Interactive Histology of Large-Scale Biomedical Image Stacks
Interactive Histology of Large-Scale Biomedical Image Stacks
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DOI：
10.1109/tvcg.2010.168
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发表时间：
2010-11-01
影响因子：
5.2
通讯作者：
Pfister, Hanspeter
中科院分区：
文献类型：
--
作者：
Jeong, Won-Ki;Schneider, Jens;Pfister, Hanspeter
组织学是利用显微镜技术研究生物组织结构的学科。随着数字成像技术的进步，大体积组织的高分辨率显微镜变得可行。然而，需要新的交互式工具来探索和分析庞大的数据集。在本文中，我们提出了一个可视化框架，专门针对任意大图像堆栈的交互式检查。我们的框架基于两项核心技术：显示感知处理和 GPU 加速纹理压缩。通过显示感知处理，仅实时获取和对齐当前可见的图像图块，从而减少内存带宽并最大限度地减少耗时的全局预处理的需要。我们新颖的 GPU 纹理压缩方案专为快速浏览图像堆栈而定制。我们评估了查看器在两种组织学应用中的可用性：数字病理学和串行电子显微照片中纳米级分辨率的神经结构可视化。
Histology is the study of the structure of biological tissue using microscopy techniques. As digital imaging technology advances, high resolution microscopy of large tissue volumes is becoming feasible; however, new interactive tools are needed to explore and analyze the enormous datasets. In this paper we present a visualization framework that specifically targets interactive examination of arbitrarily large image stacks. Our framework is built upon two core techniques: display-aware processing and GPU-accelerated texture compression. With display-aware processing, only the currently visible image tiles are fetched and aligned on-the-fly, reducing memory bandwidth and minimizing the need for time-consuming global pre-processing. Our novel texture compression scheme for GPUs is tailored for quick browsing of image stacks. We evaluate the usability of our viewer for two histology applications: digital pathology and visualization of neural structure at nanoscale-resolution in serial electron micrographs.