collaborators

5 papers

cs.CV2026

SCALP: Semi-Supervised Statistical Shape Modeling from Imperfect 3D Photogrammetry via Landmark-Anchored Spectral Warp

Nawazish Khan, Sanjay Bhandari, Sarang Joshi +8

Correspondence-based statistical shape modeling (SSM) is vital for population-level morphometric analysis, but conventional pipelines assume clean, fully registered surfaces. Real-…

cs.CV2025

Domain-Shift Immunity in Deep Deformable Registration via Local Feature Representations

Mingzhen Shao, Sarang Joshi

Deep learning has advanced deformable image registration, surpassing traditional optimization-based methods in both accuracy and efficiency. However, learning-based models are wide…

eess.IV2025

Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPS

Seunghoi Kim, Henry F. J. Tregidgo, Matteo Figini +3

Hallucinations are spurious structures not present in the ground truth, posing a critical challenge in medical image reconstruction, especially for data-driven conditional models.…

cs.CV2025

MORPH-LER: Log-Euclidean Regularization for Population-Aware Image Registration

Mokshagna Sai Teja Karanam, Krithika Iyer, Sarang Joshi +1

Spatial transformations that capture population-level morphological statistics are critical for medical image analysis. Commonly used smoothness regularizers for image registration…

cs.CV2025

LEDA: Log-Euclidean Diffeomorphism Autoencoder for Efficient Statistical Analysis of Diffeomorphisms

Krithika Iyer, Shireen Elhabian, Sarang Joshi

Image registration is a core task in computational anatomy that establishes correspondences between images. Invertible deformable registration, which computes a deformation field a…