Area of research
Radiology, Nuclear Medicine and Imaging · Artificial Intelligence
Research interest
Research focused on Artificial intelligence and Nodule (geology), with related work in Benchmark (surveying), Segmentation, Stereochemistry. Notable publications include 'Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT', 'Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT', and 'Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT'.
MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images
A light triggered optical and chiroptical switch based on a homochiral Eu<sub>2</sub>L<sub>3</sub> helicate
Eutypellacytosporins A–D, Meroterpenoids from the Arctic Fungus <i>Eutypella</i> sp. D-1
Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT
Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT
Transferable Multi-model Ensemble for Benign-Malignant Lung Nodule Classification on Chest CT