GPU-Enabled Volume Renderer for Use with MATLAB

Traditional tools, such as 3D Slicer, Fiji, and MATLAB<sup>®</sup>, often encounter limitations in rendering performance and data management as the dataset sizes increase. This work presents a GPU-enabled volume renderer with a MATLAB<sup>®</sup> interface that addresses thes...

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Main Author: Raphael Scheible
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Digital
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Online Access:https://www.mdpi.com/2673-6470/4/4/49
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author Raphael Scheible
author_facet Raphael Scheible
author_sort Raphael Scheible
collection DOAJ
description Traditional tools, such as 3D Slicer, Fiji, and MATLAB<sup>®</sup>, often encounter limitations in rendering performance and data management as the dataset sizes increase. This work presents a GPU-enabled volume renderer with a MATLAB<sup>®</sup> interface that addresses these issues. The proposed renderer uses flexible memory management and leverages the GPU texture-mapping features of NVIDIA devices. It transfers data between the CPU and the GPU only in the case of a data change between renderings, and uses texture memory to make use of specific hardware benefits of the GPU and improve the quality. A case study using the ViBE-Z zebrafish larval dataset demonstrated the renderer’s ability to produce visualizations while managing extensive data effectively within the MATLAB<sup>®</sup> environment. The renderer is available as open-source software.
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spelling doaj-art-dc5b71f625b7457db9b343d7606005cc2025-08-20T02:55:45ZengMDPI AGDigital2673-64702024-11-0144990100710.3390/digital4040049GPU-Enabled Volume Renderer for Use with MATLABRaphael Scheible0Institute of Artificial Intelligence and Informatics in Medicine, University Hospital Rechts der Isar, Technical University of Munich, 81675 Munich, GermanyTraditional tools, such as 3D Slicer, Fiji, and MATLAB<sup>®</sup>, often encounter limitations in rendering performance and data management as the dataset sizes increase. This work presents a GPU-enabled volume renderer with a MATLAB<sup>®</sup> interface that addresses these issues. The proposed renderer uses flexible memory management and leverages the GPU texture-mapping features of NVIDIA devices. It transfers data between the CPU and the GPU only in the case of a data change between renderings, and uses texture memory to make use of specific hardware benefits of the GPU and improve the quality. A case study using the ViBE-Z zebrafish larval dataset demonstrated the renderer’s ability to produce visualizations while managing extensive data effectively within the MATLAB<sup>®</sup> environment. The renderer is available as open-source software.https://www.mdpi.com/2673-6470/4/4/49imagingthree-dimensionalbiomedical image processingmedical image processingvisualizationdirect volume rendering
spellingShingle Raphael Scheible
GPU-Enabled Volume Renderer for Use with MATLAB
Digital
imaging
three-dimensional
biomedical image processing
medical image processing
visualization
direct volume rendering
title GPU-Enabled Volume Renderer for Use with MATLAB
title_full GPU-Enabled Volume Renderer for Use with MATLAB
title_fullStr GPU-Enabled Volume Renderer for Use with MATLAB
title_full_unstemmed GPU-Enabled Volume Renderer for Use with MATLAB
title_short GPU-Enabled Volume Renderer for Use with MATLAB
title_sort gpu enabled volume renderer for use with matlab
topic imaging
three-dimensional
biomedical image processing
medical image processing
visualization
direct volume rendering
url https://www.mdpi.com/2673-6470/4/4/49
work_keys_str_mv AT raphaelscheible gpuenabledvolumerendererforusewithmatlab