Tools to interpret CT scan of halite
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Updated
Jun 7, 2019 - Python
Tools to interpret CT scan of halite
Automatic midplane finder and tissue segmentation for head CT scans
Deep-Learning solution for detecting Intra-Cranial Hemorrhage (ICH) 🧠 using X-Ray Scans in DICOM (.dcm) format.
Train a 3D convolutional neural network to predict presence of pneumonia.
Adopted a convolutional neural network for COVID-19 testing. Examined the performance of different pre-trained models on CT testing and identified that larger, out-of-field datasets boost the testing power of the models.
A net providing information about stroke type using kt-scan image
Biomedical Image Processing involves applying computer algorithms to analyze and enhance medical images, such as X-rays or MRI scans. It aims to extract meaningful information, diagnose diseases, and aid in medical research by employing advanced image analysis techniques and computational tools.
A combination of work done in our MPhys project and in the internship with the Christie NHS Foundation Trust over the summer.
Preprocessing the STOIC2021 dataset for detecting COVID-19 severity
Application for displaying and analyzing 3D volumes that utilizes custom made engine.
Successful detection of Covid-19 using Chest X-Rays by building a Convolutional Neural Network (CNN) and visualising the world data using Covid-19 Trends.
Software for the OCT Scanner Project
Supervised Algorithms For The Detection Of COVID-19 From Chest CT & X-ray Scan Images
The YOLOv4 is used for pancreas detection on CT-scans.
COVID-19 CT scan image classification using EfficientNetB2 with transfer learning and deployment using Streamlit. This project focuses on accurately classifying CT scan images into three categories: COVID-19, Healthy, and Others. Leveraging transfer learning on pretrained EfficientNetB2 models, the classification model achieves robust performance.
An implementation of a HIAS compatible xDNN classifier by Nitin Mane. Inspired by SARS-CoV-2 CT-scan dataset: A large dataset of real patients CT scans for SARS-CoV-2 identification by Eduardo Soares, Plamen Angelov, Sarah Biaso, Michele Higa Froes, Daniel Kanda Abe.
Deep CNN-Based CAD System for COVID-19 Detection Using Multiple Lung CT Scans.
COVID-19 Classification from 3D CT Images
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