MEDICAL IMAGE PROCCESSING
Descrição da oferta de emprego
The goal is to perform vessel segmentation on retina images to isolate and display only the vessels using traditional image processing techniques, without any deep learning or AI methods.
Below are the project requirements.
Project Stages.
Image Preprocessing.
Normalization Noise removal (Smoothing) Median/adaptive median approaches Sharpening Transformations (Brightness, Contrast) Histogram equalization Convolution/Correlation Entropy, Range, and Standard Deviation Filters Note.
The algorithm must handle noise and varying input sizes.
Texture Modeling.
Gaussian Mixture Model (GMM) Histogram of Oriented Gradients (HoG) Co-occurrence Histogram (CoHog) Laplacian of Gaussian (LoG) Local Binary Pattern (LBP) Geometric Shape Modeling.
Hough Transform Extreme Point Detection.
Analyze the effect of the M matrix in Harris corner detection.
Rotation and Scale Invariance.
Ensure invariance using appropriate methods.
Include SIFT if applicable.
Thresholding.
Implement Otsu’s method or its variations.
Morphological Operations.
Select appropriate operations.
Validation.
Test on at least 10 images and compare results with labeled data.
Evaluation.
Calculate IoU for each image and compute the average IoU across all images.
Additional Requirements.
Document the project in a.
pynb file (e.
., [login to view URL]).
Input images should be stored in a DB folder next to the notebook file.
Each step should include a brief explanation above the code, with outputs displayed below.
The program should handle inputs of varying noise levels, rotations, and sizes, consistently isolating the vessels in the output.
Could you let me know if this can be implemented in Python in the specified format? Additionally, please provide an estimated completion time and cost.
Matlab and Mathematica Algoritmo Python OpenCV Imagem ID do Projeto.
# Sobre o projeto 4 propostas Aberto para ofertas Projeto remoto Ativo em 1 minuto atrás
Detalhes da oferta
- Indeterminado
- Em todo Portugal
- Indeterminado - Indeterminado
- 24/11/2024
- 22/02/2025
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