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Layer-based visualization and biomedical information exploration of multi-channel large histological data.

Authors
  • Zhang, Qi1
  • Peters, Terry2
  • Fenster, Aaron3
  • 1 School of Information Technology, Illinois State University, 100 North University Street, Normal, IL 61761, United States; Department of Medical Biophysics, Western University, London, Ontario, Canada N6A 5C1. Electronic address: [email protected] , (Canada)
  • 2 Robarts Research Institute, Western University, 1151 Richmond St. N., London, Ontario, Canada N6A 5B7; Department of Medical Biophysics, Western University, London, Ontario, Canada N6A 5C1. Electronic address: [email protected] , (Canada)
  • 3 Robarts Research Institute, Western University, 1151 Richmond St. N., London, Ontario, Canada N6A 5B7; Department of Medical Biophysics, Western University, London, Ontario, Canada N6A 5C1. Electronic address: [email protected] , (Canada)
Type
Published Article
Journal
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Publication Date
Mar 01, 2019
Volume
72
Pages
34–46
Identifiers
DOI: 10.1016/j.compmedimag.2019.01.004
PMID: 30772074
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Modern microscopes can acquire multi-channel large histological data from tissues of human beings or animals, which contain rich biomedical information for disease diagnosis and biological feature analysis. However, due to the large size, fuzzy tissue structure, and complicated multiple elements integrated in the image color space, it is still a challenge for current software systems to effectively calculate histological data, show the inner tissue structures and unveil hidden biomedical information. Therefore, we developed new algorithms and a software platform to address this issue. This paper presents a multi-channel biomedical data computing and visualization system that can efficiently process large 3D histological images acquired from high-resolution microscopes. A novelty of our system is that it can dynamically display a volume of interest and extract tissue information using a layer-based data navigation scheme. During the data exploring process, the actual resolution of the loaded data can be dynamically determined and updated, and data rendering is synchronized in four display windows at each data layer, where 2D textures are extracted from the imaging volume and mapped onto the displayed clipping planes in 3D space. To test the efficiency and scalability of this system, we performed extensive evaluations using several different hardware systems and large histological color datasets acquired from a CryoViz 3D digital system. The experimental results demonstrated that our system can deliver interactive data navigation speed and display detailed imaging information in real time, which is beyond the capability of commonly available biomedical data exploration software platforms. Taking advantage of both CPU (central processing unit) main memory and GPU (graphics processing unit) graphics memory, the presented software platform can efficiently compute, process and visualize very large biomedical data and enhance data information. The performance of this system can satisfactorily address the challenges of navigating and interrogating volumetric multi-spectral large histological image at multiple resolution levels. Copyright © 2019 Elsevier Ltd. All rights reserved.

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