Rutgers University, Department of Biomedical Engineering, Piscataway, NJ 08854, USA.
Comput Med Imaging Graph. 2011 Oct-Dec;35(7-8):557-67. doi: 10.1016/j.compmedimag.2011.01.010. Epub 2011 Mar 11.
We present an interactive program called HistoStitcher(©) for accurate and rapid reassembly of histology fragments into a pseudo-whole digitized histological section. HistoStitcher(©) provides both an intuitive graphical interface to assist the operator in performing the stitch of adjacent histology fragments by selecting pairs of anatomical landmarks, and a set of computational routines for determining and applying an optimal linear transformation to generate the stitched image. Reconstruction of whole histological sections from images of slides containing smaller fragments is required in applications where preparation of whole sections of large tissue specimens is not feasible or efficient, and such whole mounts are required to facilitate (a) disease annotation and (b) image registration with radiological images. Unlike manual reassembly of image fragments in a general purpose image editing program (such as Photoshop), HistoStitcher(©) provides memory efficient operation on high resolution digitized histology images and a highly flexible stitching process capable of producing more accurate results in less time. Further, by parameterizing the series of transformations determined by the stitching process, the stitching parameters can be saved, loaded at a later time, refined, or reapplied to multi-resolution scans, or quickly transmitted to another site. In this paper, we describe in detail the design of HistoStitcher(©) and the mathematical routines used for calculating the optimal image transformation, and demonstrate its operation for stitching high resolution histology quadrants of a prostate specimen to form a digitally reassembled whole histology section, for 8 different patient studies. To evaluate stitching quality, a 6 point scoring scheme, which assesses the alignment and continuity of anatomical structures important for disease annotation, is employed by three independent expert pathologists. For 6 studies compared with this scheme, reconstructed sections generated via HistoStitcher(©) scored higher than reconstructions generated by an expert pathologist using Photoshop.
我们展示了一个名为 HistoStitcher(©)的交互式程序，用于将组织学碎片准确而快速地重新组装成一个伪全数字化的组织学切片。HistoStitcher(©) 提供了一个直观的图形界面，以帮助操作员通过选择一对解剖学标志来执行相邻组织学碎片的拼接，并且提供了一组计算例程，用于确定并应用最佳线性变换以生成拼接图像。在无法或效率不高的情况下制备大组织标本的全切片时，需要从小的切片图像重建全组织切片，并且需要这种全切片来促进 (a) 疾病标注和 (b) 与放射图像的图像配准。与在通用图像编辑程序（如 Photoshop）中手动重新组装图像碎片不同，HistoStitcher(©) 提供了对高分辨率数字化组织学图像的高效内存操作，以及一种高度灵活的拼接过程，能够在更短的时间内产生更准确的结果。此外，通过参数化拼接过程中确定的一系列变换，可以保存拼接参数，以后加载、细化或重新应用于多分辨率扫描，或快速传输到另一个站点。在本文中，我们详细描述了 HistoStitcher(©) 的设计和用于计算最佳图像变换的数学例程，并展示了其用于拼接前列腺标本的高分辨率组织学象限以形成数字化重新组装的全组织学切片的操作，共 8 个不同的患者研究。为了评估拼接质量，使用了一个 6 分评分方案，该方案评估了对于疾病标注重要的解剖结构的对齐和连续性，由三位独立的专家病理学家进行评估。对于与该方案比较的 6 项研究，通过 HistoStitcher(©) 生成的重建切片的得分高于专家病理学家使用 Photoshop 生成的重建切片。
