Scherf Heike, Tilgner Rico
Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.
Am J Phys Anthropol. 2009 Sep;140(1):39-51. doi: 10.1002/ajpa.21033.
In the last decade, high-resolution computed tomography (CT) and microcomputed tomography (micro-CT) have been increasingly used in anthropological studies and as a complement to traditional histological techniques. This is due in large part to the ability of CT techniques to nondestructively extract three-dimensional representations of bone structures. Despite prior studies employing CT techniques, no completely reliable method of bone segmentation has been established. Accurate preprocessing of digital data is crucial for measurement accuracy, especially when subtle structures such as trabecular bone are investigated. The research presented here is a new, reproducible, accurate, and fully automated computerized segmentation method for high-resolution CT datasets of fossil and recent cancellous bone: the Ray Casting Algorithm (RCA). We compare this technique with commonly used methods of image thresholding (i.e., the half-maximum height protocol and the automatic, adaptive iterative thresholding procedure). While the quality of the input images is crucial for conventional image segmentation, the RCA method is robust regarding the signal to noise ratio, beam hardening, ring artifacts, and blurriness. Tests with data of extant and fossil material demonstrate the superior quality of RCA compared with conventional thresholding procedures, and emphasize the need for careful consideration of optimal CT scanning parameters.
在过去十年中，高分辨率计算机断层扫描（CT）和微型计算机断层扫描（micro-CT）在人类学研究中得到了越来越广泛的应用，并作为传统组织学技术的补充。这在很大程度上归因于CT技术能够无损地提取骨结构的三维表示。尽管先前有研究采用CT技术，但尚未建立完全可靠的骨分割方法。数字数据的准确预处理对于测量精度至关重要，尤其是在研究诸如松质骨等细微结构时。本文提出的研究是一种针对化石和现代松质骨的高分辨率CT数据集的全新、可重复、准确且完全自动化的计算机化分割方法：射线投射算法（RCA）。我们将该技术与常用的图像阈值化方法（即半最大高度协议和自动、自适应迭代阈值化程序）进行比较。虽然输入图像的质量对于传统图像分割至关重要，但RCA方法在信噪比、束硬化、环形伪影和模糊度方面具有鲁棒性。对现存和化石材料数据的测试表明，与传统阈值化程序相比，RCA具有更高的质量，并强调需要仔细考虑最佳CT扫描参数。
