Assessing deep learning models for multi-class upper endoscopic disease segmentation: A comprehensive comparative study

Figure 8 Representative examples of these challenging cases with predicted masks generated by the top-performing models. Light blue: Fully overlapping regions; Medium blue: Two-map overlaps; Dark blue: Single-map regions; Yellow (self-collected): Ground truth lesions; Pink: Barrett’s esophagus ground truth masks; Lime: Suspicious regions ground truth masks; Blue: High-grade dysplasia ground truth masks; Yellow (EDD2020): Cancer; HardA: Hard examples from self-collected dataset; HardB: Hard examples from EDD2020 dataset; GERD: Gastroesophageal reflux disease; DU: Duodenal ulcer; GN: Gastric neoplasm; EV: Esophageal varices; HGD: High-grade dysplasia; Sus: Suspicious precancerous lesions; BE: Barrett’s esophagus.