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ProductsDeep Learning Planning

Public source

Reviewed 7 Aug 2026

Completeness Good (44%)

Deep Learning Planning

RaySearch Laboratories

Deep learning planning enhances the planning workflow by automating the creation of personalized treatment plans, significantly reducing the time required compared to manual treatment planning. This technology leads to more consistent and reproducible planning results, promoting a more standardized approach to patient care.

No papers to support — we monitor for new evidence.

Key features

Dose prediction

General Information

Product name

Deep Learning Planning

Workflow phase

Planning

Modality

CT

Treatment site

Brain/CNS, Breast, Head & neck, Thorax

Exact structures

Brain/CNS: Brain (Proton) | Head & Neck: oropharynx (Proton) | Breast: Left (SMLC), Locoregional Right (SMLC), Locoregional (SMLC) | Thorax: Lungs (SBRT, Proton) | Pelvis: Prostate (VMAT), Rectum (VMAT)

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class unknown

Not verified by Health AI Register

FDA Certification

Pathway:

510(k) cleared

Class:

Class II

FDA Number:

K222312

View FDA record

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

No research papers or evidence on file yet.

The registry monitors publications for new evidence.

Technical Specifications

Prerequisites

Specific TPS required

Defined prerequisite(s)

RayStation

Treatment technique

Pencil beam scanning, Proton therapy, SBRT, SMLC, VMAT

Delivery system

Linac, Proton system

Workflow features

Not applicable

Patient population age

Adult

Input

3D binary masks

Input format

Not specified

Output

3D voxel level dose distribution

Output format

Not specified

Integration

Integrated in TPS

Integration method

Not specified

API documentation availability

Not specified

API documentation, if publicly available

Not specified

TPS compatibility

RayStation

Deployment

Not specified

Trigger for AI functionality

On demand, triggered by a user through e.g. a button click, image upload

Processing time

Not specified

Retraining locally

Not specified

Claims

Not specified

Known limitations

Not specified

Market Presence

On market since

Not specified

AI Platforms

Resellers

Not specified

Countries present

Not specified

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Not specified

Based on

Not specified

Source: Public | First published: Mar 27, 2026 | Last updated: Aug 7, 2026