Jekyll2026-02-22T12:30:02+00:00https://www.slideio.com/feed.xmlSlideIOMedical imaging library for python and c++.Stanislav MelnikovVersion 2.8.0 – OMETIFF Support2026-02-22T09:00:00+00:002026-02-22T09:00:00+00:00https://www.slideio.com/news/2026/02/22/Version%202.8.0We are pleased to announce the release of SlideIO version 2.8.0, an update to our open-source library for pathology image analysis.

This version introduces support for OME-TIFF files and adds the ability for the SlideIO converter to convert data to OME-TIFF format. It also includes multiple fixes and general improvements to stability and usability.

To help you take full advantage of the latest improvements, we have prepared a comprehensive tutorial that demonstrates how to use SlideIO in practical pathology image analysis scenarios. The tutorial is available in our GitHub repository:

https://github.com/Booritas/slideio-tutorial

It provides:

  • Step‑by‑step instructions for setting up and using SlideIO
  • Code examples for reading and working with whole slide images
  • Example workflows relevant to pathology image analysis

We welcome your feedback and issue reports on GitHub and appreciate your continued support of the SlideIO project.

]]>Stanislav MelnikovVersion 2.7.4 – Improved VSI Z‑Stack Metadata Parsing2025-11-23T09:00:00+00:002025-11-23T09:00:00+00:00https://www.slideio.com/news/2025/11/23/Version%202.7.4We are pleased to announce the maintenance release of SlideIO version 2.7.4, an update to our open‑source library for pathology image analysis.

This release includes an important fix for parsing VSI z‑stack metadata, improving the robustness and accuracy of SlideIO when working with Olympus VSI files. The updated metadata handling ensures more reliable access to z‑stack information, which is critical for quantitative and 3D pathology workflows.

To help you take full advantage of the latest improvements, we have prepared a comprehensive tutorial that demonstrates how to use SlideIO in practical pathology image analysis scenarios. The tutorial is available in our GitHub repository:

https://github.com/Booritas/slideio-tutorial

It provides:

  • Step‑by‑step instructions for setting up and using SlideIO
  • Code examples for reading and working with whole slide images
  • Example workflows relevant to pathology image analysis

We welcome your feedback and issue reports on GitHub and appreciate your continued support of the SlideIO project.

]]>Stanislav MelnikovVersion 2.7.3 – Improved SCN Z‑Stack handling2025-08-31T09:00:00+00:002025-08-31T09:00:00+00:00https://www.slideio.com/news/2025/08/31/Version%202.7.3We are pleased to announce the maintenance release of SlideIO version 2.7.3, an update to our open‑source library for pathology image analysis.

This release includes an important fix for reading SCN z‑stack slides, improving the robustness and accuracy of SlideIO when working with Leica SCN files.

To help you take full advantage of the latest improvements, we have prepared a comprehensive tutorial that demonstrates how to use SlideIO in practical pathology image analysis scenarios. The tutorial is available in our GitHub repository:

https://github.com/Booritas/slideio-tutorial

It provides:

  • Step‑by‑step instructions for setting up and using SlideIO
  • Code examples for reading and working with whole slide images
  • Example workflows relevant to pathology image analysis

We welcome your feedback and issue reports on GitHub and appreciate your continued support of the SlideIO project.

]]>Stanislav MelnikovVersion 2.6.0 - Support PerkinElmer Vectra QPTIF images2024-06-30T09:00:00+00:002024-06-30T09:00:00+00:00https://www.slideio.com/news/2024/06/30/Version%202.6.0We are excited to announce the release of SlideIO version 2.6.0, an update to our open-source library for pathology image analysis. This latest version adds support PerkinElmer Vectra QPTIF. To help you get started with these new capabilities, we have prepared a comprehensive tutorial that demonstrates the usage of the library. The tutorial, available at our GitHub repository here, provides step-by-step instructions and code samples to guide you through the process of reading pathology image analysis workflows.

]]>Stanislav MelnikovVersion 2.5.0 - Support of Olympus VSI images2024-02-24T09:00:00+00:002024-02-24T09:00:00+00:00https://www.slideio.com/news/2024/02/24/Version%202.5.0We are excited to announce the release of SlideIO version 2.5.0, an update to our open-source library for pathology image analysis. This latest version adds support of Olympus VSI images. Additionally, API extended to retrieve information about internal image pyramid.

To help you get started with these new capabilities, we have prepared a comprehensive tutorial that demonstrates the usage of the library. The tutorial, available at our GitHub repository here, provides step-by-step instructions and code samples to guide you through the process of reading pathology image analysis workflows.

]]>Stanislav MelnikovVersion 2.4.1 - Support of DICOM WSI images2024-01-21T09:00:00+00:002024-01-21T09:00:00+00:00https://www.slideio.com/news/2024/01/21/Version%202.4.1We are excited to announce the release of SlideIO version 2.4.1, an update to our open-source library for pathology image analysis. This latest version adds support of DICOM whole slide images (WSI). Slideio 2.4.1 release is focused on improvement of reading of DICOM images. The driver now supports whole slide images. Additionally, added support of Jpeg 2000 encrypted images.

