Brain white matter fiber deep clustering method guided by tag-fMRI

Abstract

The invention belongs to a clustering method of brain white matter fibers, and particularly relates to a tamp-. The invention discloses a brain white matter fiber deep clustering method guided by fMRI. Task-is used for carrying out deep clustering on brain white matter fibers. FMRI data are used for obtaining functional information of the white matter fibers, meanwhile, DTI data are used for obtaining structural information of the white matter fibers, the functional information and the structural information are combined to represent one white matter fiber, and the white matter fiber serves asinput of the embedded clustering convolution automatic encoder to be clustered. According to the method disclosed by the invention, the average tag-on the fiber track is extracted; the fMRI signal represents a fiber, and the result of the clustering is further structurally restricted and optimized in combination with the structure information from the DTI data. Jointly inputting the two types ofinformation into a CAEEC (convolutional autoencoder) of an embedded cluster to generate a clustered fiber bundle, and in the CAEC training process, optimizing the training process by combining reconstruction-oriented loss, clustering-oriented loss and sparse regularization items; the hierarchical structure of the fiber can be better extracted by the convolutional automatic encoder embedded with the cluster, and the local features of the data are reserved in the feature space.

Description

technical field [0001] The invention belongs to the field of medical image processing and deep learning, and in particular relates to a method for deep clustering of brain white matter fibers guided by task-fMRI. Background technique [0002] In recent years, with the development of Diffusion Tensor Imaging (DTI) technology, researchers can use Tractography to infer the trajectory of nerve fibers in the brain. However, the inferred individual fiber trajectories are difficult to exploit. Compared with a single fiber, a fiber bundle (a group of fibers) is of great significance for improving people's perception of fiber structure and function, as well as fiber bundle-based diagnosis and treatment. For example, we can compare Alzheimer's and normal groups in a bundle Differences in the characteristics of fibers for disease diagnosis. Therefore, the researchers aimed to partition the dense fiber trajectories of the whole brain into fiber tracts with internal integrity, namely f...

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Problems solved by technology

However, the functional implications of the fiber bundles obtained from these fiber clusters are unclear.

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