GlioAI: Automatic Brain Tumor Detection System

Automatic Brain Tumor Detection Using 2D Deep Convolutional Neural Network for Diffusion-Weighted MRI

Overview

Context

Objectives

Workflow

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User Journey
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App Workflow

Synopsis

Back-End Design: Implement Convolutional Neural Network

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Training Method

Dataset

Experiment and Results

Model and Training

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Transfer Learning: Model Accuracy

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No Transfer Learning: Model Accuracy

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Transfer Learning: Loss Curve

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No Transfer Learning: Loss Curve

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Comparison of the Models

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Evaluation

Conclusion

Feature Roadmap

App

Neural Network Architecture

Web Platform Engineering

Reflection

Future of GlioAI

Takeaway

Bottleneck

Phase I: Build Crowdsourcing Protocols for Doctors in Need of Diagnostic Feedback

Phase II: Working With Tangible Atoms to Deploy Network for Shipping Treatments

Project OKRS

Dependencies

Deep Learning

Web Application

Links for Other Viewing Formats

References

Attribution

Contributing

License

Sophomore at Adlai Stevenson High School

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