Diagnosis of Esophageal Lesions by Multi-Classification and Segmentation Using an Improved Multi-Task Deep Learning Model. - Suigu Tang; Xiaoyuan Yu; Chak-Fong Cheang; Zeming Hu; Tong Fang; I. Cheong Choi; Hon Ho Yu (Sensors, 2022)

Multi-Task Model for Esophageal Lesion Analysis Using Endoscopic Images: Classification with Image Retrieval and Segmentation with Attention. - Xiaoyuan Yu; Suigu Tang; Chak-Fong Cheang; Hon Ho Yu; I. Cheong Choi (Sensors, 2022)

CLELNet: A continual learning network for esophageal lesion analysis on endoscopic images. - Suigu Tang; Xiaoyuan Yu; Chak-Fong Cheang; Xiaoyu Ji; Hon Ho Yu; I. Cheong Choi (Comput. Methods Programs Biomed., 2023)

Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images. - Suigu Tang; Xiaoyuan Yu; Chak-Fong Cheang; Yanyan Liang 001; Penghui Zhao; Hon Ho Yu; I. Cheong Choi (Comput. Biol. Medicine, 2023)

TransCS-Net: A hybrid transformer-based privacy-protecting network using compressed sensing for medical image segmentation. - Suigu Tang; Chak-Fong Cheang; Xiaoyuan Yu; Yanyan Liang 001; Qi Feng; Zongren Chen (Biomed. Signal Process. Control., 2023)

EDSDF: An Efficient Deep Supervised Distillation Framework for medical image segmentation. - Xuefang Chen; Zhining Li; Suigu Tang; Jiayao Li; Huazhu Liu; Jian Nong (Neurocomputing, 2025)