Search Results for author:
Found 15 papers, 6 papers with code
Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge
The segmentation of pelvic fracture fragments in CT and X-ray images is crucial for trauma diagnosis, surgical planning, and intraoperative guidance.
Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge
Furthermore, no open-source dataset is currently available to support the development of multi-class aortic segmentation methods.
Mammo-Clustering:A Weakly Supervised Multi-view Global-Local Context Clustering Network for Detection and Classification in Mammography
Our model shows potential in reducing the burden on doctors and increasing the feasibility of breast cancer screening for women in underdeveloped regions.
Three-Dimensional Medical Image Fusion with Deformable Cross-Attention
Furthermore, the prevailing methodologies are largely confined to fusing two-dimensional (2D) medical image slices, leading to a lack of contextual supervision in the fusion images and subsequently, a decreased information yield for physicians relative to three-dimensional (3D) images.
QUIZ: An Arbitrary Volumetric Point Matching Method for Medical Image Registration
Rigid pre-registration involving local-global matching or other large deformation scenarios is crucial.
Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains
In this paper, we propose an unsupervised MAR method based on the diffusion model, a generative model with a high capacity to represent data distributions.
INR-LDDMM: Fluid-based Medical Image Registration Integrating Implicit Neural Representation and Large Deformation Diffeomorphic Metric Mapping
Moreover, we adopt a coarse-to-fine approach to address the challenge of deformable-based registration methods dropping into local optimal solutions, thus aiding the management of significant deformations in medical image registration.
XTransCT: Ultra-Fast Volumetric CT Reconstruction using Two Orthogonal X-Ray Projections for Image-guided Radiation Therapy via a Transformer Network
Computed tomography (CT) scans offer a detailed, three-dimensional representation of patients' internal organs.
Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising
The results demonstrate that our method outperforms the state-of-the-art unsupervised method and surpasses several supervised deep learning-based methods.
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images
Deformable image registration is a necessary technique for fusing multi-modal pathology slices.
TransCT: Dual-path Transformer for Low Dose Computed Tomography
Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radiation to patients.
Elastic Net based Feature Ranking and Selection
After features are sorted according to their frequency, linear support vector machine performs the classification in an incremental manner.
CT Super Resolution via Zero Shot Learning
We incorporated the CT domain knowledge into the SADIR and unrolled it into a DL network (SADIR Net).
A Matlab Toolbox for Feature Importance Ranking
Moreover, the toolbox is evaluated on a database of 163 ultrasound images.
Atlas Based Segmentations via Semi-Supervised Diffeomorphic Registrations
Whereas supervised segmentation methods only automate the segmentation process for a select few number of OARs, we demonstrate that our methods can achieve similar performance for OARs of interest, while also providing segmentations for every other OAR on the provided atlas.
