Ajay K. Pandey

About

Ajay K. Pandey is a leading researcher at the intersection of robotics, medical imaging, and orthopaedic surgery, with a primary focus on advancing robotic knee arthroscopy. His work centers on integrating deep learning, ultrasound imaging, and dexterous robotic systems to overcome the limitations of minimally invasive surgery. Pandey’s major contributions include pioneering the automatic segmentation of femoral cartilage from ultrasound images using deep learning architectures like Mask R-CNN and Bayesian CNNs—critical for real-time surgical guidance. His highly cited papers, such as “Ultrasound guidance in minimally invasive robotic procedures” (69 citations) and “Deep Learning-Based Femoral Cartilage Automatic Segmentation in Ultrasound Imaging for Guidance in Robotic Knee Arthroscopy” (47 citations), demonstrate his impact in enabling safer, more precise arthroscopic procedures. He has also explored surgeon attitudes toward robotic adoption, bespoke snake-like surgical robots (e.g., the RAVEN II), and even organic optoelectronic tactile sensors for soft-touch applications. With over 350 total citations across his top works, Pandey’s research is shaping the future of image-guided, robot-assisted orthopaedic surgery—making him a key figure for students and researchers interested in surgical robotics and AI-driven medical technologies.

Research Focus

Key Achievements

Top Papers

1. 1
   Ultrasound guidance in minimally invasive robotic procedures

   69 citations · 2019
2. 2
   Deep Learning-Based Femoral Cartilage Automatic Segmentation in Ultrasound Imaging for Guidance in Robotic Knee Arthroscopy

   47 citations · 2019
3. 3
   Orthopaedic surgeon attitudes towards current limitations and the potential for robotic and technological innovation in arthroscopic surgery

   47 citations · 2017
4. 4
   Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning

   41 citations · 2020
5. 5
   Segmentation of Femoral Cartilage from Knee Ultrasound Images Using Mask R-CNN

   36 citations · 2019
6. 6
   Supervised Scene Illumination Control in Stereo Arthroscopes for Robot Assisted Minimally Invasive Surgery

   28 citations · 2020
7. 7
   Robotic and Image-Guided Knee Arthroscopy

   27 citations · 2019
8. 8
   Organic Optoelectronic Diodes as Tactile Sensors for Soft-Touch Applications

   25 citations · 2019
9. 9
   End-to-End Design of Bespoke, Dexterous Snake-Like Surgical Robots: A Case Study With the RAVEN II

   25 citations · 2022
10. 10
    Bayesian CNN for Segmentation Uncertainty Inference on 4D Ultrasound Images of the Femoral Cartilage for Guidance in Robotic Knee Arthroscopy

    20 citations · 2020

Key Collaborators

Contact & Links