Area of research
Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Artificial intelligence, Convolutional neural network, Benchmark (surveying), Segmentation, and Monochromatic color.
AutoPET Challenge on Fully Automated Lesion Segmentation in Oncologic PET/CT Imaging, Part 2: Domain Generalization
Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series
Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy
Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging
Vi<sup>2</sup>CLR: Video and Image for Visual Contrastive Learning of Representation
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
Classification-Driven Dynamic Image Enhancement
MovieQA: Understanding Stories in Movies through Question-Answering