To help you get started with these new capabilities, we have prepared a comprehensive tutorial that demonstrates the usage of the library. The tutorial, available at our GitHub repository here, provides step-by-step instructions and code samples to guide you through the process of reading pathology image analysis workflows.

]]>Stanislav MelnikovVersion 2.3.0 - Improving performance of NDPI driver2024-01-02T09:00:00+00:002024-01-02T09:00:00+00:00https://www.slideio.com/news/2024/01/02/Version%202.3.0We are excited to announce the release of SlideIO version 2.3.0, an update to our open-source library for pathology image analysis. This latest version improves reading of Hammamatsu NDPI images. Slideio 2.3.0 release is focused on improvement of performance of NDPI drivers. The driver now uses restart markers to read regions of large JPEG images.

To help you get started with these new capabilities, we have prepared a comprehensive tutorial that demonstrates the usage of the library. The tutorial, available at our GitHub repository here, provides step-by-step instructions and code samples to guide you through the process of reading pathology image analysis workflows.

]]>Stanislav MelnikovVersion 2.2.0 - Introducing image transfomations2023-06-16T09:00:00+00:002023-06-16T09:00:00+00:00https://www.slideio.com/news/2023/06/16/Version%202.2.0We are excited to announce the release of SlideIO version 2.2.0, an update to our open-source library for pathology image analysis. This latest version introduces a range of new features, with a focus on image transformations and expanded filter support. One of the key highlights of SlideIO 2.2.0 is the addition of image transformations. We understand the importance of flexible image manipulation in pathology analysis, and to address this, we have incorporated comprehensive color transformations. With the new color transformation functionality, users can now easily convert images between various color spaces, including grayscale, HSV, HLS, YUV, and more. This allows for enhanced analysis and exploration of different color representations, unlocking deeper insights within pathology images.

Additionally, SlideIO 2.2.0 now offers extensive support for filters through integration with the widely-used OpenCV library. Users can leverage a rich set of filters, including Gaussian blur, median blur, Sobel, Scharr, Laplacian, bilateral, and Canny filters, to enhance image quality, perform edge detection, noise reduction, and other advanced analysis tasks. These filters provide powerful tools to preprocess and enhance pathology images, improving the accuracy and effectiveness of subsequent analysis techniques.

To help you get started with these new capabilities, we have prepared a comprehensive tutorial that demonstrates the usage of image transformations and the supported filters. The tutorial, available at our GitHub repository here, provides step-by-step instructions and code samples to guide you through the process of utilizing these features in your pathology image analysis workflows.

]]>Stanislav MelnikovVersion 2.1.1 - Maintenance release2023-05-24T09:00:00+00:002023-05-24T09:00:00+00:00https://www.slideio.com/news/2023/05/24/Version%202.1.1We are excited to announce the release of SlideIO Library version 2.1.1, a maintenance release that includes important updates and fixes for the slide converter. If you have any questions or concerns, please do not hesitate to contact us. Thank you for your continued support.

]]>Stanislav MelnikovVersion 2.1.0 - Pathology Slide Converter2023-05-21T09:00:00+00:002023-05-21T09:00:00+00:00https://www.slideio.com/news/2023/05/21/Version%202.1.0We are thrilled to announce the release of SlideIO Library 2.1.0, featuring an exciting new addition - the Pathology Slide Converter. With this latest version, users can now convert any slide supported by the SlideIO library to the widely used Aperio SVS format. Key Features of the Pathology Slide Converter:

Output File Format: The first version of the converter converter allows seamless conversion of slides to the Aperio SVS format.

Compression Selection: Users have the flexibility to choose between two compression algorithms, JPEG and JPEG2000, during the conversion process. This empowers users to optimize the file size and image quality based on their specific requirements. Please note that JPEG compression can be selected only for 8bit 1 and 3 channel images.

Selective Conversion: Users can convert the entire slide or specify a rectangular block of interest, offering granular control over the conversion process. This enables focused extraction and conversion of specific regions or areas within the slide.

Aperio SVS Limitations: It is important to note that the Aperio SVS format does not support multiple images within a slide. User can select which image from multi-imagge slide should be converted. Another limitation of the format is missing support 3D and 4D images, therefore only conversion of single Z-slices and time frame is possible.

The introduction of the Pathology Slide Converter in SlideIO Library 2.1.0 expands the capabilities of the library and provides users with a powerful tool for working with pathology slides. Whether you are conducting research, developing medical applications, or collaborating with Aperio systems, the converter opens up new opportunities for leveraging the Aperio SVS format.

Upgrade to SlideIO Library 2.1.0 today and unlock the full potential of pathology slide conversion. Explore the wide range of supported slide formats and effortlessly convert them to Aperio SVS format with ease and precision.

Happy converting and exploring the world of pathology slides with SlideIO Library 2.1.0!

]]>Stanislav Melnikov