Simplifying deep learning for medical imaging

REMEX Lab's home page.

Repository for Master thesis project investigating classification of 3D chest CT scans using Vision Transformer.

This script reads DICOM files in a source directory or in a list of source directories and searches for the patients in the given patients' list creates a DICOM DataBase in the destination directory, copies the files, and creates a DicomDataBase.csv file and a summary.txt file.

Repository containing files associated with ENIGMA diffusion weighted image preprocessing protocol and instructional video series. Designed by Ryan Cali for the 2022 ReproNim Fellowship Project and the Imaging Genetics Center at the University of Southern California. Questions? Reach out to the author: rcali@loni.usc.edu

This project uses Convolutional Neural Network (CNN) to detect malignant skin cancer moles

Empowering healthcare with AI, LeukoVision automates the detection of leukemia cells in blood smear images. Revolutionizing leukemia care with speed and accuracy.

Project Overview:- The objective of this hackathon challenge is to develop a robust and efficient algorithm or AI model capable of accurately segmenting the hypodense region from Brain Non-Contrast Computed Tomography (NCCT) images. The primary goal is to automate and streamline the identification of early ischemic changes in acute stroke patients.

This work involves detecting malaria by their cell images.

This project aims to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN). The model is trained on a dataset of chest X-ray images and evaluated for its performance. The project is ongoing, and I aim to fine-tune the model in the future. If you are seeing this, it means I am still working on the project.