activity
20202026
most citedUsing Uncertainty in Deep Learning Reconstruction for Cone-Beam CT of the Brain

13 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Automated ACL Footprint Identification Using 3D Deep Learning

Ruida Cheng, Gabriel Gibson, Ali Uneri +2

One of the most common reasons for anterior cruciate ligament (ACL) reconstruction failure is femoral tunnel malpositioning (ACL footprint center and tunnel orientation). Such fail…

physics.med-ph2025★ 2 cited

Differentiable Forward and Back-Projector for Rigid Motion Estimation in X-ray Imaging

Xiao Jiang, Xin Wang, Ali Uneri +2

Objective: In this work, we propose a framework for differentiable forward and back-projector that enables scalable, accurate, and memory-efficient gradient computation for rigid m…

eess.IV2024★ 3 cited

RTA-Former: Reverse Transformer Attention for Polyp Segmentation

Zhikai Li, Murong Yi, Ali Uneri +2

Polyp segmentation is a key aspect of colorectal cancer prevention, enabling early detection and guiding subsequent treatments. Intelligent diagnostic tools, including deep learnin…

physics.med-ph2021★ 13 cited

Using Uncertainty in Deep Learning Reconstruction for Cone-Beam CT of the Brain

Pengwei Wu, Alejandro Sisniega, Ali Uneri +7

Contrast resolution beyond the limits of conventional cone-beam CT (CBCT) systems is essential to high-quality imaging of the brain. We present a deep learning reconstruction metho…

physics.med-ph2020★ 3 cited

C-Arm Non-Circular Orbits: Geometric Calibration, Image Quality, and Avoidance of Metal Artifacts

Pengwei Wu, Niral Sheth, Alejandro Sisniega +12

Metal artifacts present a frequent challenge to cone-beam CT (CBCT) in image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy. Recent advances in m…