187 citations · 721 across the 60 of their papers we have counts for
40 papers · 1 filter
CenSynCMB: Centre Maps and Physics-Guided Synthesis for Microbleed Detection
Lucas He, Hanyuan Zhang, Krinos Li +7
Cerebral microbleeds (CMBs) are MRI markers of small vessel disease and the microbleed component of amyloid related imaging abnormalities (ARIA-H), but their small size, sparsity,…
A Unified Framework for Joint Detection of Lacunes and Enlarged Perivascular Spaces
Lucas He, Krinos Li, Hanyuan Zhang +7
Cerebral small vessel disease (CSVD) markers, specifically enlarged perivascular spaces (EPVS) and lacunae, present a unique challenge in medical image analysis due to their radiol…
rNCA: Self-Repairing Segmentation Masks
Malte Silbernagel, Albert Alonso, Jens Petersen +3
Accurately predicting topologically correct masks remains a difficult task for general segmentation models, which often produce fragmented or disconnected outputs. Fixing these art…
Leveraging Labelled Data Knowledge: A Cooperative Rectification Learning Network for Semi-supervised 3D Medical Image Segmentation
Yanyan Wang, Kechen Song, Yuyuan Liu +3
Semi-supervised 3D medical image segmentation aims to achieve accurate segmentation using few labelled data and numerous unlabelled data. The main challenge in the design of semi-s…
Leveraging point annotations in segmentation learning with boundary loss
Eva Breznik, Hoel Kervadec, Filip Malmberg +4
This paper investigates the combination of intensity-based distance maps with boundary loss for point-supervised semantic segmentation. By design the boundary loss imposes a strong…
Source Identification: A Self-Supervision Task for Dense Prediction
Shuai Chen, Subhradeep Kayal, Marleen de Bruijne
The paradigm of self-supervision focuses on representation learning from raw data without the need of labor-consuming annotations, which is the main bottleneck of current data-driv…