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项目作者： duygut

项目描述 ：
Detecting white blood cancer cells based on the collected images by pattern recognition and machine learning techniques.
高级语言： MATLAB
项目地址: git://github.com/duygut/Detection_of_cancer_cells_over_blood_microscopy_images-.git
创建时间： 2019-11-01T03:00:52Z
项目社区：https://github.com/duygut/Detection_of_cancer_cells_over_blood_microscopy_images-
开源协议：GNU General Public License v3.0
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Detection of cancer cells over blood microscopy images based on shape anomaly

The codes in this repository have been implemented in MATLAB.

  • The aim of this project is detecting white blood cancer cells based on the collected images by pattern recognition and machine learning techniques.

  • The project has 6 main topics:

  1. Image acquisition
  2. Image preprocessing
  3. Image Segmentation
  4. Morphologic Operations
  5. Feature Extraction
  6. Clasification
  • In this project the different results have been shown with different methods and their impact on classification accuracy.
    • CIELAB Lab color segmentation and K-Means clustering used for image segmentation,
    • Watershed algorithm applied to detect and separate overlapped white blood cells.
    • Texture, statistical and geometrical features are used for feature extraction of white blood cells
    • Support Vector Machine and Multilayer Perceptron Neural Network used for classification.

In total 108 images were analyzed and up to 95% accuracy has been achieved.

Dataset can be request in below link

https://homes.di.unimi.it/scotti/all/