172 citations · 212 across the 5 of their papers we have counts for
5 papers
Multi-Scale Structural-aware Exposure Correction for Endoscopic Imaging
Axel Garcia-Vega, Ricardo Espinosa, Luis Ramirez-Guzman +5
Endoscopy is the most widely used imaging technique for the diagnosis of cancerous lesions in hollow organs. However, endoscopic images are often affected by illumination artefacts…
A Novel Hybrid Endoscopic Dataset for Evaluating Machine Learning-based Photometric Image Enhancement Models
Axel Garcia-Vega, Ricardo Espinosa, Gilberto Ochoa-Ruiz +4
Endoscopy is the most widely used medical technique for cancer and polyp detection inside hollow organs. However, images acquired by an endoscope are frequently affected by illumin…
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Sharib Ali, Noha Ghatwary, Debesh Jha +29
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and charac…
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Sharib Ali, Mariia Dmitrieva, Noha Ghatwary +34
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy…
Endoscopy disease detection challenge 2020
Sharib Ali, Noha Ghatwary, Barbara Braden +7
Whilst many technologies are built around endoscopy, there is a need to have a comprehensive dataset collected from multiple centers to address the generalization issues with most…