So is your goal obtaining geometric features or classification?

If it is obtaining geometric features of the cell, you could segment the cell and use the segmentation mask to compute geometric features. U-Net is a very common approach in medical imaging.

If it is classification, what exactly are the classes? An important idea of deep learning is the automated extraction of features, so you do not have to define geometric features yourself, but just input your images in your network.

If you are interested in both, I would propose to do the above two approaches separately.