Tracing and analysis of the whole mouse brain vasculature with systematic cleaning to remove and consolidate erroneous images.

Abstract

Whole mouse brain microvascular images at submicrometer scale can be obtained by Knife-Edge Scanning Microscopy (KESM). However, due to the large size of the image dataset and the noise from the serial sectioning process of the KESM, whole mouse brain vascular reconstruction and analysis with submicrometer resolution have not been achieved yet, while several previous studies demonstrated manually selected small noise-free portion of the KESM dataset. In addition to the KESM dataset, there have been studies for vessel reconstruction and analysis of the whole mouse brain at lower resolution or of partial brain regions at submicrometer resolution. However, to the best of our knowledge, there has been no study for vessel reconstruction and analysis of the whole mouse brain at submicrometer resolution. In this paper, we propose a framework for the 3D reconstruction and analysis of the whole KESM mouse brain vasculature dataset with rich vasculature information extracted at submicrometer resolution. The framework consists of two methods. The propose methods provide the systematic cleaning to remove and consolidate erroneous images automatically, which enables the full tracing and analysis of the whole KESM mouse brain dataset with richer vasculature information.