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GiornoSolos/
brain-tumor-classifier

Name: brain-tumor-classifier
Availability: InStock

pytorch

brain-tumor-classifier

image-classification

medical

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license: apache-2.0 tags:

medical
brain-tumor
classification
pytorch
computer-vision
healthcare datasets:
brain-tumor-mri-dataset metrics:
accuracy model-index:
name: brain-tumor-classifier results:
- task: type: image-classification name: Brain Tumor Classification dataset: name: Brain Tumor MRI Dataset type: brain-tumor-mri-dataset metrics:
  - type: accuracy value: 0.942 name: Accuracy

Brain Tumor Classification Model

This model classifies brain MRI scans into 4 categories:

Glioma: Glial cell tumors
Meningioma: Meningeal tissue tumors
No Tumor: Normal brain tissue
Pituitary: Pituitary gland tumors

Model Details

Architecture: ResNet50 + Enhanced Classifier
Accuracy: 94.2%
Input Size: 224x224x3
Classes: 4

Usage

python

from transformers import pipeline

classifier = pipeline("image-classification", model="GiornoSolos/brain-tumor-classifier")
result = classifier("path_to_mri_image.jpg")

Important Note

This model is for research and educational purposes only. Do not use for medical diagnosis. Always consult qualified healthcare professionals.

Training Details

Framework: PyTorch
Base Model: ResNet50 (ImageNet pretrained)
Optimizer: AdamW
Loss: CrossEntropyLoss with label smoothing
Data Augmentation: Rotation, flip, affine transforms

Classes

0: glioma
1: meningioma
2: notumor
3: pituitary