Code for diagnosing glaucoma from Lumos lens
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Updated
Jul 17, 2019 - Python
Code for diagnosing glaucoma from Lumos lens
In order to perform Glaucoma Diagnosis, image segmentation is performed to identify the size of Optic Disk and Cup. This repository contains U-Net segmentation network for the retinal image segmentation.
Convert hand written intraocular pressure graphs to csv.
Repositório com a parte prática do meu Trabalho de Conclusão de Curso III, referente ao algoritmo da arquitetura CapsNet para a classificação de imagens de retina em glaucomatosas e normais.
Standardized Multi-Channel Dataset for Glaucoma (SMDG-19) is a collection and standardization of 19 public full-fundus glaucoma images and associated metadata.
This project involves building a Glaucoma Detection AI-ML model using a Convolutional Neural Network (CNN) to classify retinal images as either "Glaucoma Affected" or "Normal." The model is trained using ImageDataGenerator for data augmentation, with binary cross-entropy loss, Adam optimizer, and is saved in `.keras` format.
Code for the SIPAIM 2024 paper 'Automatic Glaucoma Classification and Justification Using a Large and Diverse Dataset'.
Web App para detectar medicamentos contraindicados para el glaucuoma
This study presents a deep learning-based approach for automated glaucoma detection using VGG16, a convolutional neural network (CNN) pre-trained on ImageNet.
This project uses deep learning algorithms and the Keras library to determine if a person has certain diseases or not from their chest x-rays and other scans. The trained model is displayed using Streamlit, which enables the user to upload an image and receive instant feedback.
Source code of LightHCG model. D, Kim(2025), "LightHCG: a Lightweight yet powerful HSIC Disentanglement based Causal Glaucoma Detection Model framework", arXiv:2512.02437, pp. 1-11.
Actively maintained and comprehensive public glaucoma dataset catalog
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