Search Results for author:
Found 5 papers, 4 papers with code
On Transferability of Histological Tissue Labels in Computational Pathology
Deep learning tools in computational pathology, unlike natural vision tasks, face with limited histological tissue labels for classification.
HistoKT: Cross Knowledge Transfer in Computational Pathology
In this paper, we take a data-centric approach to the transfer learning problem and examine the existence of generalizable knowledge between histopathological datasets.
Probeable DARTS with Application to Computational Pathology
AI technology has made remarkable achievements in computational pathology (CPath), especially with the help of deep neural networks.
Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligence
The emergence of digital pathology has opened new horizons for histopathology and cytology.
Focus Quality Assessment of High-Throughput Whole Slide Imaging in Digital Pathology
We also extend our method to generate a local slide-level focus quality heatmap, which can be used for automated slide quality control, and demonstrate the utility of our method for clinical scan quality control by comparison with subjective slide quality scores.
