This repository uses preprocessing technics such as image growing and erosion and dilation to crop the lungs from chest X-ray images.
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Updated
Dec 1, 2021 - Python
This repository uses preprocessing technics such as image growing and erosion and dilation to crop the lungs from chest X-ray images.
The preparation for the Lung X-Ray Mask Segmentation project included the use of augmentation methods like flipping to improve the dataset, along with measures to ensure data uniformity and quality. The model architecture was explored with two types of ResNets: the traditional CNN layers and Depthwise Separable.
Visual Analysis of Lung Segmentation using the U-NET Architecture on the Montgomery dataset
A deep learning approach to fight COVID virus. This model uses CNN with transfer learning to detect if a person is infected with COVID by looking at the lung X-Ray and further it segments the infected region of lungs producing a mask using U-Net
Few-shot learning project: Semantic segmentation of COVID-19 infection in CT scans
Tensorflow based training, inference and feature engineering pipelines used in OSIC Kaggle Competition
Deep learning models to lung lesion segmentation & classification on CT slices with pytorch.
George Mason University: DAEN Capstone project Spring 2021
This is a project of the Google Developer Student Club of FPT University Da Nang, built by members, and entered the TOP 10 finalists at the FPT Edu Hackathon 2021 in Hanoi, Vietnam.
Lung tumor segmentation with the UNet model.
Small version of the U-Net architecture, implemented in PyTorch. (Can be trained without significant computing resources)
This repository is dedicated to the scoring of lung diseases, where we propose a two-step workflow used for segmentation and scoring of lung diseases, including COVID-19
[ICCV 2023] Self-supervised Semantic Segmentation: Consistency over Transformation
COVID-19 Lung Infection Segmentation from CT Images
Lung Masking/Segmentation from Chest X-Rays using a custom modified lightweight U-Net Architecture,
Lung Segmentation using U-NET Architecture
Lung segmentation for chest X-Ray images with ResUNet and UNet. In addition, feature extraction and tuberculosis cases diagnosis had developed.
CT Scan utilities. Works with DICOM files.
Keypoint-based lung fissure segmentation with Geometric Convolutional Networks (Master's Thesis)
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