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Dr. Gilberto Ochoa-Ruiz
Tecnologico de Monterrey
Guadalajara, Mexico

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Dr. Gilberto Ochoa-Ruiz

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Research Projects

He is currently involved in the following projects related with medical Imaging and digital pathology, win which we are interested in developing new image medical analysis and processing methods, but also machine learning models to facilitate the diagnosis of various diseases. We are also actively exploring the development of interpretability and explainability tools for deep learning models.

Robust Surgical Tool Segmentation, Tracking and Depth Perception

In collaboration with Dr. Sharib Ali, from the University of Leeds (United Kingdom)

Goal: To develop new datasets, schemes and models for implement robust and real-time computer vision methods for Computer Integrated Surgery (CIS) applications and procedural quality assessment purposes

RECONDITE: Deep learning and image analysis methods for improving the endoscopic identification of kidney stones composition

In collaboration with Prof. Christian Daul the Centre de Recherche en Automatique de Nancy, CRAN (France) and the Institut National de la Santé et de la Recherche Medicale (INSERM)

Goal: To investigate deep learning algorithms for automatically classifying in vivo kidney stones from endoscopy images

PROTEUS: Endoscopic 3D View Enhancement and Automatic Categorization of Gastro-Intestinal Inflammations from Endoscopic data

In collaboration with Prof. Christian Daul theCentre de Recherche en Automatique de Nancy, CRAN and the Hopital Ambroise-Paré (Paris)

Goal: Real-time 3D organ reconstruction from epithelial surfaces, such as those found in the esophagus, stomach and colon. To explore DL-based SLAM for obtaining fine-grained organ atlas for cancer diagnosis and to combine it with methods for automatically categorizing lesions or pre-cancerous areas from endoscopic procedures

ISOLATE: SegmentatIon and claSsification Of vascuLar pATtern symmEtries on cerebral vessels using DL

In collaboration with Dr. Christian Mata Miquel and Prof. Enrique Benitez from the Biomedical Engineering Research Center (CREB, Barcelona) of the Universitat Politecnica de Catalunya (Spain) and the Hospital Sant Joan de Deu (Barcelona)

Goal: To develop novel CADx tools for aiding physicians in the diagnosis of CP. Various algorithms for vessel segmentation and skeletonization have been explored and tested. The results of these preprocessing methods are to be used for classifying vascular pattern asymmetries

Watch: Wildfire Analysis Through Computer vision tecHniques

A collaborative project for early wildfire dentification and fire widespread forecasting. A collaboration with several Mexican universities and the Universitá di Corsica (France) with Prof. Lucile Rossi from Laboratoire Sciences Pour l’Environnement and the GOLIATi team

Goal: To investigate novel drone-IoT model for detecting, monitoring and spread forecasting of fires using computer vision

MEANING MEtric And maNIfold learNinG

A collaboration with CINVESTAV Guadalajara with Prof. Andres Mendez Vazquez group.

Goal: To investigate novel methods for deep metric learning, and related areas such as few-shot learning (FSL), OOD generalization, neural network dissection and explainability.

Collaborators