452 citations · 477 across the 8 of their papers we have counts for
9 papers
AG-Fusion: adaptive gated multimodal fusion for 3d object detection in complex scenes
Sixian Liu, Chen Xu, Qiang Wang +2
Multimodal camera-LiDAR fusion technology has found extensive application in 3D object detection, demonstrating encouraging performance. However, existing methods exhibit significa…
Semi-weakly-supervised neural network training for medical image registration
Yiwen Li, Yunguan Fu, Iani J. M. B. Gayo +11
For training registration networks, weak supervision from segmented corresponding regions-of-interest (ROIs) have been proven effective for (a) supplementing unsupervised methods,…
A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models
Yunguan Fu, Yiwen Li, Shaheer U Saeed +2
Denoising diffusion models have found applications in image segmentation by generating segmented masks conditioned on images. Existing studies predominantly focus on adjusting mode…
Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation
Yunguan Fu, Yiwen Li, Shaheer U. Saeed +2
Recently, denoising diffusion probabilistic models (DDPM) have been applied to image segmentation by generating segmentation masks conditioned on images, while the applications wer…
MONAI: An open-source framework for deep learning in healthcare
M. Jorge Cardoso, Wenqi Li, Richard Brown +53
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagn…
Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration
Yiwen Li, Yunguan Fu, Iani Gayo +12
The prowess that makes few-shot learning desirable in medical image analysis is the efficient use of the support image data, which are labelled to classify or segment new classes,…
Few-shot image segmentation for cross-institution male pelvic organs using registration-assisted prototypical learning
Yiwen Li, Yunguan Fu, Qianye Yang +6
The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class a…
Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes
Yiwen Li, Gratianus Wesley Putra Data, Yunguan Fu +2
Despite the success of deep learning methods for semantic segmentation, few-shot semantic segmentation remains a challenging task due to the limited training data and the generalis…
GroSS: Group-Size Series Decomposition for Grouped Architecture Search
Henry Howard-Jenkins, Yiwen Li, Victor A. Prisacariu
We present a novel approach which is able to explore the configuration of grouped convolutions within neural networks. Group-size Series (GroSS) decomposition is a mathematical for…