Soronow Alec L R, Jacobs Matthew W, Dickson Richard G, Kim Euiseok J
Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, California 95064.
Department of Molecular, Cell, and Developmental Biology, University of California, Santa Cruz, California 95064
eNeuro. 2025 Feb 5;12(2). doi: 10.1523/ENEURO.0036-23.2025. Print 2025 Feb.
For comprehensive anatomical analysis of a mouse brain, accurate and efficient registration of the experimental brain samples to a reference atlas is necessary. Here, we introduce Bell Jar, a semiautomated solution that can align and annotate tissue sections with anatomical structures from a reference atlas as well as detect fluorescent signals with cellular resolution (e.g., cell bodies or nuclei). Bell Jar utilizes Mattes mutual information-directed B-spline transformations to achieve precise alignments, even with damaged sample tissues. While user input remains a requirement for fine-tuning section matches, the platform streamlines the process, aiding rapid analyses in high-throughput neuroanatomy studies. As a standalone desktop application with a user-friendly interface, Bell Jar's performance, which surpasses traditional manual and existing automated methods, can improve the reproducibility and throughput of histological analyses.
为了对小鼠大脑进行全面的解剖分析，需要将实验性脑样本准确、高效地配准到参考图谱上。在此，我们介绍“钟罩”（Bell Jar），这是一种半自动化解决方案，它可以将组织切片与参考图谱中的解剖结构进行对齐和标注，并以细胞分辨率（如细胞体或细胞核）检测荧光信号。“钟罩”利用基于马特斯互信息引导的B样条变换来实现精确对齐，即使是对于受损的样本组织也能如此。虽然微调切片匹配仍需要用户输入，但该平台简化了流程，有助于在高通量神经解剖学研究中进行快速分析。作为一个具有用户友好界面的独立桌面应用程序，“钟罩”的性能超越了传统的手动方法和现有的自动化方法，可提高组织学分析的可重复性和通量。
