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