Tools to interpret CT scan of halite

Visual Volume visualizes volumetric data using Three.js and WebGL, rendering 3D data from sources like CT scans.

A combination of work done in our MPhys project and in the internship with the Christie NHS Foundation Trust over the summer.

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.

COVID-19 Classification from 3D CT Images

Image-to-image deep learning framework for MRI to porosity map translation

Workflow-centred open-source fully automated lung volumetry in chest CT.

LUng CAncer Screeningwith Multimodal Biomarkers

A GUI tool for visualizing 3D CT scans with ground truth and predicted segmentation overlays. The viewer allows for easy navigation through slices and adjustment of CT scan intensities. Perfect for medical image analysis and comparison of segmentation results.

A repository containing deep learning models and evaluation methods for enhancing medical image segmentation in Computed Tomography (CT) scans, with a focus on U-Net variants, nnUNet, and Swin-UNet architectures.

A python class compatible with TensorFlow to perform data augmentation on 3D objects during CNN training.

In-depth motion analysis of mobile lung cancer tumors. Designed for 4D-CT scans of the thorax and provide valuable information for proton therapy treatment planning

Reconstruction of medical image data using DICOM format input data

U-Net for biomedical image segmentation

View volumetric (3D) medical images in Jupyter notebooks

Idiopathic pulmonary fibrosis (IPF) is a restrictive interstitial lung disease that causes lung function decline by lung tissue scarring. Although lung function decline is assessed by the forced vital capacity (FVC), determining the accurate progression of IPF remains a challenge. To address this challenge, we proposed Fibro-CoSANet, a novel end…

Deep CNN for performing 3D super resolution on CT/MRI scans

Segmentation and Classification models for COVID CT scans (COVID, pneumonia, normal) based on Mask R-CNN.

CNN's for bone segmentation of CT-scans.

A COVID-19 CT Scan Dataset Applicable in Machine Learning and Deep Learning