Rossetti Blair J, Wang Fusheng, Zhang Pengyue, Teodoro George, Brat Daniel J, Kong Jun
Department of Biomedical Informatics, Emory University, Atlanta, GA, 30322, USA.
Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794, USA.
Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:424-428. doi: 10.1109/ISBI.2017.7950552. Epub 2017 Jun 19.
High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the direct application of conventional registration techniques. In this paper, we develop a three-stage registration with multi-resolution mapping and propagation method to dynamically produce registered subvolumes from serial whole slide images. We validate our algorithm with gigapixel images of serial brain tumor sections and synthetic image volumes. The qualitative and quantitative assessment results demonstrate the efficacy of our approach and suggest its promise for 3D histology reconstruction analysis.
高通量连续组织学成像为在三维空间中对微观解剖结构进行常规研究提供了一条新途径。然而,连续全切片成像的出现带来了新的配准挑战,因为数十亿像素的图像尺寸使得传统配准技术无法直接应用。在本文中,我们开发了一种具有多分辨率映射和传播方法的三阶段配准方法,以从连续全切片图像中动态生成配准后的子体积。我们使用连续脑肿瘤切片的数十亿像素图像和合成图像体积对我们的算法进行了验证。定性和定量评估结果证明了我们方法的有效性,并表明其在三维组织学重建分析中的前景。