AI enabled cancer cell detection
Cell inspection in pathological examinations
During cancer screening, specimens are obtained through biopsy or liquid biopsy, and can contain cells shed from the tumor or DNA related to the tumor. Doctors determine whether cells are normal or unhealthy based on their unique characteristics, and refer to the degree of cytopathy to determine prognosis and subsequent treatment.
Biopsy images and cell variations
Analyzing cell characteristics can distinguish cancer cells from normal cells and also classify cancer cells. However, under microscopic images cancer cells vary in appearance and are randomly located, which could drastically affect a doctor’s judgment or selection criteria. In light of these uncertainties, traditional inspection systems are insufficient for detecting and determining cell variations.
Classifying cells with AI deep learning
Using SolVision’s Classification tool, the AI model can be trained to recognize the different features of normal cells and cancer cells. The system’s data augmentation tool enables simulation of potential cell types and variations to strengthen training and stability of the AI model. The advanced AI model can then be used to identify and classify cells accurately for doctors to make better prognosis.