I apologize if this is somewhat repetitive. I am very, very new to image segmentation and do not have much background on machine learning. I posted a similar question here (Cell segmentation methods for time-series images?). However I am now analyzing time-series data that is not in video format, but rather individual images at different times.
I am measuring fluorescence for cells using time lapse images. For each sample, I have 50-100 cells. I currently manually select the ROIs (individual cells) using HCImage and measure the change in fluorescence. I generally have 50+ images that are 3 seconds apart for one sample. I select the majority of the ROIs in the time 0 seconds and time 3 seconds images and then scroll through the stack to select any ROI I didn’t notice before. The cells/ROIs do not move. However, the fluorescence of the cell/ROI does change during different times. I have attached images at time 0 seconds, time 3 seconds, time 6 seconds, and time 9 seconds as an example.
My question- Is there any program that would automatically select ROIs so I do not have to spend time manually examining the images at different times to select the ROI? I was recommended ImageJ, but I am not sure if I am able examine multiple images (50+ in one sample) in a reasonable amount of time. My cells are also clustered together in certain areas of the image (please see attached images). In addition, is it possible to train a sample and use the same parameters/instructions to select ROIs in other samples?
I am new to image segmentation and have no prior experience. Thank you for your help.
*Images removed at request of author.