ct_segmentation_eggs
This repository is part of a research work on obtaining morphometric measurements of the internal parts of chicken eggs using segmentation techniques using deep learning such as U-Net and FCN.
Science Score: 44.0%
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Repository
This repository is part of a research work on obtaining morphometric measurements of the internal parts of chicken eggs using segmentation techniques using deep learning such as U-Net and FCN.
Basic Info
- Host: GitHub
- Owner: jeanpierrelv
- Language: Python
- Default Branch: main
- Size: 18.5 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
🥚 Alternative Non-Destructive Approach for Estimating Morphometric Measurements of Chicken Eggs from Tomographic Images with Computer Vision
This repository contains code and resources for estimating morphometric measurements (e.g., height, width, and shell thickness) of chicken eggs using real CT images. The system uses two approaches:
📌 Project Overview
Conventional methods for measuring internal structures of chicken eggs often require destructive techniques. In this phase, we propose an approach based on 3D real computed tomography (CT) images.
The main goals of this part are:
- Segmentation-based estimation using 3D U-Net or Fully Convolutional Networks (FCN).
- Direct estimation using a head of fully connected layers for regression after feature extraction.
- Estimate internal measurements: shell thickness, egg height, egg width, volumes, and more.
🧠 Methods
We use deep learning techniques, including:
- 3D U-Net / FCN for semantic segmentation of CT volumes.
- Fully Connected Regression Head to directly estimate measurements from latent features.
- PyTorch framework for training and inference.
The system has been tested with real tomographic data of chicken eggs.
📁 Repository Structure
bash
.
├── models/model_3D.py # 3D segmentation models (U-Net, FCN)
├── data/data_backup.tar.xz # 3D CT images and labels
├── Models/tests_train.py # Training script
├── graph_metrics_real.py # Metrics curves
├── 3D_Voxel_test.py # Morphometric measurement extraction
└── README.md # Project documentation
🚀 Cite
BibTeX
@article{article, author = {Vargas, Jean and Abreu, Katariny and de Paula, Davi and Salvadeo, Denis and Souza, Lilian and Rabello, Carlos}, year = {2024}, month = {12}, pages = {4039}, title = {Alternative Non-Destructive Approach for Estimating Morphometric Measurements of Chicken Eggs from Tomographic Images with Computer Vision}, volume = {13}, journal = {Foods}, doi = {10.3390/foods13244039} }
Owner
- Name: Jean Pierre López
- Login: jeanpierrelv
- Kind: user
- Location: Campinas, Brazil
- Company: @Unicamp
- Repositories: 1
- Profile: https://github.com/jeanpierrelv
I'm Ph.D. student at School of Electric Engineering - University of Campinas
Citation (CITATION.cff)
@article{article,
author = {Vargas, Jean and Abreu, Katariny and de Paula, Davi and Salvadeo, Denis and Souza, Lilian and Rabello, Carlos},
year = {2024},
month = {12},
pages = {4039},
title = {Alternative Non-Destructive Approach for Estimating Morphometric Measurements of Chicken Eggs from Tomographic Images with Computer Vision},
volume = {13},
journal = {Foods},
doi = {10.3390/foods13244039}
}
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