CryoCloud v2.23 – Faster Map Visualisation, New Results Plots & Workflow Updates

Automatic volume resizing for faster map loading, expanded results visualisation, and improved dataset browsing. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏

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Hi there,

We’re pleased to share CryoCloud version 2.23.

This release introduces faster map visualisation through automatic volume resizing, expands visual outputs available directly in results pages, and delivers improvements to workflows, dataset handling, and platform performance.

🚀 New Features

Expanded results visualisation

We have added additional visual outputs directly to job result pages.

For example, FSC curves are now visible directly in Refine3D and PostProcess job results, making it easier to inspect reconstruction quality without downloading files.

In addition, Class3D and Refine3D job results also include angular distribution plot. This needs to be selected from the Volume Viewer as an additional layer

We will continue expanding embedded visualisations across additional jobs. If there are additional result pages you would like visualisation added to, let us know at support@cryocloud.io.

Faster map visualisation with automatic volume resizing

To improve responsiveness when inspecting maps, CryoCloud now automatically generates cropped and downsampled variants of output volumes.

This applies to Class3D, Refine3D, PostProcess and Mask creation jobs. The UI loads these optimised maps by default, allowing significantly faster visualisation in the browser. The original full-resolution maps remain available and can still be downloaded or explicitly loaded when needed.

✨ Improvements

Faster dataset auto-detection

Dataset auto-detection has been optimised for large datasets, improving reliability and reducing processing time when importing new data.

🐛 Bug Fixes

Improved reliability of dataset auto-detection
Fixed file listing limits when browsing large datasets
Improved handling of dataset sources in bucket root directories
Fixed page reset behaviour in target reference tables
Various stability and validation fixes across dataset import and processing workflows

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