Optimal segmentation of microcomputed tomographic images of porous tissue-engineering scaffolds
Optimal segmentation of microcomputed tomographic images of porous tissue-engineering scaffolds
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DOI：
10.1002/jbm.a.30498
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发表时间：
2005-12-15
影响因子：
4.9
通讯作者：
Robb, RA
中科院分区：
文献类型：
--
作者：
Rajagopalan, S;Lu, LC;Robb, RA
多孔组织工程支架的形态计量学特性在细胞的初始附着和随后的组织再生中起着主导作用。这些特性可以通过使用支架的高分辨率微计算机断层扫描(MU CT)成像的定量分析来非破坏性地获得。准确地将这些采集到的图像分割成固体和多孔子空间对于形态计量分析的完整性至关重要。缺乏一种单一的图像处理技术来提供如此准确的可分离性，而不受所获得数据的所有错综复杂的影响，这使得这项看似简单的任务极易出错。因此，必须通过对由多种方法产生的分割进行排序来选择最佳分割。本文提出了一种健壮的、易于实现的、无歧义的、基于信号处理的、与地面真实情况无关的、与视觉锐度相关的分割评级度量。通过使用该度量，第一次有可能用广泛的技术对数据进行阈值，并自动选择最能描绘所采集图像的技术。所提出的解决方案已经在可生物降解的聚富马酸丙酯(PPF)(PPF)制成的支架的muCT图像上进行了广泛的测试，使用的是溶剂浇铸颗粒浸出工艺。所提出的方法和所获得的结果可能对基于图像的组织工程支架的准确表征具有深远的意义。(C)2005年威利期刊公司。
The morphometric properties of the porous tissue-engineering scaffolds play a dominant role in the initial cell attachment and Subsequent tissue regeneration. These properties can be derived nondestructively with the use of quantitative analysis of high-resolution microcomputed tomography (mu CT) imaging of scaffolds. Accurate segmentation of these acquired images into solid and porous subspaces is critical to the integrity of morphometric analysis. The absence of a single image-processiiig technique to provide Such accurate separability immune to all the intricacies of the acquired data makes this seemingly simple task significantly error prone. Consequently, in optimal segmentation has to be selected by ranking the segmentations produced by a multiplicity of methods. This article proposes a robust, easy-to-implement, unambiguous, signal-processing-based, ground-truth-free, segmentation rating metric that correlates with Visual acuity. With the use of this metric it is possible, for the first time, to threshold the data with a wide range of techniques and Select automatically the technique that best delineates the acquired image. The proposed Solution has been extensively tested on mu CT images of scaffolds fabricated with biodegradable poly (propylene fumarate) (PPF) with the use of a solvent casting particulate leaching process. The approaches proposed and the results obtained may have profound implications for accurate image-based characterization of tissue-engineering scaffolds. (c) 2005 Wiley Periodicals, Inc.