Uncertainty-Driven 3-D Gaussian Splatting for Robust Real-Time RGB-D SLAM
An uncertainty-aware 3D Gaussian Splatting framework for robust real-time RGB-D localization and mapping.
Sep 3, 2026
Contrastive Discrepancy: A label-free metric for deformable image registration supporting testing-time hyperparameter selection
A label-free Contrastive Discrepancy metric for evaluating deformable image registration and automatically selecting testing-time hyperparameters without manual annotations.
Sep 1, 2026
UniTransAD: Unified Translation Framework for Anomaly Detection in Brain MRI
A unified translation-based framework for flexible and generalizable unsupervised anomaly detection across diverse brain MRI diseases and sequences.
Jul 10, 2026
Contour-informed inter-patient deformable registration for more reliable voxel-based analysis of Head-and-Neck cancer patients
The integration of contour-informed regularization in CPT-DIR improved DIR accuracy, particularly in anatomically and dosimetrically relevant regions.
Jan 1, 2026
Comparative evaluation of static and dynamic 4D dose recalculations in pencil beam scanning proton therapy for oesophageal cancer
Protocol-based static 4DDC tended to overestimate target coverage robustness to respiratory motion. Although differences were minor in most cases, patients with large motion can have significant discrepancies, underscoring the importance of implementing dynamic 4DDC in PBS proton planning for esophageal cancer.
Jan 1, 2026
Continuous sPatial-Temporal Deformable Image Registration (CPT-DIR) for motion modelling in radiotherapy: beyond classic voxel-based methods
By leveraging the continuous representations, the CPT-DIR method enhances registration and interpolation accuracy, automation, and speed.
Dec 26, 2025
Enhancing Brain MRI Super-Resolution Through Multi-Slice Aware Matching and Fusion
A Multi-Slice Aware Matching and Fusion (MSAMF) network for brain MRI super-resolution that utilizes multi-slice reference images through multi-scale matching and fusion mechanisms to generate high-quality super-resolution images.
Oct 1, 2025
Gaussian Representation for Deformable Image Registration
This study presented an optimization-based DIR ap-proach that employed an explicit Gaussian representation to achieveefficient DVF estimation, strong generalization, and high interpretabil-ity.
Jul 9, 2025
A proof-of-concept study of direct magnetic resonance imaging-based proton dose calculation for brain tumors via neural networks with Monte Carlo-comparable accuracy
This study demonstrated the feasibility of MC-quality proton dose calculations directly from MR images for brain tumor patients, achieving comparable accuracy with faster computation and simplified implementation.
Jul 5, 2025
Uncertainty-Aware Testing-Time Optimization for 3D Human Pose Estimation
In this paper, we propose an Uncertainty-Aware testing-time Optimization (UAO) framework for 3D human pose estimation. During the training process, we propose the GUMLP to estimate 3D results and uncertainty values for each joint. For test-time optimization, our UAO framework freezes the pre-trained network parameters and optimizes a latent state initialized by the input 2D pose. To constrain the optimization direction in both 2D and 3D spaces, projection and uncertainty constraints are applied. Extensive experiments show that our approach achieves state-of-the-art performance on two popular datasets
Jun 15, 2025
MiLNet: Multiplex Interactive Learning Network for RGB-T Semantic Segmentation
A novel module-free Multiplex Interactive Learning Network (MiLNet) for RGB-T semantic segmentation that integrates multi-model, multi-modal, and multi-level feature learning through asymmetric simulated learning and inverse hierarchical fusion strategies.
Mar 3, 2025
Diffusion Schrödinger bridge models for high-quality MR-to-CT synthesis for proton treatment planning
A diffusion Schrödinger bridge model for high-quality MR-to-CT synthesis for proton treatment planning.
Jan 1, 2025
A Prior Causality‐Guided Multi‐View Diffusion Network for Brain Disorder Classification
A Prior Causality-Guided Multi-View Diffusion Network (PCMDN) for brain disorder classification that leverages prior causality knowledge and multi-view diffusion processes to improve classification accuracy.
Jan 1, 2025
HYRE: Hybrid Regressor for 3D Human Pose and Shape Estimation
A novel Hybrid Regressor (HYRE) that combines parametric and non-parametric paradigms for 3D human pose and shape estimation, bridging the gap between physically plausible and pixel-aligned results through joint learning.
Dec 25, 2024
Generating Synthetic Computed Tomography for Radiotherapy: SynthRAD2023 Challenge Report
SynthRAD2023 challenge report comparing synthetic CT generation methods for radiotherapy using multi-center data, evaluating both image similarity and dose-based metrics for MRI-to-CT and CBCT-to-CT tasks.
Oct 1, 2024
A Unified Generation-Registration Framework for Improved MR-based CT Synthesis in Proton Therapy
This study conclusively demonstrates that a holistic MR-based CT synthesis approach, integrating both image-to-image translation and deformable registration, significantly improves the precision and quality of sCT generation, particularly for the challenging body area with varied anatomic changes between corresponding MR and CT.
Aug 13, 2024
ModelNet-O: A large-scale synthetic dataset for occlusion-aware point cloud classification
A large-scale synthetic dataset ModelNet-O for occlusion-aware point cloud classification, featuring diverse occlusion patterns and complex object arrangements to evaluate model robustness under occlusion conditions.
Jun 19, 2024
Towards robust referring image segmentation
We propose a novel ranking loss function, named Bi-directional Exponential Angular Triplet Loss, to help learn an angularly separable common feature space by explicitly constraining the included angles between embedding vectors.
Mar 5, 2024
Towards open vocabulary learning: A survey
This survey offers a detailed examination of the latest developments in open vocabulary learning in computer vision, which appears to be a first of its kind. We provide an overview of the necessary background knowledge, which includes fundamental concepts and introductory knowledge of detection, segmentation, and vision language pre-training. Following that, we summarize more than 50 different models used for various scene understanding tasks. For each task, we categorize the methods based on their technical viewpoint. Additionally, we provide information regarding several closely related domains. In the experiment section, we provide a detailed description of the settings and compare results fairly. Finally, we summarize several challenges and also point out several future research directions for open vocabulary learning.
Feb 5, 2024
Uncertainty-aware MR-based CT synthesis for robust proton therapy planning of brain tumour
The enhanced framework incorporates 3D uncertainty prediction and generates high-quality sCTs from MR images. The framework also facilitates conditioned robust optimisation, bolstering proton plan robustness against network prediction errors. The innovative feature of uncertainty visualisation and robust analyses contribute to evaluating sCT clinical utility for individual patients.
Feb 1, 2024
Optimization induced equilibrium networks: An explicit optimization perspective for understanding equilibrium models
In this paper, we decompose the feed-forward DNN and find a more reasonable basic unit layer, which shows a close relationship with the proximal operator. Based on it, we propose new equilibrium models, OptEqs, and explore their underlying optimization problems thoroughly. We provide two strategies to introduce customized regularizations to the equilibrium points, and achieve significant performance improvement in experiments. We highlight that by modifying the underlying optimization problems, we can create more effective network architectures. Our work may inspire more interpretable equilibrium models from the optimization perspective.
Jun 10, 2022
Towards efficient scene understanding via squeeze reasoning
Jul 30, 2021