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.
Thoracic lymph node stationing tool for chest CT using TotalSegmentator anatomy, bronchial branch parsing, and IASLC-style rule-based station segmentation.
Wizard diagnostico per quesito clinico: dispnea acuta & sospetta EP (D-dimero: 1.38)
Rule-based measurement of eight cardiovascular diameters from TotalSegmentator masks on non-ECG-gated contrast-enhanced chest CT
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