Publications (25)
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…
Reinforced Diffusion: Learning to Push the Limits of Anisotropic Diffusion for Image Denoising
Xinran Qin, Yuhui Quan, Ruotao Xu +1
Image denoising is an important problem in low-level vision and serves as a critical module for many image recovery tasks. Anisotropic diffusion is a wide family of image denoising…
DIETS: Diabetic Insulin Management System in Everyday Life
Hanyu Zeng, Hui Ji, Pengfei Zhou
People with diabetes need insulin delivery to effectively manage their blood glucose levels, especially after meals, because their bodies either do not produce enough insulin or ca…
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67
Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…
AHP-Net: adaptive-hyper-parameter deep learning based image reconstruction method for multilevel low-dose CT
Qiaoqiao Ding, Yuesong Nan, Hao Gao +1
Low-dose CT (LDCT) imaging is desirable in many clinical applications to reduce X-ray radiation dose to patients. Inspired by deep learning (DL), a recent promising direction of mo…
Convolutional Neural Network on Semi-Regular Triangulated Meshes and its Application to Brain Image Data
Caoqiang Liu, Hui Ji, Anqi Qiu
We developed a convolution neural network (CNN) on semi-regular triangulated meshes whose vertices have 6 neighbours. The key blocks of the proposed CNN, including convolution and…