TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture. It aims to detect and classify the brain tumours from MRI scans. The detection is done using Image Processing algorithms and classification using Deep learning techniques.
The model is also deployed as a web application using Flask framework.
Download trained model from here.
- TumorInsight Web App - Technology at your fingertips!
- Image Segmentation (K-means clustering)
- Image Processing (Median filtering, morphological processing etc.)
- RESNET50 architecture for classification
- Flask framwework for integrating with frontend of web app
- And More...
TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture. It aims to detect and classify the brain tumours from MRI scans. The detection is done using Image Processing algorithms and classification using Deep learning techniques.
The model is also deployed as a web application using Flask framework.
In addition, you can also customize the following properties according to the need.
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Finally, call func(arg) in main()
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func(input())- Xcode 10.2.1
- Swift 5.0
Follow these steps to use this project.
- Clone the repository.
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Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/NewFeature) - Commit your Changes (
git commit -m 'Add some NewFeature') - Push to the Branch (
git push origin feature/NewFeature) - Open a Pull Request
TumorInsight is available under the MIT license. See the LICENSE file for more info.
Pranav Khurana
