alelign and Beyene Petros's survey in 2018, kidney stone disease is an escalating urogenital disorder among various countries, impacting almost 15% of the global population. It is a common disorder, regardless of ages, sexes and races, but found to be more frequent in men than in women within 20-49 years. The study also says that it undergoes a prevalence of greater than 30% recurrence rate within ten years (Tanzila, Rahman and Shorif Uddin, 2013).
Renal calculi or kidney stones are hard solid particles or crystals that are deposits of acid salts and minerals that stick together in specific chemical concentrated enough in urine. The name nephrolithiasis also applies to these stones. The primary symptom for these renal calculi is severe pain, especially when it travels down the urethras, and this intense pain is called renal colic. Usually, this pain is experienced in one side, back or abdomen region. Therefore, it is essential to diagnose the problem at the initial stage, i.e. when the symptom starts appearing. There are various techniques available to detect kidney stone. In medical imaging practicalities, ultrasound is a therapeutic application as it is portable, versatile, and obsolete to radiations of ionizations and is relatively cost-effective and affordable. However, even though ultrasound is adaptable, comparatively safe and transferable, it has still much acoustic interference, i.e. speckle noise, a complex phenomenon. That decreases the ability to detect the targeted region or organ.
Moreover, these images are of low contrast and formed of the back-scattered wave due to diffused reflections. So, detection of nephrolithiasis in ultrasound images is a real-time challenge. Thus, to obtain specific and accurate results, noise (speckle) removal filtering is the foremost and crucial step that must be carried out. That will result in the removal of erroneous detection. Furthermore, preprocessing techniques are applied, and the image is segmented to delineate the boundaries of different tissues to characterize and differentiate between healthy (Pramanik et al., 2020) and weak tissues, followed by morphological analysis for automatic detection of renal calculi. There has been consequential and remarkable publicizing of robotic facilitate surgery in the province of upper tract oncology and urological pelvic. To accomplish the significant robotic-assisted surgery, the morphologically analyzed image is fed into the robot. It will recognize the exact location of the stone to carry out the procedure of surgery.
The effective speckle-noise reduction and segmentation process for nephrolithiasis identification for ultrasound images with less interference and decreased image perplex is proposed in this research paper. To combat speckle distortion or noise, the image is subjected to rigorous preprocessing processes, which results in a significant reduction in speckle noise and simplifies subsequent processing. For improved edge detection for irregular areas, image segmentation using the ROI model is used. Picture segmentation is followed by morphological regression to smooth out the image pixels. In addition, the position or coordination of the observed renal calculi is fed into the robot, making laparoscopic ureter-lithotomy easier. That has been discovered to be more effective than existing processes. This study will be combined with the robotic arm in the future for real-time deployment and observation.