I’m a master’s student in modern human anatomy and I am teaching myself python to help with my capstone project. I’m still a novice and want some advice for what functions are best for what I want to quantify.
My project involves block face milling of whole brains. The industrial mill I am using unsurprisingly doesn’t have published feed and speed rates for neural tissue or the PVA I am using as a substrate. I took sample cuts a wide range of RPMs and feed rates and want to quantify the presence of cutting artifacts.
Here is a link to an imgur gallery with some samples photos so you can see what the photos are like.
You can visually see that the some of the photos have big arcing cutting artifacts, while the others without cut arcs have chaotic ice crystal formation.
I haven’t started my code yet, but I’m thinking that a Probabilistic Hough Transform would be useful to differentiate the long regular arcs from the short random ice crystals.
Is this the best function for what I am trying to accomplish? Ridge filters and contour finding also look like they could be useful for my goal.
Thank you for reading, and thank you for your advice.