We developed a deep learning based pipeline to segment the lumen boundary in IVUS datasets based on multiframes inputs.
We used SVMs to filter out false positive detections causes by single subject VBM when applied for discovering abnormalities in MRI scans.
Application of AI for medical imaging problems.
We applied CycleGANs to improve realism in ultrasound simulation based on ray-casting methods.
We explored and evaluated different feature extraction techniques in the context of IVUS segmentation.