SliceMap: an algorithm for automated brain region annotation.

Area of Science:

• Neuroscience
• Computational Biology
• Medical Imaging

Background:

• Neurodegenerative diseases affect specific brain regions, necessitating precise analysis in animal models.
• Accurate staging and therapy assessment in transgenic mice require automated quantification of selected brain areas.

Purpose of the Study:

• To develop an automated algorithm, SliceMap, for contextual quantification of microtome-cut brain slices.
• To enable accurate, region-based analysis of neurodegenerative disease progression in mouse models.

Main Methods:

• SliceMap algorithm performs coarse congealing-based registration to reference slices.
• Refined elastic registration uses optimally matching reference slices.
• Morphotextural metrics assess registration performance and detect poorly cut slices.

Main Results:

• SliceMap enables contextual quantification by mapping anatomical information onto brain slices.
• The method was implemented as a FIJI plugin for image analysis.
• Regional quantification of tau pathology in a tauopathy mouse model was successfully performed.

Conclusions:

• SliceMap facilitates accurate, region-based quantification of brain slices.
• This contributes to more precise assessment of neurodegenerative disease development and therapeutic responses.
• The tool aids in advancing research for diseases like Alzheimer's Disease.