The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.
Keyphrases
- deep learning
- machine learning
- convolutional neural network
- high resolution
- artificial intelligence
- high throughput
- big data
- climate change
- autism spectrum disorder
- magnetic resonance
- magnetic resonance imaging
- mass spectrometry
- computed tomography
- working memory
- optical coherence tomography
- photodynamic therapy
- data analysis