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Description
What would you like to see added to ROI Extractors?
I would like to introduce two separate traces with their respective spatial components:
_roi_response_neuropilwith the respective_neuropil_images_masks. This can be used to store the actual neuropil signals that sometimes refer to the area surrounding the ROIs._roi_response_backgroundwith the respective_background_images_masks. This can be used more generally to store the signal in the field of view that excludes the areas in the identified ROIs.
Right now we define the following:
roiextractors/src/roiextractors/segmentationextractor.py
Lines 34 to 47 in a6873d2
| def __init__(self): | |
| """Create a new SegmentationExtractor for a specific data format (unique to each child SegmentationExtractor).""" | |
| self._sampling_frequency = None | |
| self._times = None | |
| self._channel_names = ["OpticalChannel"] | |
| self._num_planes = 1 | |
| self._roi_response_raw = None | |
| self._roi_response_dff = None | |
| self._roi_response_neuropil = None | |
| self._roi_response_denoised = None | |
| self._roi_response_deconvolved = None | |
| self._image_correlation = None | |
| self._image_mean = None | |
| self._image_mask = None |
Maybe I would also add one for baseline (_roi_response_baseline) activity which spatial components are in common with the _roi_response_raw, _roi_response_denoised, _roi_response_deconvolved etc..
And _image_maximum_projection to store the maximum projection image that is also a very common summary image for segmentation algos.
@pauladkisson, @h-mayorquin, @weiglszonja @ehennestad what do you think?
Do you have any interest in helping implement the feature?
Yes.
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