Baby brain age predicting method based on resting state functional magnetic resonance image and system

Abstract

The invention belongs to the field of computer medicine, and particularly relates to a baby brain age predicting method based on a resting state functional magnetic resonance image and a system. The method and the system aim to settle a problem of incapability of predicting the baby brain age based on the functional magnetic resonance image based on dynamic function connection. The method according to the invention comprises the steps of acquiring a functional magnetic resonance image set of a measured object; performing brain area segmenting on each image, and performing characteristic dimension reduction on each brain area; based on the functional magnetic resonance image set after dimension reduction and a time sequence, constructing a brain area-time sequence characteristic matrix; constructing a dynamic function connecting matrix based on the brain area-time sequence characteristic matrix; and performing brain age predicting through a pre-trained classification model. The method and the system quickly and conveniently realize functional magnetic resonance image brain age predicting based on the dynamic function connection through a computer means, thereby quickly determining whether the brain growth degree of the baby matches an actual age, finding a possible brain retardation in time, and facilitating assistance to clinical decision of a doctor.

Description

technical field [0001] The invention belongs to the field of computer medicine, and in particular relates to a method and system for predicting infant brain age based on resting state functional magnetic resonance images. Background technique [0002] Autism is a common disease caused by brain development disorders. Its symptoms are manifested as abnormal social skills, communication skills, interests and behavior patterns. It is a major problem that threatens the health of children and adolescents. Studies have shown that timely detection and intervention are of great help in the treatment of autism. However, due to the weak communication and comprehension ability of infants and young children, it is difficult to detect their early symptoms in time through direct communication. Generally speaking, the symptoms of autism cannot be manifested until after the age of three. Therefore, it is important to accurately evaluate the developmental stages of the brains of early infant...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, the problem that the brain age of infants cannot be predicted based on functional magnetic resonance images of dynamic functional connectivity, the present invention provides a method for predicting brain age of infants based on resting-state functional magnetic resonance images, including :

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