Research Lines
The lab's research focuses on machine learning and its applications. We are interested in the foundations of machine learning and how it is used to solve challenging problems.
Medical Image Analysis
Topics of interest:
- Topic 1:
Automatic search for patterns related with pathology signatures associated with healthy and abnormal tissues (Histopathology). - Topic 2:
Automatic evaluation of disease in Ophthalmic images.
Related Publications (Thesis):
| Type | Year | Author | Title |
|---|---|---|---|
| Master Thesis | 2020 | Juan Sebastián Lara Ramírez | Prostate histopathology image classification and retrieval using weakly-supervised multimodal fusion and representation learning |
| Master Thesis | 2020 | Andrés Daniel Pérez Pérez | A deep learning model to assess and enhance eye fundus image quality |
| Doctoral Thesis | 2020 | Oscar Julián Perdomo Charry | Deep learning analysis of eye fundus images to support medical diagnosis |
| Doctoral Thesis | 2015 | Andrés Mauricio Castillo Robles | Robust automatic assignment of nuclear magnetic resonance spectra for small molecules |
| Master Thesis | 2013 | John Edilson Arevalo Ovalle | Representation learning for histopathology image analysis |
| Master Thesis | 2011 | David Edmundo Romo Bucheli | Predicción de Patrones de Navegación en Mega-imágenes Histopatológicas |
| Master Thesis | 2011 | Angel Alfonso Cruz Roa | Anotación Automática de Imágenes Médicas Usando la Representación de Bolsa de Características |