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JinghaoLu / MIN1PIPE

A MINiscope 1-photon-based Calcium Imaging Signal Extraction PIPEline.
GNU General Public License v3.0
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Seeds Classification #47

Open atombysx opened 3 years ago

atombysx commented 3 years ago

I’m currently running MIN1PIPE on Miniscope videos recorded in the VTA. As VTA is too deep, it has a smaller field of view and a bulb of light covering the centre of the video.

Hence, I used a 24 structural element size and it worked well.

However, when it comes to seeds classification, it identified many seeds for only a few overlapping neurons at the end. (See image attached)

I wonder if you have encountered this before. Is there a way to work around this?

My thoughts are to either train a new RNN for this setting or run CNMF again on the data_processed.m by roifn * sigfn.

Many thanks 0 2 percent processed signal diagrams

JinghaoLu commented 2 years ago

Hi sorry for the really late reply. To solve this problem, first an improved signal to noise ratio will certainly help. Second, I suggest you spatially downsample the video as much as possible so that you can use SE size within the range of [3,7]. The root of this issue, however, is still the low signal level within the FOV, so that the algorithm cannot tell the neurons from the background.