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This repository contains a MATLAB project for malaria detection in microscopic images. It includes a MATLAB app and a standalone script that apply a malaria cell prediction algorithm. The project aims to assist in automating the detection of malaria cells, aiding in medical diagnosis and research.

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mchinmayarao/MalariaDetector

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MalariaDetector

This project aims to detect malaria cells in microscopic images using MATLAB. It provides both a MATLAB app and a standalone script for malaria detection.

Project Structure

  • Malaria: The main project folder.
    • app.mlapp: MATLAB app file for the Malaria detection app.
    • MalariaDetector.app: MATLAB app bundle file for the Malaria detection app.
    • test_images: Folder containing test images for malaria detection.
      • infected: Subfolder containing infected image samples.
      • NotInfected: Subfolder containing non-infected image samples.

Usage

  1. MATLAB App (app.mlapp)

    • Open MATLAB and navigate to the Malaria folder.
    • Run the app.mlapp file to launch the Malaria detection app.
    • Click on the "Choose Image" button to select an image file (PNG format).
    • The app will apply the malaria cell prediction algorithm and display the result.
  2. Standalone Script (malaria_detection.m)

    • Open MATLAB and navigate to the Malaria folder.
    • Run the malaria_detection.m script to perform malaria detection on the chosen image.
    • Update the file paths in the script to point to the desired image file.

Dependencies

  • MATLAB: The project requires MATLAB software to run.
  • MATLAB Image Processing Toolbox: Ensure that you have the Image Processing Toolbox installed.

Sample Images

The test_images folder contains sample infected and non-infected microscopic images. You can use these images to test the malaria detection algorithm.

About

This repository contains a MATLAB project for malaria detection in microscopic images. It includes a MATLAB app and a standalone script that apply a malaria cell prediction algorithm. The project aims to assist in automating the detection of malaria cells, aiding in medical diagnosis and research.

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