Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

P. Lodhia

View on Semantic Scholar

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Open access Oct 2026

EP3.9 A Novel Classification of Cam Morphology in Femoroacetabular Impingement

Abstract Background Cam morphology is prevalent in many athletes, and is a risk factor for hip pain and osteoarthritis. However, a standardized classification system for the various types of bony morphology has yet to be established. A robust classification system should reproducibly group similar morphologies to guide...

Akash Chopra, P. Lodhia, Mark McConkey · 0 citations
Review Open access Oct 2026

TP4.1 Comparable accuracy of three-dimensional reconstruction of MRI and CT in the evaluation of femoroacetabular morphology: a systematic review

3D MRI compared to 3D CT was accurate in evaluating acetabulum and proximal femur osseous anatomy and Techniques for constructing 3D MRI models varied greatly and were more time consuming than 3D CT in the majority of studies.

Helen Crofts, Eric T. Piatt, T. Chae et al. · 0 citations
Open access Oct 2026

EP4.12 MRI Versus CT-Based Three-Dimensional Reconstruction for Quantifying Cam Morphology with Alpha and Omega Angles

Abstract Background Cam morphology of the proximal femur is three-dimensional (3D), yet it is commonly summarized using single-plane alpha-angle measurements. Omega angle is an angle that quantifies the circumferential arc of cam deformity around the femoral head–neck junction. 3D Magnetic Resonance Imaging (MRI) may a...

P. Lodhia, M. Alfalasi, Shazly Sheha et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.