Pneumonia Detection from Chest X-Rays 2D Images

Exploratoring a chest x-rays dataset and train a model that can predict the presence of pneumonia with human radiologist-level accuracy

Exploratoring a chest x-rays dataset and train a model that can predict the presence of pneumonia with human radiologist-level accuracy

Measuring the hippocampal volumes using a U-net trained model, integrated into a clinical-grade viewer and automatically measures hippocampal volumes, and generate reports.

Building a regression model to predict the estimated hospitalization time for a patient in order to help select/filter patients and evaluate model bias and uncertainty

An implementation of a 6MWT monitoring algorithm on an Andoid application that utilize multiple sensors, with a web tracking interface that allows post-test consultation and remote-monitoring using WebRTC technology.

Using MRI and GE features, we classify between AD (macro-)stages

Malignancy classification pipelines using machine and deep learning approaches

Multi-scale morphological sifting & K-means for mass detection and segmentation

U-Net architecture pipeline using PyTorch for medical image segmentation

Expectation Maximization algorithm using intinsity and position atlas information

Lung segmentation, pre-processing and image registration on 4DCT dataset

Brain tissue (WM, GM, CSF) segmentation using both multi-atlas and nnUNet

An ensemble pipeline using VGG16_BN architecture and attention blocks

2D Mammograms to reports with CLIP-based architecture and image-reports datasets