RaySearch Laboratories has launched RayStation 2024B, the latest version of its RayStation treatment planning system, to automate critical clinical workflows.

RayStation 2024B is designed for cancer treatment planning by automating essential clinical workflows, including image import, deep-learning segmentation, and automated plan adaptation.

The new RayStation version introduces a new workspace for fully automated follow-up and plan adaptation.

This automation encompasses several steps, beginning with the enhancement of the patient’s daily image for precise dose computation, followed by delineation of organs and body parts, and concluding with the adaptation of the treatment plan based on the new image.

The system’s capability to automatically import images and apply deep-learning segmentation ensures that all patients are segmented immediately after image acquisition, saving time and reducing manual effort.

This functionality is part of a comprehensive framework that allows for the automated import of any DICOM data, triggering subsequent actions within RayStation.

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Additionally, RayStation 2024B expands its library of deep-learning segmentation models, featuring guideline-based models for head-and-neck lymph nodes and brachial plexus.

The update also significantly boosts the speed of image segmentation.

RayStation 2024B also features a new tool for stereotactic radiosurgery planning, which aids in minimising the dose to healthy tissue while treating multiple tumours.

RaySearch said that the RayStation treatment planning system supports a broad spectrum of treatment machines, serving as a unified control centre for all planning needs.

RaySearch founder and CEO Johan Löf said: “Automation of repetitive tasks is essential to boost the efficiency at the clinics. This efficiency gain will be important to be able to serve an increasing patient population to be treated for cancer, as well as to free up time to handle the more complicated patient cases.”