Boosting Large Multidimensional Bioimage Visualization and Analysis: Vaa3D and Applications

Tutorial Description

Multidimensional biomedical images are indispensable data resources in current biology and medicalscience. However, a common bottleneck is the inability to efficiently explore the complicated 3D image content and thus to input user-specified information of the observed image patterns directly in the 3D space. This presents an obstacle for the unbiased, high-throughput and quantitative analysis of bioimage data and creates tremendous need for the development of new techniques that help explore large 3D data directly and efficiently without expensive virtual reality devices and/or parallel computing infrastructures.

This tutorial will focus on the open-source, cross-platform Vaa3D system and several of its recent developments specifically designed for bridging such gaps, particularly for the tasks of visualization, interaction, analysis and management of large-scale and very large-scale (terabyte-size images) multidimensional (including 3D, 4D and 5D) images on computers or in virtual reality (VR). We will demonstrate that Vaa3D can be generally useful for both microscopy and biomedical images and also for surface object visualization problems.

We will provide a guided and interactive tour of the several popular features of Vaa3D and present the methods involved ‘behind the scenes’ (e.g. how to map a computer mouse click/stroke to the corresponding biological entity in the 3D image) and “inside the scenes’ (e.g. how to manipulate 3D image in virtual space). All the applications considered will be demonstrated live using a common laptop/VR and, when possible, reproduced by the participants on their own laptops.

Outline

Introduction (from 2D to 3D visualization);
Data management for large-scale biomedical images (TeraFly and TeraConverter);
Multidimensional medical and microscopy image visualization;
Generation, quantification, measurement and annotation of 3D surface meshes;
Turning the computer mouse into a 3D Virtual Finger;
Image processing functionalities (segmentation, registration, filtering, profiling, etc.);
Automatic neuron reconstruction;
Smart imaging techniques for large-scale biomedical images;
Plugin generation (live demo + developers hands-on);
Visualization and annotation of terabyte-scale image data on computers (live demo + general users hands-on);
Visualization and annotation of terabyte-scale image data in VR (live demo + general users hands-on).

Learning objectives

Participants will learn how to use Vaa3D to visualize and analyze multidimensional medical and microscopy image;
Participants will learn how to use various image processing functionalities in Vaa3D;
Participants with programming background will learn how to take advantage from the powerful Vaa3D features by developing customized plugins;
Participants will learn how to manage large-scale biomedical images on computers/VR.

Materials To Be Distributed

All related materials can be accessed from our GitHub wiki page (https://github.com/Vaa3D/Vaa3D_Wiki/wiki/Vaa3D-Wiki).

Organizations

Institute for Brain and Intelligence, Southeast University, Nanjing, China
Southeast University – Allen Institute Joint Center, Southeast University, Nanjing, China

Organizers

Zhi Zhou, Ph.D. Allen Institute for Brain Science, Seattle, U.S.A. Email: alan.zhizhou@gmail.com
Yimin Wang, Ph.D. Shanghai University, Shanghai, China. Email: y_wang@shu.edu.cn
Lijuan Liu, Ph.D. Southeast University, Nanjing, China. Email: lijuan-liu@seu.edu.cn

Main Speakers

Yimin Wang, Ph.D.

Dr. Yimin Wang is with Shanghai University, China. His research interests visualization, processing, and analytics of large-scale imaging data. He is an active developer for Vaa3D and his recent work includes a virtual reality neuron reconstructions system based on Vaa3D.

Lijuan Liu, Ph.D.

Dr. Lijuan Liu is an associate research fellow at the Southeast University, Nanjing, China. She is the leader of Annotation group in Southeast University-Allen Institute Joint center for neuron morphology. Recently her research interest is identification of neuronal cell types in thalamus.

Peng Xie, Ph.D.

Dr. Xie is a scientist at the Allen Institute for Brain Science, Seattle, USA. His major research interest is to understand the neuronal morphology from a data-driven perspective. Through comparison of neuron morphology data across brain structures and across species, he pursues the goal of understanding the designing logic and functional implication of neuronal pattern formation.

Liya Ding, Ph.D.

Dr. Liya Ding is an associate research professor in the Brain and Intelligence Institute of Southeast University, Nanjing China. Her field of research is computer vision. Her recent focuses are biomedical image processing and 3D structure reconstruction from microscopy images.

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