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- W4232687376 abstract "To begin understanding the relationship between tau measured at autopsy and neuroimaging biomarkers in living subjects, we develop computational tools to quantify the 3D distribution of tau tangles together with MRI in a standard coordinate system. One ex vivo medial temporal lobe of an Alzheimer's disease patient was cut into three approximately 2cm slabs and imaged in an 11T MR scanner at 0.125 mm isotropic resolution. After imaging, tissue was cut into 10um sections every 1mm and stained for tau, amyloid, and myelin, and digitally imaged with a light microscope. Each histology image was aligned to other stains, to their neighboring slices, and to MRI simultaneously using a novel multi-modal registration algorithm. Each slab of tissue was aligned to its neighbors and to the Mai Paxinos atlas manually. In each section stained for tau, tangles (but not threads or plaques) were identified using a convolutional neural network. Training data was generated by manually identifying tangles, other tissue, or background on 10 randomly selected regions per slice, for a total of 2391 examples of which 500 were reserved for testing accuracy. Estimates of tangle density were generated for each page of the Mai atlas, and quantified for each subregion manually delineated by a neuroanatomist. Our simultaneous approach to alignment resulted in accurate 3D reconstructions, avoiding long range distortions that occur when stacking histology images alone. Our neural network discriminated between tau tangles, other tissue, and background with an accuracy of 99.6%. Aligned neuroimaging data, as well as tangle density estimates for each labeled tissue region are presented in the attached figure for one slice corresponding to page 36 of the Mai Paxinos atlas." @default.
- W4232687376 created "2022-05-12" @default.
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- W4232687376 date "2018-07-01" @default.
- W4232687376 modified "2023-10-16" @default.
- W4232687376 title "IC‐P‐061: QUANTIFICATION OF 3D TANGLE DISTRIBUTION IN MEDIAL TEMPORAL LOBE USING MULTIMODAL IMAGE REGISTRATION AND CONVOLUTIONAL NEURAL NETWORKS" @default.
- W4232687376 doi "https://doi.org/10.1016/j.jalz.2018.06.2126" @default.
- W4232687376 hasPublicationYear "2018" @default.
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