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AI‑Powered Workflow & Contouring in Radiotherapy Planning

How RAD365 Leveraged AI to Accelerate Radiotherapy Preparation

Client Overview

A group of oncology specialists was seeking to optimize their radiotherapy planning cycle. Manual organ segmentation in CT scans for contouring was time-consuming, error-prone, and fatiguing for radiologists, slowing down treatment initiation.

Objective

Automate organ segmentation during CT planning.

Ensure consistent contouring accuracy and reduce radiologist workload.

Shorten treatment planning timelines in oncology cases.

Solution: RAD365 integrated Deep Learning tools like Mirada DLC Expert into its radiology AI workflow:

  • Automated segmentation of organs-at-risk and target volumes.
  • Convolutional Neural Networks (CNN) trained on large image libraries.
  • Embedded AI into its internal Radiology Workflow Manager and Smart DICOM platforms.
  • Results were validated at academic and professional bodies including AAPM.

Results

Accelerated Planning Cycles

Reduced time required for contouring by up to 70%.

Precision & Consistency

AI-generated contours minimized variability and improved treatment accuracy.

Reduced Fatigue

Less manual effort allowed radiologists to focus on complex cases.

Clinical Adoption & Validation

Showcased successful implementation at professional radiotherapy forums.

Conclusion

By bringing AI into radiotherapy prep, RAD365 helped oncologists deliver faster, more precise cancer care. The project demonstrated that when advanced tech is paired with expert oversight, patient outcomes and provider productivity both improve.