Connect the parts
MRI Scan DICOM/PNG -> Grayscale Masking & Thresholding -> Contour Extraction -> Feature Vector -> Classifier (Tumor / Healthy).
HEALTHCARE AI / archived
Brain Tumor Detection (MRI)
A Computer Vision model trained on MRI scan data to detect tumor presence using classical image processing and ML techniques..
The problem.
Study image-processing approaches to MRI tumor classification.
My contribution.
Designed and implemented the application described in this project, including its core workflow and supporting interface.
How the parts connect.
MRI Scan DICOM/PNG
Part of the project architecture.
Grayscale Masking & Thresholding
Part of the project architecture.
Contour Extraction
Part of the project architecture.
Feature Vector
Part of the project architecture.
The decisions.
Keep the workflow focused
Automated MRI-based tumor detection
Build, test, deliver.
Implementation and setup instructions.
What to keep in mind.
This is a portfolio study. No independently verified performance or accuracy benchmark is claimed.
Repository availability and external demonstrations can change; consult the source for current setup and limitations.