Open source python/c++ library for reading of medical images
Overview
Slideio is a c++ library and a python module for the reading of medical images. It allows reading whole slides as well as any region of a slide. Large slides can be effectively scaled to a smaller size. The module uses internal zoom pyramids of images to make the scaling process as fast as possible. Slideio supports 2D slides as well as 3D data sets and time series.
The module delivers a raster as a numpy array and compatible with the popular computer vision library OpenCV.
The module builds accesses images through a system of image drivers that implement specifics of different image formats. Currently following drivers are implemented:
| Driver | File format | File extensions | Format developer | Scanners |
|---|---|---|---|---|
| SVS | Aperio SVS | *.svs | Leica Microsystems | Aperio GT 450 and Aperio GT 450 DX |
| AFI | Aperio AFI - Fluorescent images | *.afi | Leica Microsystems | |
| SCN | Leica SCN images | *.scn | Leica Microsystems | Leica SCN400 |
| CZI | Zeiss CZI images | *.czi | Zeiss Microscopy | ZEISS Axioscan 7 |
| ZVI | Zeiss ZVI image format | *.zvi | Zeiss Microscopy | |
| DCM | DICOM images | *.dcm, no extension | ||
| NDPI | Hamamatsu NDPI image format | *.ndpi | Hamamatsu | |
| GDAL | General image formates | .jpeg,.jpg,.tiff,.tiff,*.png | - | - |
The library is built as a c++ python extension and provides c++ and python interfaces.
Library latest news
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Version 2.0.5
We are pleased to announce the release of SlideIO library maintenance version 2.0.5! This release focuses on resolving several bugs that have been reported by our users, specifically those related to rounding errors during strong rescaling of images.
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Version 2.0.4
We are excited to announce the release of SlideIO version 2.0.4! This version comes with an improvement in memory consumption for tiff-based images, specifically Aperio SVS and Leica SCN.
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Version 2.0.2
We are thrilled to announce the release of SlideIO version 2.0.2! This version comes with two new features that improve the performance and functionality of the library when working with DICOM images.