5 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…
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…
Computer-aided diagnosis in histopathological images of the endometrium using a convolutional neural network and attention mechanisms
Hao Sun, Xianxu Zeng, Tao Xu +2
Uterine cancer, also known as endometrial cancer, can seriously affect the female reproductive organs, and histopathological image analysis is the gold standard for diagnosing endo…
Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue
Yutao Ma, Tao Xu, Xiaolei Huang +10
Objective: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge fo…