PT-Finder: A multi-modal neural network approach to target identification
Efficient target identification for bioactive compounds, including novel synthetic analogs, is
crucial for accelerating the drug discovery pipeline. However, the process of target …
crucial for accelerating the drug discovery pipeline. However, the process of target …
OralEpitheliumDB: A dataset for oral epithelial dysplasia image segmentation and classification
Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the
most reliable way to prevent oral cancer. Computational algorithms have been used as an …
most reliable way to prevent oral cancer. Computational algorithms have been used as an …
[HTML][HTML] Bend-Net: bending loss regularized multitask learning network for nuclei segmentation in histopathology images
Separating overlapped nuclei is a significant challenge in histopathology image analysis.
Recently published approaches have achieved promising overall performance on nuclei …
Recently published approaches have achieved promising overall performance on nuclei …
An Improved U-Net Model for Simultaneous Nuclei Segmentation and Classification
T Liu, D Zhang, H Wang, X Qi - International Conference on Intelligent …, 2024 - Springer
Nuclei segmentation and classification of pathological images are the first steps in automatic
cancer prognosis and grading. Recent methods use the U-Net variant models to segment …
cancer prognosis and grading. Recent methods use the U-Net variant models to segment …