Texture-based medical image segmentation

version 1.0.0.0 (410 KB) by Kei Otsuka
Demo files to take the first step to use texture-based approach for medical imaging

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Updated 8 Mar 2018

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This demo is used in MathWorks Webinar and shows how to use texture-based approach for medical imaging. GLCM(gray-level co-occurrence matrix) is one way to characterize the texture of an image by calculating how often pairs of pixel with specific values, and is good algorithm to understand what the texture is for image segmentation.
MathWorksのビデオ、"医用画像処理:テクスチャ解析の基礎"にて使用したデモファイルです。GLCM(同時生起行列)は特定の輝度の並びがどの程度の頻度で存在しているかを表した行列で、テクスチャ情報とは何かを理解するために最適なアルゴリズムの一つです。本デモではGLCMを利用して、医用画像のセグメンテーションを行う例を2つ後紹介します。
[Keyward]
画像処理・セグメンテーション・医用画像・GLCM・同時生起行列・デモ・IPCVデモ

Cite As

Kei Otsuka (2022). Texture-based medical image segmentation (https://www.mathworks.com/matlabcentral/fileexchange/66287-texture-based-medical-image-segmentation), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017b
Compatible with any release
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