You will get Brain Tumor Segmentation with AI: A NIFTI-Based Approach


Project details
This project focuses on developing an AI-driven solution for brain tumor segmentation using NIFTI-format MRI scans. By leveraging deep learning techniques, such as U-Net architectures, the project aims to accurately identify and classify tumor regions into categories like "NOT TUMOR," "NECROTIC/CORE," "EDEMA," and "ENHANCING." The workflow includes loading and preprocessing medical imaging data, training robust neural networks, and evaluating performance with metrics like Dice Coefficient. With the ability to predict tumor segmentations on unseen datasets.
Machine Learning Tools
Keras, NumPy, OpenCV, Python, TensorFlowWhat's included $500
These options are included with the project scope.
$500
- Delivery Time 5 days
- Number of Revisions Unlimited
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
About Essa
Chemist
Minneapolis, United States - 1:42 pm local time
Proficient in machine learning, including deep learning, building and training neural networks, and computer vision. Skilled
in data preparation, SQL, and BigQuery for data analysis, with experience in model development. Also skilled in prompt development and evaluating AI responses.
Steps for completing your project
After purchasing the project, send requirements so Essa can start the project.
Delivery time starts when Essa receives requirements from you.
Essa works on your project following the steps below.
Revisions may occur after the delivery date.
Project Approval
All the necessary review and revisions are completed.



