Manuals

1. Medicalholodeck
1.1 Main control pad
1.1.1 Library 1.1.2 Jump 1.1.3 4D Record 1.1.4 TeamXR 1.1.5 Remote Render 1.1.6 Settings 1.1.7 Reset workspace 1.1.8 Undo 1.1.9 Redo 1.1.10 Exit 1.1.11 Capture a movie 1.1.12 Take a photo 1.1.13 Handle
1.2 Object pad
1.2.1 Cutter 1.2.2 Laser 1.2.3 Masking 1.2.4 Measure area 1.2.5 Measure distance 1.2.6 Delete 1.2.7 Scale 1.2.8 Move 1.2.9 Move backward 1.2.10 Frame rate 1.2.11 Remove dataset 1.2.12 Light on/off 1.2.13 Measure angle 1.2.14 Draw 1.2.15 Marker 1.2.16 Rotate horizontally 1.2.17 Rotate vertically
1.3 Library panel
1.3.1 Saved scenes 1.3.2 Medical Imaging 1.3.3 RecordXR 1.3.4 Dissection Master 1.3.5 Anatomy Master
1.4 Object marker
1.4.1 Center 1.4.2 Lock 1.4.3 Delete 1.4.4 Groups 1.4.5 Cuts visibility
1.5 Lighting
1.5.1 Light 1.5.2 Light Marker
1.6 Controllers
1.6.1 Left controller 1.6.2 Right controller
1.7 Settings
1.7.1 Settings 1.7.2 Licenses 1.7.3 PACS 1.7.4 Services
1.8 Quality settings
1.8.1 Medical imaging settings 1.8.2 Low framerate screen 1.8.3 About 3D DICOM files 1.8.4 Processing and texturing 1.8.5 Challenges with large datasets in VR 1.8.6 Adaptive detail rendering
1.9 Tutorials
1.9.1 Activate licenses 1.9.2 Use Your Hands To Navigate in VR 1.9.3 Capture Screenshots and Videos
2. Medical Imaging
2.1 User interface
2.1.1 Import 2.1.2 Save 2.1.3 Export 2.1.4 Load data 2.1.5 Delete data
2.2 Medical Imaging panel
2.2.1 Option preset 2.2.2 Transfer function 2.2.3 Tissue filter 2.2.4 Transfer function preset 2.2.5 Mesh generator 2.2.6 Edge filter 2.2.7 Quality settings 2.2.8 Handle
2.3 Tutorials
2.3.1 Import and display data 2.3.2 Importing data on standalone devices 2.3.3 Edit DICOM 2.3.4 Measure, mark and draw on DICOM
3. Medicalholodeck AI
3.1 What is AI segmentation? 3.2 How to run AI segmentation in the cloud? 3.3 How to run AI segmentation on your device?
3.4 How to use the segmentation control panel?
3.4.1 Structure 3.4.2 Options
3.5 How to install TotalSegmentator?
3.5.1 Installing Python 3.5.2 Installing PyThorch 3.5.3 Installing TotalSegmentator
4. Dissection Master
4.1 Model
4.1.1 Changing layers 4.1.2 Scaling 4.1.3 Moving 4.1.4 Rotating 4.1.5 Annotations 4.1.6 Visibility Controls
5. Anatomy Master
5.1 Model
5.1.1 Scaling 5.1.2 Taking apart 5.1.3 Moving 5.1.4 Rotating 5.1.5 Cutting 5.1.6 Annotations 5.1.7 Visibility controls
6. RecordXR
6.1 User interface
6.1.1 Main control pad 6.1.2 RecordXR panel 6.1.3 Library panel
7. RecordXR Studio
7.1 Editing tools
7.1.1 Preview window 7.1.2 Timeline toolbar 7.1.3 Timeline
7.2 Metadata section
7.2.1 Title 7.2.2 Avatar 7.2.3 Preview icons 7.2.4 Duration 7.2.5 Description
7.3 Project controls
7.3.1 Save project 7.3.2 Export RXR 7.3.3 Close
7.4 Tutorials
7.4.1 Get records from Medicalholodeck 7.4.2 Open RecordXR Studio 7.4.3 Open a project 7.4.4 Add recordings 7.4.5 Zoom in/zoom out 7.4.6 Change the order 7.4.7 Trim 7.4.8 Set the metadata 7.4.9 Add an avatar 7.4.10 Saving the project 7.4.11 Export a .RXR file 7.4.12 Exit the platform 7.4.13 Open the recording
8. Link
8.1 Device dashboard
8.1.1 Device bar 8.1.2 License management 8.1.3 Datasets 8.1.4 RecordXR 8.1.5 Presets 8.1.6 Transfer Functions 8.1.7 Upload
8.2 Tutorials
8.2.1 How to add your device 8.2.2 Activating a license via Link 8.2.3 Uploading data from your computer to your headset 8.2.4 Accessing files via Link

8. Quality settings

Learn how to adjust quality settings and improve performance on both PC-VR and standalone devices. 3D DICOM data is volumetric - so the larger you scale it or the closer you get in VR, the more processing power your device needs. Only the models and data in your field of view are rendered.

