Brain MRI Tumor Classification Deep Learning Model
Brain MRI Tumor Classification Deep Learning Model
Brain MRI Tumor Classification Deep Learning Model
Brain MRI Tumor Classification Deep Learning Model
Deep Learning
Machine Learning
Python
This is a deep learning model that can classify MRI images of the brain into four categories: glioma tumor, meningioma tumor, pituitary tumor and no tumor. The model was trained on the Images Dataset "Brain Tumor Classification (MRI)" From Kaggle by SARTAJ under the CC0: Public Domain License. In addition to the model, I have also provided a graphical user interface (GUI) that allows users to upload an MRI image and get a prediction from the model. The GUI was built using the Tkinter library in Python.
The model is a convolutional neural network (CNN) with the following architecture:
Layer (type) Output Shape Param #
=================================================================
conv2d (Conv2D) (None, 1248, 1248, 32) 896
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 624, 624, 32) 0
_________________________________________________________________
conv2d_1 (Conv2D) (None, 622, 622, 64) 18496
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 311, 311, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 309, 309, 128) 73856
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 154, 154, 128) 0
_________________________________________________________________
flatten (Flatten) (None, 307328) 0
_________________________________________________________________
dense (Dense) (None, 128) 39338112
_________________________________________________________________
dropout (Dropout) (None, 128) 0
_________________________________________________________________
dense_1 (Dense) (None, 4) 516
=================================================================
Total params: 39,436,876
Trainable params: 39,436,876
Non-trainable params: 0More information:
GitHub Repository
Hugging Face Repository
Detailed Medium Article
Deep Learning
Machine Learning
Python
This is a deep learning model that can classify MRI images of the brain into four categories: glioma tumor, meningioma tumor, pituitary tumor and no tumor. The model was trained on the Images Dataset "Brain Tumor Classification (MRI)" From Kaggle by SARTAJ under the CC0: Public Domain License. In addition to the model, I have also provided a graphical user interface (GUI) that allows users to upload an MRI image and get a prediction from the model. The GUI was built using the Tkinter library in Python.
The model is a convolutional neural network (CNN) with the following architecture:
Layer (type) Output Shape Param #
=================================================================
conv2d (Conv2D) (None, 1248, 1248, 32) 896
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 624, 624, 32) 0
_________________________________________________________________
conv2d_1 (Conv2D) (None, 622, 622, 64) 18496
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 311, 311, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 309, 309, 128) 73856
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 154, 154, 128) 0
_________________________________________________________________
flatten (Flatten) (None, 307328) 0
_________________________________________________________________
dense (Dense) (None, 128) 39338112
_________________________________________________________________
dropout (Dropout) (None, 128) 0
_________________________________________________________________
dense_1 (Dense) (None, 4) 516
=================================================================
Total params: 39,436,876
Trainable params: 39,436,876
Non-trainable params: 0More information:
GitHub Repository
Hugging Face Repository
Detailed Medium Article
Deep Learning
Machine Learning
Python
This is a deep learning model that can classify MRI images of the brain into four categories: glioma tumor, meningioma tumor, pituitary tumor and no tumor. The model was trained on the Images Dataset "Brain Tumor Classification (MRI)" From Kaggle by SARTAJ under the CC0: Public Domain License. In addition to the model, I have also provided a graphical user interface (GUI) that allows users to upload an MRI image and get a prediction from the model. The GUI was built using the Tkinter library in Python.
The model is a convolutional neural network (CNN) with the following architecture:
Layer (type) Output Shape Param #
=================================================================
conv2d (Conv2D) (None, 1248, 1248, 32) 896
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 624, 624, 32) 0
_________________________________________________________________
conv2d_1 (Conv2D) (None, 622, 622, 64) 18496
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 311, 311, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 309, 309, 128) 73856
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 154, 154, 128) 0
_________________________________________________________________
flatten (Flatten) (None, 307328) 0
_________________________________________________________________
dense (Dense) (None, 128) 39338112
_________________________________________________________________
dropout (Dropout) (None, 128) 0
_________________________________________________________________
dense_1 (Dense) (None, 4) 516
=================================================================
Total params: 39,436,876
Trainable params: 39,436,876
Non-trainable params: 0More information:
GitHub Repository
Hugging Face Repository
Detailed Medium Article
Deep Learning
Machine Learning
Python
This is a deep learning model that can classify MRI images of the brain into four categories: glioma tumor, meningioma tumor, pituitary tumor and no tumor. The model was trained on the Images Dataset "Brain Tumor Classification (MRI)" From Kaggle by SARTAJ under the CC0: Public Domain License. In addition to the model, I have also provided a graphical user interface (GUI) that allows users to upload an MRI image and get a prediction from the model. The GUI was built using the Tkinter library in Python.
The model is a convolutional neural network (CNN) with the following architecture:
Layer (type) Output Shape Param #
=================================================================
conv2d (Conv2D) (None, 1248, 1248, 32) 896
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 624, 624, 32) 0
_________________________________________________________________
conv2d_1 (Conv2D) (None, 622, 622, 64) 18496
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 311, 311, 64) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 309, 309, 128) 73856
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 154, 154, 128) 0
_________________________________________________________________
flatten (Flatten) (None, 307328) 0
_________________________________________________________________
dense (Dense) (None, 128) 39338112
_________________________________________________________________
dropout (Dropout) (None, 128) 0
_________________________________________________________________
dense_1 (Dense) (None, 4) 516
=================================================================
Total params: 39,436,876
Trainable params: 39,436,876
Non-trainable params: 0More information:
GitHub Repository
Hugging Face Repository
Detailed Medium Article
