4 papers · 1 filter
GraphMAR: Geometry-Aware Graph Learning Framework for Spatially Adaptive CT Metal Artifact Reduction
Zilong Li, Chenglong Ma, Yiming Lei +7
Computed tomography (CT) metal artifact reduction (MAR) aims to reduce the severe streaking artifacts induced by metallic implants and other high-density objects. Effective MAR gen…
One CT Unified Model Training Framework to Rule All Scanning Protocols
Fengzhi Xu, Ziyuan Yang, Zexin Lu +4
Non-ideal measurement computed tomography (NICT), which lowers radiation at the cost of image quality, is expanding the clinical use of CT. Although unified models have shown promi…
FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising
Zhihao Chen, Qi Gao, Zilong Li +4
Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despite significant advancements drive…
Point, Segment and Count: A Generalized Framework for Object Counting
Zhizhong Huang, Mingliang Dai, Yi Zhang +2
Class-agnostic object counting aims to count all objects in an image with respect to example boxes or class names, \emph{a.k.a} few-shot and zero-shot counting. In this paper, we p…