You are here

A user-friendly framework for interactive rendering of biological image volumes

Provides automatic visualization of features inside biological image volumes in 3D. The software provides a simple and interactive visualization for the exploration of biological datasets through dataset-specific transfer functions and direct volume rendering.

The method employs a K-Means++ clustering algorithm to classify a two-dimensional histogram created from the input volume. The classification process utilizes spatial and data properties from the volume. Then using properties derived from the classified clusters the software automatically generates color and opacity transfer functions and presents the user with a high quality initial rendering of the volume data. User input can be incorporated through the simple yet intuitive interface for transfer function manipulation included in our framework. Our new interface helps users focus on feature space exploration instead of the usual effort intensive, low-level widget manipulation.

Release Date:
October, 2012
Data type:
Windows, Mac OS X, Ubuntu

Project development

Institution: SAIC-Frederick Inc, KnowledgeVis LLC

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.