research
∙
08/30/2023
A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models
Denoising diffusion models have found applications in image segmentation...
share
research
∙
08/22/2023
Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
We propose Boundary-RL, a novel weakly supervised segmentation method th...
research
∙
08/20/2023
Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction
Three-dimensional (3D) freehand ultrasound (US) reconstruction without u...
research
∙
03/10/2023
Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation
Recently, denoising diffusion probabilistic models (DDPM) have been appl...
research
∙
03/03/2023
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion
We propose an image synthesis mechanism for multi-sequence prostate MR i...
research
∙
02/24/2023
3D Generative Model Latent Disentanglement via Local Eigenprojection
Designing realistic digital humans is extremely complex. Most data-drive...
research
∙
12/03/2022
Active learning using adaptable task-based prioritisation
Supervised machine learning-based medical image computing applications n...
research
∙
11/09/2022
Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames
Three-dimensional (3D) freehand ultrasound (US) reconstruction without a...
research
∙
09/12/2022
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
The prowess that makes few-shot learning desirable in medical image anal...
research
∙
07/26/2022
Cross-Modality Image Registration using a Training-Time Privileged Third Modality
In this work, we consider the task of pairwise cross-modality image regi...
research
∙
07/21/2022
Strategising template-guided needle placement for MR-targeted prostate biopsy
Clinically significant prostate cancer has a better chance to be sampled...
research
∙
11/24/2021
3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces
Learning a disentangled, interpretable, and structured latent representa...
research
∙
10/12/2021
Voice-assisted Image Labelling for Endoscopic Ultrasound Classification using Neural Networks
Ultrasound imaging is a commonly used technology for visualising patient...
research
∙
03/25/2021
Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy
Super-resolution (SR) methods have seen significant advances thanks to t...
research
∙
01/29/2021
Gesture Recognition in Robotic Surgery: a Review
Objective: Surgical activity recognition is a fundamental step in comput...
research
∙
11/04/2020
DeepReg: a deep learning toolkit for medical image registration
DeepReg (https://github.com/DeepRegNet/DeepReg) is a community-supported...
research
∙
09/08/2020
Intraoperative Liver Surface Completion with Graph Convolutional VAE
In this work we propose a method based on geometric deep learning to pre...
research
∙
03/10/2020
Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction
Surgical gesture recognition is important for surgical data science and ...
research
∙
11/29/2019
Learning from Irregularly Sampled Data for Endomicroscopy Super-resolution: A Comparative Study of Sparse and Dense Approaches
Purpose: Probe-based Confocal Laser Endomicroscopy (pCLE) enables perfor...
research
∙
08/20/2019
More unlabelled data or label more data? A study on semi-supervised laparoscopic image segmentation
Improving a semi-supervised image segmentation task has the option of ad...
research
∙
07/05/2019
Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
In the medical domain, the lack of large training data sets and benchmar...
research
∙
02/09/2018
