OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

Surgical Image Guidance and Healthcare Toolkit

Personal resume website built by using Python Django, NodeJS/Express framework, Go Gin framework, Java spring boot, spring security, JWT, and MongoDB. Terraform / Ansible leveraged in its deployment. EKS monitoring by Grafana/Prometheus sample provided.

CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!

Advanced Normalization Tools (ANTs)

A set of tools for medical imaging processing and analysis that I have been crafting over the years.

AI Toolkit for Healthcare Imaging

Medical imaging toolkit for deep learning

[MedIA] Accompanying paper list and source code for survey "A comprehensive survey on deep active learning in medical image analysis"

Code for ICASSP 2024 paper"Embedded Feature Similarity Optimization with Specific Parameter Initialization for 2D/3D Medical Image Registration"

Automated Segmentation for Eustachian Tube Disfunction

Repositório com atividades da disciplina de Processamento de Imagens Médicas 2024.1

Website for the myriad team of the CREATIS laboratory

TubeTK is an open-source toolkit for the segmentation, registration, and analysis of tubes and surfaces in images, developed by Kitware, Inc.

Medical Image processing project.

A Python bootcamp for medical students designed to teach basic DICOM and imaging data handling skills.

research aimed at predicting outcomes such as: post-operation mortality, Impact of comorbidities on ICU admission after cardiac surgeries, total icu stay post emergency operation, as well as utilizing deep learning to perform CT/MRI segmentation.

This project loads CT scans, arranges DICOM slices into 3D images, segments, performs alpha fusion, and optimizes coregistration for precise visualization.

This GitHub repository hosts the notebooks and tools developed as part of this thesis to automate the extraction, processing, and analysis of data from the MICCAI 2023 conference, aiding in the systematic review and providing a structured foundation for further research in this crucial area.

Official implementation of "ASF-YOLO: A Novel YOLO Model with Attentional Scale Sequence Fusion for Cell Instance Segmentation".