Deepika Blessy Telagathoti
Papers
1
Total Citations
47
H-Index
1
About
Deepika Blessy Telagathoti is a researcher at the intersection of medical imaging, digital image processing, and robotic surgery, with a focused interest in improving diagnostic accuracy through computational techniques. Her most cited work, "Speckle Noise Removal by SORAMA Segmentation in Digital Image Processing to Facilitate Precise Robotic Surgery" (2022, 47 citations), addresses a critical challenge in ultrasound imaging for kidney stone detection. By developing a novel segmentation method that effectively removes speckle noise—a common artifact that obscures renal calculi in ultrasound images—Telagathoti’s research enhances the clarity and precision of diagnostic imaging. This contribution is particularly significant for robotic surgery, where accurate visualization of kidney stones is essential for minimally invasive procedures. Her work bridges the gap between image processing algorithms and clinical applications, offering a practical solution to improve surgical outcomes. With 47 citations on this paper alone, Telagathoti’s research demonstrates clear impact in the field of biomedical engineering. Her achievements highlight a commitment to translating computational methods into tangible benefits for patient care, making her a notable voice in the advancement of medical imaging and robotic-assisted surgery.
Research Focus
Key Achievements
Top Papers
- 1