Elisha Lim
Papers
1
Total Citations
14
H-Index
1
About
Elisha Lim is a researcher at the forefront of integrating deep learning with medical imaging, particularly for spine surgery. Their work centers on developing and validating advanced computational methods to enhance the accuracy and efficiency of preoperative planning. Lim’s most-cited study, published in 2024, demonstrates that deep-learning-reconstructed lumbar spine 3D MRI can achieve performance comparable to CT for critical tasks like pedicle screw placement and geometric measurements. This contribution is significant because it offers a radiation-free alternative for surgical planning, directly impacting patient safety and clinical workflow. With 14 citations already, this paper signals growing recognition of Lim’s impact in the field. By bridging artificial intelligence and orthopedics, Elisha Lim is helping to redefine how spine surgeries are planned, making procedures safer and more precise. Their work is a compelling example of how interdisciplinary research can translate into tangible clinical benefits.
Research Focus
Key Achievements
Top Papers
- 1