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@@ -1,35 +1,10 @@
-# 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
+# Masterarbeit: Anomalie-Detektion in Zellbildern zur Anwendung der Leukaemieerkennung
 
-## Usage
+Dritter Platz der ISBI2019 (Supervised) mit Codeanpassungen bzw. Ergaenzungen.  
 
-Use the script `main_manual.py` to train the model on the dataset. The expected training data layout is described below.
+**Offizieller Release von Prellberg et al.:https://github.com/jprellberg/isbi2019cancer**  
 
-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
-```
+Zum trainieren und evaluieren von Modellen: run.ipynb  
+Bereits trainierte Modelle: ../results/
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