Medical Imaging Segmentation with NVIDIA MONAI

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Overview

This example demonstrates how to:

• Preprocess medical imaging data

• Train a MONAI U-Net model

• Evaluate segmentation performance

• Run inference on new images

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Steps

1

Preprocess Data

Load and normalize medical imaging data.

2

Train Model

Initialize and train a MONAI U-Net model using your dataset.

3

Evaluate Performance

Assess the model's segmentation accuracy with test data.

4

Run Inference

Use the trained model to predict and segment new images.

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GitHub repository

The repository walks you through how to go through the above steps:

GitHub - valohai/NVIDIA-MONAI-ValohaiGitHub