Suma Suma
Papers
1
Total Citations
4
H-Index
1
About
Suma Suma is a researcher whose work sits at the intersection of medical imaging, computational modeling, and data compression. Her primary research focus is on developing efficient image coding techniques, particularly through region-of-interest (ROI) based medical image compression. Her most cited paper, "Computational Modelling of Image Coding using ROI based Medical Image Compression" (2014), addresses a critical challenge in modern healthcare: the need to transmit high-quality medical images in real-time over constrained bandwidth, especially for robotic-guided surgeries and telemedicine. This work has garnered 4 citations, reflecting its foundational role in exploring how selective compression can preserve diagnostic quality while reducing data load. Suma’s contributions are especially relevant to the growing fields of digital medical imaging and remote surgical robotics, where efficient data transmission is paramount. By investigating the trade-offs between compression ratios and image fidelity, she has helped pave the way for more practical, bandwidth-aware medical imaging systems. Her research offers valuable insights for students and engineers working on image processing, telemedicine, and real-time robotic communication.
Research Focus
Key Achievements
Top Papers
- 1