microscopy

Per SVK's suggestion, it is worth exploring if one can use an autoencoder (regular or variational) instead of PCA for the sliding-window-based image denoising originally written by @ramav87 .

@saimani5 @markpoxley will you be interested in exploring it?

When trying to read a LIF file without readlif installed, users are receiving this error:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/rex/anaconda3/envs/segmentation/lib/python3.7/site-packages/aicsimageio/aics_image.py", line 226, in __init__
    ReaderClass = self.determine_reader(image, **kwargs)
  File "/home/rex/anaconda3/envs/segmentat

Is your feature request related to a problem? Please describe.
In current version it is not possible to get just cell detection and cell analysis without cell classification. This could be potentially beneficial if you are analyzing cFos (nuclear) staining. With parameters that can be changed in cellfinder now I was able to get very good cFos detection results. When classification is done mor

As suggested by @jcohenadad, it would be helpful to display the units of every metric in the csv output.

e.g. something like this:

Detailed Description

Rightclicking a segment item in the "Segments" tab should expose a "Activate Segment ID" menu item which makes the selected segment id "active" (i.e., use setActiveCellAction).

Context

• Specific to long-running jobs (set jobsEnabled=true in application.conf)
• Specific to

Installing brainreg brings in 3.4GB of dependencies, as measured by my virtualenv folder's size. I see many things I don't think(?!) I need for a simple registration - e.g. ipython, jinja2, pyside2, sphinx, and napari. [I could be wrong here, of course.]

Might I suggest verifying what is needed, and perhaps having separate extras for some of this functionality? This could leave the core "pip

The semantic segmentation models need to be extended to work with 3D data. This should be very straightforward - just introduce an option to select between 1D, 2D, and 3D cases to ConvBlock, [UpsampleBlock](https://g