Medical Imaging | José Ignacio Orlando

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.

Paulo GP Ziemer, Carlos a Bulant, José Ignacio Orlando, Gonzalo D Maso Talou, Luis a Mansilla Álvarez, Cristiano Guedes Bezerra, Pedro a Lemos, Héctor M García-García, Pablo J Blanco

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.

Hernán C. Külsgaard, José Ignacio Orlando, Mariana Bendersky, Juan P. Princich, Luis S. R. Manzanera, Alberto Vargas, Silvia Kochen, Ignacio Larrabide

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.

Santiago Vitale, José Ignacio Orlando, Emmanuel Iarussi, Ignacio Larrabide

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.

Lucas Lo Vercio, José Ignacio Orlando, Mariana Del Fresno, Ignacio Larrabide