Automated lung segmentation in CT
[MICCAI 2019 Young Scientist Award] [MedIA Best Paper Award] Models Genesis: self-supervised pre-training for 3D medical images. Learns transferable representations from unlabeled CT and MRI volumes, then fine-tunes for downstream segmentation and classification. Keras and PyTorch weights included.
COVID-Net Open Source Initiative - Models and Data for COVID-19 Detection in Chest CT
Image-based COVID-19 diagnosis. Links to software, data, and other resources.
AirQuant is a framework based in MATLAB primarily for extracting airway measurements from fully segmented airways of a chest CT.
This repository contains the code for registration of Chest CT done with inspiratory and expiratory breath-hold CT image pairs. The dataset used is COPDGene dataset. The dataset has landmarks for all the inhale-exhale image pairs which are used to calculate the registration error.
Workflow-centred open-source fully automated lung volumetry in chest CT.
Labelless automated airway measurement using style transfer to generate synthetic data.
Rule-based measurement of eight cardiovascular diameters from TotalSegmentator masks on non-ECG-gated contrast-enhanced chest CT
Wizard diagnostico per quesito clinico: dispnea acuta & sospetta EP (D-dimero: 1.38)
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