Tutorial 1 Generating training data with IMOD
This page provides instructions on how to generate training data using IMOD that can be used to train CDeep3M
- Use IMOD program to get information about SBEM image stack
- Generate a training dataset from training data using IMOD to train CDeep3M
A. Download the ZIP file entitled datasetone.zip from:
https://github.com/CRBS/cdeep3m/wiki/data/datasetone.zip
B. Unzip the contents to an easily accessible location:
- For Windows 7/8/10: Unzip the file into a new folder in your home directory. If you used the IMOD cygwin install, the home directory will be C:\Users\<username> (for windows 10 it may be C:\cygwin\home\<username>)
From the cygwin terminal this can be done with this command ($HOMEPATH is an environment variable in Windows set to the user's home directory):
cd ~
unzip $HOMEPATH/Downloads/datasetone.zip-
For Mac: Unzip the file into a new folder (e.g. /Users/<username>/datasetone).
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For Linux: Unzip the file into a new folder (e.g. /home/<username>/datasetone).
C. Open your terminal program
D. Navigate to the directory to which you unzipped the dataset, using the cd command in the terminal:
cd ~/datasetoneE. List the directory's contents using the ls command. you should see two files, sbem_train.mrc and sbem_model.mod
A. At the command line type:
header sbem_train.mrcand output like the following will be displayed:
- The program
headeris part of the IMOD software suite, and reads pertinent details from MRC files. Click here for a list of tools in IMOD
Step 3 Update IMOD model file for training labels
To save time a model file sbem_model.mod has been included in datasetone.zip and already has all mitochondria traced except for tile/slice 2
A. Open the training data stack in 3dmod by running the following command:
3dmod sbem_train.mrc
B. To save time open the existing model file sbem_model.mod by clicking File -> Open Model in 3dmod as seen in here:
Loaded model (mitochondria are outlined in green)
C. In this tutorial, we will be generating training data for mitochondria. Manually segment all instances of mitochondria in tile number 2 of your training data stack.
For more information on segmentation and model files click here.
A useful video illustrating the use of IMOD's Drawing tools can be found here
D. Be sure to save the model when done using the same name sbem_model.mod
Goal: generate a new MRC stack with same dimensions as the training images (we previously segmented)
All pixels inside of the traced contours value = 1,
All pixels outside of the traced contours value = 0.
Binary label stack will be created that will serve to tell the CDeep3M training algorithm where mitochondria are.
We will use the IMOD program imodmop to generate this stack.
A. Create the binary label stack using the following command:
imodmop -mask 1 sbem_model.mod sbem_train.mrc sbem_train_labels.mrc(To understance the meaning of these arguments and the imodmop syntax, view the imodmop man page in the terminal by typing man imodmop -- to exit the man page type q
B. Visuallize the label stack using 3dmod:
3dmod sbem_train_labels.mrc
Step 5 Generate training image and label PNGs
The CDeep3M training algorithm can take PNGs (or TIFs). Since PNG files are smaller we will convert from MRC to PNG.
A. First we need to make sub-directories under the train folder for images and labels
(The '-p' argument for mkdir will automatically create any missing parent directories):
mkdir -p train/images
mkdir train/labelsB. Next, convert the MRC stack of raw training images to individually numbered PNGs using the IMOD program mrc2tif. The '-p' forces conversion to PNG, rather then TIF and the 'x' at end is needed by mrc2tif as a filename prefix:
mrc2tif -p sbem_train.mrc train/images/xC. Convert the MRC stack of training labels to individually numbered PNGs using the IMOD program mrc2tif:
mrc2tif -p sbem_train_labels.mrc train/labels/x
Congratulations on completing Tutorial 1.
Click here to continue with Tutorial: 2 Launch and train CDeep3M