This project implements a deep learning pipeline for tumor detection and segmentation in medical images (MRI/CT) using the MONAI framework and PyTorch.

Machine Learning use case in the field of Healthcare. In this project MONAI and pytorch frameworks are used for 3D Liver segmentation.

The "baa-rnd-pancreas-tumor-segmentation" repository is a project that focuses on tumor segmentation in pancreatic images using the MONAI library. MONAI, which stands for Medical Open Network for AI, is a deep learning framework specifically designed for medical imaging tasks.

Collection of ipynbs for the medical imaging using MonAI and Other DL Frameworks

This repository contains a collection of MONAI tutorials, demonstrating how to use this powerful framework for deep learning in medical imaging. Each tutorial includes a Google Colab notebook with detailed explanations and code examples.

This project implements automated segmentation of the carotid intima-media-adventitia (IMA) complex using a U-Net architecture built with the Medical Open Network for Artificial Intelligence (MONAI) framework. The model processes ultrasound images to identify and segment the IMA region, which is crucial for cardiovascular disease assessment.

This project aims to automatically segment anatomically complex brain tumors from multimodal 3D MRI images. By using the MONAI (Medical Open Network for AI) framework and the 3D U-Net deep learning architecture, high-precision automatic identification of the tumor core (TC), enhanced tumor (ET), and the entire tumor region (WT) is achieved.