3 papers
cs.AI2026
A Strong Linear Baseline for Whole-Heart Cardiac Shape Completion on CT, with an Open Eleven-Structure Statistical Shape Model
Matej Gazda, Jakub Gazda, Juraj Gazda +1
Public cardiac cohorts annotate different subsets of the heart, so shapes from separate sources cannot be pooled without shared correspondence. Among released cardiac shape resourc…
eess.IV2025
Large-scale modality-invariant foundation models for brain MRI analysis: Application to lesion segmentation
Petros Koutsouvelis, Matej Gazda, Leroy Volmer +5
The field of computer vision is undergoing a paradigm shift toward large-scale foundation model pre-training via self-supervised learning (SSL). Leveraging large volumes of unlabel…
eess.IV2021
Self-supervised deep convolutional neural network for chest X-ray classification
Matej Gazda, Jakub Gazda, Jan Plavka +1
Chest radiography is a relatively cheap, widely available medical procedure that conveys key information for making diagnostic decisions. Chest X-rays are almost always used in the…