Augmentation strategy for mantis data #23

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1. ziw-liu commented on Jul 28, 2023

   

   ziw-liu

   on Jul 28, 2023

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   This is related to #16 but more specific to mantis data.
2. ziw-liu commented on Jul 28, 2023

   

   ziw-liu

   on Jul 28, 2023

   Last edited by ziw-liu

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   For this scaling range and a 5-slice output, the input stack needs to be 11-slice.

   import torch
   import matplotlib.pyplot as plt
   from monai.transforms import RandAffine
   
   # C, Z, Y, X
   x = torch.ones((1, 11, 12, 3))
   
   t = RandAffine(
       prob=1,
       rotate_range=(3.14, 0, 0),
       shear_range=(0, (0.05), (0.05)),
       scale_range=((-0.2, 1.4), 0.3, 0.3),
       padding_mode="zeros",
       mode="trilinear",
   )
   
   f, ax = plt.subplots(1, 10, figsize=(20, 4), sharey=True)
   
   for i in range(10):
       y = t(x)
       ax[i].imshow(y[0].numpy())
   
   plt.tight_layout()

   

   Figure: Z-Y projection of output of random affine transform, white pixels are resampled solely from in-grid data (not from padding).

   Z-only:
   

   This augmentation will use more I/O bandwidth (2x).
3. mattersoflight commented on Jul 30, 2023

   

   mattersoflight

   on Jul 30, 2023

   Last edited by mattersoflight

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   @ziw-liu thanks for starting this discussion on axial spatial augmentation.

   We will also investigate the unit of voxel intensity values in the reconstructed phase images, since mantis has a different illumination wavelength (450 nm) than hummingbird (532 nm).

   Examining the XY and XZ cross sections of the phase and fluorescence volumes from both microscopes will be very informative. I look forward to that data.

   For this scaling range and a 5-slice output, the input stack needs to be 11-slice.

   I don't see images in your last comment, so I ran the snippet above, and see this:
   

   It does make sense that we read more z-slices to make sure that we don't have boundary artifacts.

   Some other comments:

   • The training data acquired on hummingbird and test data from mantis has sufficient spatial resolution and sampling in z to capture the shape and texture of nuclei and membrane. In other words, 205nm, 250nm, and 570nm are all sufficient sampling intervals to resolve nuclei and cell contours. 570nm sampling is likely insufficient for the membrane.
   • We will collect a lot of data on membrane with mantis.
4. mattersoflight commented on Aug 12, 2023

   

   mattersoflight

   on Aug 12, 2023

   Last edited by mattersoflight

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   The solution to this issue is in progress.

   #27 and #29 were merged into the main to make it easy to install viscy from the main during the DL@MBL course.

   @ziw-liu can you elaborate on #28? Should it be merged while testing the 2D UNet?
5. ziw-liu commented on Aug 12, 2023

   

   ziw-liu

   on Aug 12, 2023

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   @ziw-liu can you elaborate on #28? Should it be merged while testing the 2D UNet?

   Yes, that PR has 2 bug fixes.
6. ziw-liu

   closed this as completedon Apr 8, 2024