You will get High-accuracy tumor grading AI with full pipeline and documented code
Project details
This project focuses on the classification of low-grade and high-grade gliomas using advanced machine learning techniques applied to MRI scans. Gliomas are among the most common types of brain tumors, and accurate classification is critical for treatment planning and prognosis. Unlike traditional methods, this project leverages a robust feature extraction and classification pipeline that achieves high accuracy, offering both binary classification and optional tumor segmentation. The system can generate detailed reports with confidence scores and visualizations of tumor regions, providing actionable insights for researchers, clinicians, and medical institutions. By combining automation, precision, and interpretability, this project stands out as a reliable and scalable solution for glioma analysis.
Machine Learning Tools
NumPy, OpenCV, pandas, Python, Python Scikit-Learn, scikit-learnWhat's included
| Service Tiers |
Starter
$25
|
Standard
$50
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | Unlimited |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 5 | 7 | 10 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
About M Zubair
AI/ML Engineer | Computer Vision Specialist | Online Tutor
Peshawar, Pakistan - 4:57 pm local time
A motivated and detail-oriented Computer Systems Engineering
graduate specializing in AI, Machine Learning, and Embedded
Systems. Seeking an internship or entry-level opportunity to
apply technical expertise in developing intelligent and efficient
systems.
ACADEMIC PROJECTS
Classification of Low-Grade and High-Grade Glioma (FYP)
Developed an AI-based radiomics model using CatBoost and
OpenCV.
Tools: Python, Scikit-learn, OpenCV, Pyradiomics
Image Segmentation using U-Net (PyTorch)
Built and trained a U-Net segmentation model for visual datasets.
Tools: PyTorch, NumPy
FIR Filter Design in Verilog
Designed and simulated a 4-tap FIR filter in ModelSim.
Tools: Verilog, ModelSim
Electronic Voting Machine (8051)
Created a 4-candidate EVM with LCD interface.
Tools: Embedded C, Proteus
Control System and PID Controller
Designed and tested PID models for stability improvement.
Tools: MATLAB, Simulink
Steps for completing your project
After purchasing the project, send requirements so M Zubair can start the project.
Delivery time starts when M Zubair receives requirements from you.
M Zubair works on your project following the steps below.
Revisions may occur after the delivery date.
2
All MRI scans are cleaned, standardized, and organized for analysis. Images are normalized, resized, and labeled (Low-Grade or High-Grade). Optional data augmentation improves model accuracy and robustness for reliable predictions.