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Medical Imaging Toolbox

Visualize, register, segment, and label 2D and 3D medical images

Medical Imaging Toolbox™ provides apps, functions, and workflows for designing and testing diagnostic imaging applications. You can perform 3D rendering and visualization, multimodal registration, and segmentation and labeling of radiology images. The toolbox also lets you train predefined deep learning networks (with Deep Learning Toolbox™).

You can import, preprocess, and analyze radiology images from various imaging modalities, including projected X-ray imaging, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), and nuclear medicine (PET, SPECT). The Medical Image Labeler app lets you semi-automate 2D and 3D labeling for use in AI workflows. You can perform multimodal registration of medical images, including 2D images, 3D surfaces, and 3D volumes. The toolbox provides an integrated environment for end-to-end computer-aided diagnosis and medical image analysis.

Medical Imaging Toolbox overview

Get Started

Learn the basics of Medical Imaging Toolbox

Import and Spatial Referencing

Read images and spatial metadata from medical imaging file formats

Display, Volume Rendering, and Surfaces

2-D and 3-D medical image display, 3-D surface generation, and volume rendering

Preprocessing and Augmentation

3-D registration and denoising, random intensity augmentation


Interactive medical image labeling for semantic segmentation workflows

Segmentation and Analysis

Medical image segmentation using deep learning, labeling app, or image processing algorithms, and radiomics analysis

Cellpose for Microscopy Segmentation

Segment microscopy images using Medical Imaging Toolbox Interface for Cellpose Library