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advanced_computer_vision_with_tensorflow

annotation-of-ct-images

applied-data-science-specialization

coursera-world

coursera_capstone

covid-19-detection-from-lung-ct-scans

covid-detection-using-lung-xray-images

Covid19, Pnemonia, or Normal Detection using Lung Xray Images

covidct

Detection of COVID-19 by classifying Lungs CT scan

custom_and_distributed_training_with_tensorflow

customising_your_models_with_tensorflow2

deepleaning-specialization

deeplearning

dicom-annotator-1

dicom-cnn

Convolutional neural network solution for deep learning from DICOM images

dicom_anonymizer

Python script to annotate DICOM files

dicomtool

Dicom viewer and annotation tool in python

dicomviewer

A simple annotating tool for dicom medical images

dl-lung-ct-segmentation-for-covid-19-detection

dlaicourse

inf-net

Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Images, IEEE TMI 2020.

jcs

[IEEE TIP 2021] COVID-CS Dataset and Code of JCS: An explainable COVID-19 diagnosis system by joint classification and segmentation

lung-ct-covid-pathology-detection

Early exploration of detecting signs of lung pathology in COVID-19 Lung CT cases

machine-learning-specialization

med3dresnet

Python package with annotation tool GUI to compute cardiovascular risk via Deep Learning (DL) on thoracic CT scans

multiclass-semantic-segmentation-camvid

Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.

one-stop-for-covid-19-infection-and-lung-segmentation-plus-classification

✋🏼🛑 This one stop project is a complete COVID-19 detection package comprising of 3 tasks: • Task 1 --> COVID-19 Classification • Task 2 --> COVID-19 Infection Segmentation • Task 3 --> Lung Segmentation

pattern-recognition-covid

Final project for my Pattern Recognition class.

pyosirixscripts

A widely compatible DICOM-native annotation pipeline with strong support for data visualization was created to facilitate computer vision projects involving 3D cross-sectional data.

spinefinder

This repository contains code which was used to produce the results for the paper 'Vertebrae Detection and Localization in CT with Two-Stage CNNs and Dense Annotations' by James McCouat, Ben Glocker which was accepted into the MICCAI workshop MSKI 2019.

tensorflow-in-practice-specialization