Area of research
Radiology, Nuclear Medicine and Imaging · Computer Vision and Pattern Recognition
Research interest
Research focused on Artificial intelligence and Segmentation, with related work in Convolutional neural network, Benchmark (surveying), Context (archaeology). Notable publications include 'CellViT: Vision Transformers for precise cell segmentation and classification', 'Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology', and 'A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data'.
Beyond benchmarks: Towards robust artificial intelligence bone segmentation in socio-technical systems
CellViT: Vision Transformers for precise cell segmentation and classification
Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology
Is There a Role of Artificial Intelligence in Preclinical Imaging?
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data
Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism
Self-guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs
Prediction of Low-Kev Monochromatic Images From Polyenergetic CT Scans For Improved Automatic Detection of Pulmonary Embolism
Self-Guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs