Medical Image Segmentation Using SegNet

How to create, train and evaluate SegNet for medical image segmentation
Updated 19 Aug 2020

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Deep Learning is powerful approach to segment complex medical image.
This demo shows how to prepare pixel label data for training, and how to create, train and evaluate VGG-16 based
SegNet to segment blood smear image into 3 classes – blood parasites, blood cells and background.
医用画像処理において、Deep Learningは非常に強力なアプローチの一つです。

[Keyward] 画像処理・セグメンテーション・ディープラーニング・DeepLearning・デモ・IPCVデモ

Cite As

Kei Otsuka (2024). Medical Image Segmentation Using SegNet (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017b
Compatible with R2017b to R2020a
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Fixed compatibility issue

updated to make it compatible with R2018b