Below, we show you how to optimize DICOM visualization for better performance on your VR system.

8.1

Medical imaging settings in Medicalholodeck

Quality settings help balance performance and visual clarity. If your device slows down with large and numerous files, lowering the quality can help it run more smoothly.

You can adjust quality settings for each individual model. Look for quality for volumes and data resolution at the bottom of the Medical Imaging XR panel, numbers 6 and 7. Use the quality for volumes slider to adjust the density of the volume. Select the data resolution setting to choose between low, medium, or high texture quality.

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Note that quality settings above 50% offer only small visual improvements but require significantly more performance.

You can set default rendering options in the settings panel on the left. These apply when loading a new model. Medicalholodeck’s recommended defaults are 10–14% volume quality and medium resolution for headsets, and 50% volume quality with full resolution for PCs.

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8.2

Low framerate screen

You can keep an eye on your device's performance by checking the frames per second (FPS), shown in the top-right corner of the object pad. It shows how many images your device displays each second - higher FPS means smoother motion in VR.

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If the FPS drops below 10, a low FPS warning screen will appear to help protect your device. This gives your system a chance to recover and avoid becoming unresponsive or overheating. It’s also a sign that you may need to lower the rendering quality. This screen isn’t just a warning - it’s there to help prevent crashes and keep everything running smoothly.

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When this screen appears, you can:


  • Continue if your device can handle it.

  • Reset the workspace to remove all loaded data.

Then, adjust your quality settings to optimize performance.

8.3

About 3D DICOM files

Data resolution

In volumetric imaging, resolution controls how sharp and detailed each slice appears. Users can manually select between low, medium, and high texture versions, depending on their performance needs and visual preferences.

Volumetric quality


The volume quality slider controls how much of the dataset is actively used during rendering:


  • 50% Setting: Uses all key slices from the original DICOM dataset, balancing performance and visual quality.

  • Above 50%: Uses more slices from the dataset for slightly better image quality, but the improvements are minimal and require significantly more performance.

  • Below 50%: Fewer slices are used, reducing visual precision but improving performance.

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What is volumetric data?


Volumetric data represents 3D anatomical structures by stacking 2D image slices, typically obtained through CT or MRI scans. Each slice captures a thin cross-section of the body at specific intervals. When combined these slices form a full 3D volume. These datasets are usually stored in the DICOM format, which includes both the images and the metadata needed to interpret them properly.

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8.4

From slices to 3D visualization: processing and texturing

Visualizing volumetric data in VR involves sophisticated processing techniques. Texture maps are applied to each 2D slice, and algorithms interpolate between them to generate a smooth, continuous 3D representation. The more slices included-and the higher their resolution-the more detailed the final rendering. However, this increased fidelity comes with a computational cost.

Processing involves two key factors:


  • Slice density: The number of slices in a dataset.

  • Texture resolution: The visual clarity of each slice.

Together, these determine how “complete” and realistic the 3D volume appears. A denser dataset with high-resolution textures offers more anatomical detail but requires more GPU and CPU power to render.

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8.5

Challenges with large datasets in VR

Unlike conventional 2D image viewing, real-time 3D rendering in VR must maintain high frame rates (ideally 60 FPS on a PC, 30 on a standalone headset) to prevent motion sickness and ensure a smooth experience. Large volumetric datasets, while visually impressive, can overwhelm hardware if not managed properly. The larger the dataset - in physical dimensions, not just file size - the more processing power is required to render it effectively. This is where smart optimization and quality settings become essential.

8.6

Adaptive detail rendering

To balance performance with visual quality, VR systems use level of detail (LOD) techniques that adjust rendering based on the user’s distance from the dataset. When the user is close, the system displays high detail; when farther away, it switches to lower-resolution textures, since fine details aren’t noticeable at a distance. This approach preserves meaningful content while optimizing performance.

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