Our recent work focuses on Al research in the detection of metastatic cancer in tissue samples. Projects investigate multiscale detection algorithms to identify cancerous tissue in high resolution slide scans. Our solutions adopt neural network architectures to handle the broad variations in tumor sizes that occur across different medical imaging datasets.
We are also investigating methods for automatic detection of breast cancer biomarkers. This project is an ongoing collaboration with the UF College of Medicine Oncology and Pathology Departments (Shands Hospital.)
We present an algorithm for multi-scale tumor (chimeric cell) detection in high resolution slide scans. The broad range of tumor sizes in our dataset pose a challenge for current Convolutional Neural Networks (CNN) which often fail when image features are very small (8 pixels).