NiftyNet

NiftyNet is an open-source deep learning platform. Built on top of TensorFlow, it provides a modular framework for designing, training, and deploying convolutional neural networks (CNNs) for biomedical imaging tasks such as segmentation, classification, and regression. NiftyNet enables researchers and developers to build scalable and reproducible AI pipelines for medical imaging applications.

Features of NiftyNet:

• Designed specifically for medical image analysis including 2D, 3D, and multi-modal data.
• Built on TensorFlow for deep learning model development and deployment.
• Includes pre-trained models for organ segmentation, lesion detection, and classification tasks.
• Provides built-in support for data loading, preprocessing, augmentation, and evaluation.
• Modular and extensible architecture suitable for research and experimentation.
• Supports GPU acceleration for faster model training and inference.
• Open-source and customizable for biomedical AI research.

NiftyNet Usage

$ sudo su
$ cd /opt
$ source /opt/niftynet37-env/bin/activate
$ pip show niftynet | grep Version