Amyloid plaque deposits in the brain are indicative of Alzheimer’s and other diseases. Measurements of brain amyloid burden in small animals require laborious post-mortem histological analysis or resource-intensive, contrast-enhanced imaging techniques. We describe a label-free method based on spectral...
A specific architecture, namely multi-scale structured convolutional neural networks (MS-CNN), is designed to capture discriminative features for each sub-cortical structure and to generate a label probability map for the target image. Due to complex background in brain images and the lack of ...
Spectral PACT studies indicate that structural contrasts mainly originate from cytochrome distribution and that the presence of lipid sharpens the image contrast; brain histology results provide further validation. The feasibility of imaging the structure of the brain in vivo is also discussed. Our ...
They are characterized by progressive damage to the structure and function of neurons and the accumulation of misfolded proteins in specific brain regions and neuronal populations3,4,5,6. Although these misfolded protein aggregates represent the hallmark of several NDDs, including AD, PD, and HD, ...
However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer ...
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During the Renaissance(文艺复兴), the French doubter Michel de Montaigne (1533 - 1592) was one of the first to critically look at education. Unusually for his time, Montaigne was willing to question the conventional wisdom of the period, calling into question the whole structure of the educati...
A specific architecture, namely multi-scale structured convolutional neural networks (MS-CNN), is designed to capture discriminative features for each sub-cortical structure and to generate a label probability map for the target image. Due to complex background in brain images and the lack of ...
·Ns), whereNl=|Y|. Such increment results in greater model complexity and requires more training data. A solution for a Hidden Markov Model (HMM) with a similar structure of the state space was proposed by Ghahramani and Jordan [16], where multiple cotemporal state variables (h1,t,h2,...
27 proposed a convolutional neural network model combining convolution and prior spatial features for sub-cortical brain structure segmentation and trained the network using a restricted sample selection to increase segmentation accuracy. Brain tissue boundary regions are difficult to segment for both the ...