medical imaging

Automated lumen segmentation using multi-frame convolutional neural networks in intravascular ultrasound datasets

We developed a deep learning based pipeline to segment the lumen boundary in IVUS datasets based on multiframes inputs.

Machine learning for filtering out false positive grey matter atrophies in single subject voxel based morphometry: A simulation based study

We used SVMs to filter out false positive detections causes by single subject VBM when applied for discovering abnormalities in MRI scans.

yatiris++: AI for clinical applications

Application of AI for medical imaging problems.

Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs

We applied CycleGANs to improve realism in ultrasound simulation based on ray-casting methods.

Assessment of image features for vessel wall segmentation in intravascular ultrasound images

We explored and evaluated different feature extraction techniques in the context of IVUS segmentation.