C-NMC Challenge

This is the code release for the paper:

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

Usage

Use the script main_manual.py to train the model on the dataset. The expected training data layout is described below.

Use the script submission.py to apply the trained model to the test data.

Data Layout

The training data during the challenge was released in multiple steps which is why the data layout is a little peculiar.

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

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:

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