Conclusion
This technology could be widely applied to perform unbiased quantification of the structural effect of the cardiotoxins on heart slices.
Methods
In our deep learning pipeline, we quantify the induced structural deterioration from three anticancer drugs (doxorubicin, sunitinib, and herceptin) with known adverse cardiac effects. The proposed deep learning framework is composed of three convolutional neural networks that process three different image sizes. The
Purpose
Drug induced cardiac toxicity is a disruption of the functionality of cardiomyocytes which is highly correlated to the organization of the subcellular structures. We can analyze cellular structures by utilizing microscopy imaging data. However, conventional image analysis
Results
The result of our technique is the capability of producing classification maps that accurately detect drug induced structural deterioration on the pixel level.