AI MRI Brain Tumor Detection
Summary
Freelancer Client is hiring: AI MRI Brain Tumor Detection.
Location: Remote
I have a collection of MRI scans and need a complete AI pipeline that detects brain tumors with solid, production-ready performance. A moderate level of accuracy is perfectly acceptable for this phase; my main priority is a robust, reproducible workflow that I can continue to improve over time.
What you'll do:
• Build or fine-tune a model explicitly for MRI data.
• Deliver saved model weights, evaluation metrics, and a brief report on model performance, including confusion matrix and key misclassifications.
Skills: Python, Matlab and Mathematica, Machine Learning (ML), Neural Networks, Image Processing, Documentation, Deep Learning, AI Model Development, Data Augmentation, Model Deployment
Budget: $37500–$75000 USD
Source: Freelancer Client via Remote / Online. Apply on the source website.
Original
I have a collection of MRI scans and need a complete AI pipeline that detects brain tumors with solid, production-ready performance. A moderate level of accuracy is perfectly acceptable for this phase; my main priority is a robust, reproducible workflow that I can continue to improve over time.
Scope of work
• Build or fine-tune a model explicitly for MRI data.
• Apply three preprocessing steps—noise reduction, intensity normalization, and data augmentation—so the network trains on clean, standardized images while still learning from varied examples.
• Provide training and validation scripts (Python, PyTorch or TensorFlow preferred) plus clear instructions so I can rerun everything on my own hardware.
• Deliver saved model weights, evaluation metrics, and a brief report on model performance, including confusion matrix and key misclassifications.
Acceptance criteria
1. End-to-end code executes without errors on a fresh environment.
2. Validation results meet or exceed the agreed moderate-accuracy threshold we define at project start.
3. All preprocessing steps are configurable and documented.
4. Final hand-off includes README and comments that explain each stage of the pipeline.
If you have previous experience with medical imaging or have published models on MRI data, feel free to reference that when you respond.
Location & Details
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