医学成像

为医学图像处理应用扩展深度学习工作流

通过将 Medical Imaging Toolbox™ 与 Deep Learning Toolbox™ 结合使用，将深度学习应用于自动驾驶应用。

App

医学图像标注器

Interactively explore, label, and publish animations of 2-D or 3-D medical image data （自 R2022b 起）

主题

Create Datastores for Medical Image Semantic Segmentation (Medical Imaging Toolbox)

Create datastores that contain images and pixel label data from a groundTruthMedical object for training semantic segmentation deep learning networks.
- Convert Ultrasound Image Series into Training Data for 2-D Semantic Segmentation Network (Medical Imaging Toolbox)
- Create Training Data for 3-D Medical Image Semantic Segmentation (Medical Imaging Toolbox)
Datastores for Deep Learning
Learn how to use datastores in deep learning applications.
深度学习层列表
探索 MATLAB^® 中的所有深度学习层。

精选示例

Segment Lungs from CT Scan Using Pretrained Neural Network

Import a pretrained ONNX™ (Open Neural Network Exchange) 3-D U-Net [1] and use it to perform semantic segmentation of the left and right lungs from a 3-D chest CT scan. Semantic segmentation associates each voxel in a 3-D image with a class label. In this example, you classify each voxel in a test data set as belonging to the left lung or right lung. For more information about semantic segmentation, see Semantic Segmentation (Computer Vision Toolbox).

打开实时脚本