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+# Liver Tumors Segmentation-CNNs
+This project segments tumors in the Liver using 2 cascaded CNNs. We use [3D-IRCADb 01](https://www.ircad.fr/research/3d-ircadb-01/) as our dataset.
+View the [Thesis](https://drive.google.com/file/d/1UpkakPGMc2Cvtik6IEs9TqxjxvW4n9Up/view?usp=sharing) for more details about the model, dataset, methodology and results.
+
+
+There are 3 notebooks in this project
+
+* 3d-ircadb-01_util.ipynb
+Responsible for renaming files, merging masks and augmenting the dataset
+
+* liver_CNN.ipynb
+The first CNN, it uses a CNN to segment the Liver and extract the ROI
+
+* tumor_CNN_final.ipynb
+The second CNN, it segments the tumors using a CNN after masking other organs using the extracted ROI from the first CNN
+
+There is the models directories which contains the trained models
+* liver_model_final_resunet.h5 which is the first CNN trained for 20 epochs
+* tumor_weights_final_50epochs.h5	which is the second CNN trained for 50 epochs
+* tumor_weights_final_100epochs.h5 which is the second CNN trained for 100 epochs
+
+### Dependencies ###
+I used Anaconda for package management but pip will work all the same
+
+* Tensorflow-GPU
+* Keras (Tensorflow) already comes with Tensorflow
+* Numpy
+* OpenCV
+* Matplotlib
+* Pydicom
+* Jupyter Notebook
+* Scipy
+* Scikit-learn
+* PIL
+* Seaborn
+* Imageio
+
+### Dataset Structure ###
+The structure of the dataset should be as follows ( if you don't want to change the code :grinning: )
+```
+train
+|_ patients               # Contains all the CT-slices from all patients together with no directories inside
+|_ masks                  # Contains the masks for the Liver and Tumors for the patients
+   |_ merged_livertumors  # Contains the masks of tumors after merging each slice's tumor masks together
+   |_ 1.1_liver           # Contains the mask for the liver of each slice for patient 1
+   |_ 1.2_liver           # Contains the mask for the liver of each slice for patient 2
+   |_ 1.3_liver           # Contains the mask for the liver of each slice for patient 3
+      .
+      .
+      .
+   |_ 1.20_liver          # Contains the mask for the liver of each slice for patient 20
+```