Blob Detection

Considerations and Justifications for Choice We decided to experiment with different methods to explore alternatives not commonly mentioned in literature related to automated cell counting. As we are using yeast cells for our samples, their simple, near-circular cell shape would be suitable for blob detection as they can be identified according to their enclosed areas. […]

Synthetic Dataset

Considerations and Justifications for Choice When training the deep learning model (see Deep Learning (Multiclass Classification with CNN) for more information),  generating a synthetic dataset was helpful for increasing the size of the training and validation dataset to improve model performance. Subsequently, even after moving away from deep learning models — which meant a negation […]

Deep Learning (Multiclass Classification with CNN)

Considerations and Justifications for Choice After conducting preliminary research on common cell-counting models [1][2], we settled on experimenting with deep learning first. We decided to utilise a classification approach. By cropping the microscope images into multiple pieces, the range of cells in each piece would fall between 0 and 5 cells. The model would then […]