Project DetailsThe target of this work is to dperformo automatic analysis to images from prof. Daphna Weihs lab's experiments.
It is already known that we can evaluate the probability of development of metastases of cancer cells by their penetration level on gel surface and this evaluation ability is essential to fit the best treatment to sick patients.
In this project we use only two images, the first is DIC a microscopic image of the cells and the second is surface that shows light of bids that are in the bottom of the gel. So, if we have a penetrating cell, we will see its region not in focus.
Our first task was to do automatic analysis of DIC images in order to find cells locations and count them. We managed this task by a method based on object detection and we reached good results even when the input is a low-quality image. Once we know the cell's locations, we check the relative blur level of those regions in surface images. Points that were detected as cells in DIC image and have high blur level in surface image, we classify as penetrating cell and if the blur level is low, we classify the cell as not penetrating cell.
We achieve relatively good results in this task.
