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- # C-NMC Challenge
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- This is the code release for the paper:
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- Prellberg J., Kramer O. (2019) Acute Lymphoblastic Leukemia Classification from Microscopic Images Using Convolutional Neural Networks. In: Gupta A., Gupta R. (eds) ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging. Lecture Notes in Bioengineering. Springer, Singapore
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- ## Usage
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- Use the script `main_manual.py` to train the model on the dataset. The expected training data layout is described below.
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- Use the script `submission.py` to apply the trained model to the test data.
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- ## Data Layout
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- The training data during the challenge was released in multiple steps which is why the data layout is a little peculiar.
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- ```
- data/fold_0/all/*.bmp
- data/fold_0/hem/*.bmp
- data/fold_1/...
- data/fold_2/...
- data/phase2/*.bmp
- data/phase3/*.bmp
- data/phase2.csv
- ```
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- The `fold_0` to `fold_2` folders contain the training images with two subdirectories for the two classes each. The directories `phase2` and `phase3` are the preliminary test-set and test-set respectively and contain images numbered starting from `1.bmp`. The labels for the preliminary test-set are specified in `phase2.csv` which looks as follows:
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- ```
- Patient_ID,new_names,labels
- UID_57_29_1_all.bmp,1.bmp,1
- UID_57_22_2_all.bmp,2.bmp,1
- UID_57_31_3_all.bmp,3.bmp,1
- UID_H49_35_1_hem.bmp,4.bmp,0
- ```
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