4 papers
Intelligent Pathological Diagnosis of Gestational Trophoblastic Diseases via Visual-Language Deep Learning Model
Yuhang Liu, Yueyang Cang, Wenge Que +12
The pathological diagnosis of gestational trophoblastic disease(GTD) takes a long time, relies heavily on the experience of pathologists, and the consistency of initial diagnosis i…
RetCompletion:High-Speed Inference Image Completion with Retentive Network
Yueyang Cang, Pingge Hu, Xiaoteng Zhang +3
Time cost is a major challenge in achieving high-quality pluralistic image completion. Recently, the Retentive Network (RetNet) in natural language processing offers a novel approa…
Segmentation Network with Compound Loss Function for Hydatidiform Mole Hydrops Lesion Recognition
Chengze Zhu, Pingge Hu, Xianxu Zeng +3
Pathological morphology diagnosis is the standard diagnosis method of hydatidiform mole. As a disease with malignant potential, the hydatidiform mole section of hydrops lesions is…
A Semantic Segmentation Network Based Real-Time Computer-Aided Diagnosis System for Hydatidiform Mole Hydrops Lesion Recognition in Microscopic View
Chengze Zhu, Pingge Hu, Xianxu Zeng +3
As a disease with malignant potential, hydatidiform mole (HM) is one of the most common gestational trophoblastic diseases. For pathologists, the HM section of hydrops lesions is a…