Olympus scanR high-content screening station v. 3.3 adds improved deep-learning capabilities for fast, efficient image analysis

The scanR high-content screening (HCS) station provides fully automated image acquisition and data analysis. Version 3.3 improves the deep-learning technology’s capabilities to reliably separate objects in biological samples using instance segmentation, the ability to detect and delineate distinct objects of interest in an image.

Accurate object segmentation: raw data (left), standard threshold (middle), TrueAI instance segmentation (right). Instance segmentation reliably separates difficult-to-distinguish objects that are very close together, such as cells or nuclei in colonies or tissue.Accurate object segmentation: raw data (left), standard threshold (middle), TrueAI instance segmentation (right). Instance segmentation reliably separates difficult-to-distinguish objects that are very close together, such as cells or nuclei in colonies or tissue. Image Credit: Olympus Life Science Solutions

Reliable image segmentation

Using a self-learning microscopy approach, the scanR system’s AI automatically analyzes data in an assay-based workflow. The deep-learning technology can detect cells, nuclei and subcellular objects, and extract features from a list of over 100 object parameters. Version 3.3 significantly improves the deep learning object segmentation capabilities to more accurately segment difficult-to-distinguish objects, such as cells or nuclei that are very close together, like in cell colonies or tissue.

Pretrained models

In addition to tools to develop neural network models for specific applications, scanR version 3.3 comes with pretrained neural network models for nuclei and cells. These can be used in a broad range of standard applications, including the ability to distinguish between confluent cells and dense nuclei, eliminating the time to train the neural network.

Easier calibration and collaboration

Version 3.3 of the scanR software also includes a well plate calibration assistant that makes it fast and simple to calibrate a new well plate for the system. In addition, a new level of license enables collaborators to open, review and re-gate scanR analysis files for easier results sharing.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Evident Corporation. (2021, December 08). Olympus scanR high-content screening station v. 3.3 adds improved deep-learning capabilities for fast, efficient image analysis. News-Medical. Retrieved on March 21, 2023 from https://www.news-medical.net/news/20211208/Olympus-scanR-high-content-screening-station-v-33-adds-improved-deep-learning-capabilities-for-fast-efficient-image-analysis.aspx.

  • MLA

    Evident Corporation. "Olympus scanR high-content screening station v. 3.3 adds improved deep-learning capabilities for fast, efficient image analysis". News-Medical. 21 March 2023. <https://www.news-medical.net/news/20211208/Olympus-scanR-high-content-screening-station-v-33-adds-improved-deep-learning-capabilities-for-fast-efficient-image-analysis.aspx>.

  • Chicago

    Evident Corporation. "Olympus scanR high-content screening station v. 3.3 adds improved deep-learning capabilities for fast, efficient image analysis". News-Medical. https://www.news-medical.net/news/20211208/Olympus-scanR-high-content-screening-station-v-33-adds-improved-deep-learning-capabilities-for-fast-efficient-image-analysis.aspx. (accessed March 21, 2023).

  • Harvard

    Evident Corporation. 2021. Olympus scanR high-content screening station v. 3.3 adds improved deep-learning capabilities for fast, efficient image analysis. News-Medical, viewed 21 March 2023, https://www.news-medical.net/news/20211208/Olympus-scanR-high-content-screening-station-v-33-adds-improved-deep-learning-capabilities-for-fast-efficient-image-analysis.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post
You might also like...
New partnership creates an automated anatomic pathology slide-scanning solution