13 citations · 16 across the 5 of their papers we have counts for
5 papers
Tackling domain generalization for out-of-distribution endoscopic imaging
Mansoor Ali Teevno, Gilberto Ochoa-Ruiz, Sharib Ali
While recent advances in deep learning (DL) for surgical scene segmentation have yielded promising results on single-center and single-imaging modality data, these methods usually…
Domain Generalization for Endoscopic Image Segmentation by Disentangling Style-Content Information and SuperPixel Consistency
Mansoor Ali Teevno, Rafael Martinez-Garcia-Pena, Gilberto Ochoa-Ruiz +1
Frequent monitoring is necessary to stratify individuals based on their likelihood of developing gastrointestinal (GI) cancer precursors. In clinical practice, white-light imaging…
SUPRA: Superpixel Guided Loss for Improved Multi-modal Segmentation in Endoscopy
Rafael Martinez-Garcia-Peña, Mansoor Ali Teevno, Gilberto Ochoa-Ruiz +1
Domain shift is a well-known problem in the medical imaging community. In particular, for endoscopic image analysis where the data can have different modalities the performance of…
A semi-supervised Teacher-Student framework for surgical tool detection and localization
Mansoor Ali, Gilberto Ochoa-Ruiz, Sharib Ali
Surgical tool detection in minimally invasive surgery is an essential part of computer-assisted interventions. Current approaches are mostly based on supervised methods which requi…
Knowledge distillation with a class-aware loss for endoscopic disease detection
Pedro E. Chavarrias-Solanon, Mansoor Ali-Teevno, Gilberto Ochoa-Ruiz +1
Prevalence of gastrointestinal (GI) cancer is growing alarmingly every year leading to a substantial increase in the mortality rate. Endoscopic detection is providing crucial diagn…