Abstract: A system of generating data from diffusion-weighted images for pre-processing and a method thereof are disclosed. In the system, a processing parameter set including diffusion information is acquired; after a raw diffusion-weighted image including data images and image information is acquired, the image information is interpreted to set image processing data of the raw diffusion-weighted image, and non-deformation correction and deformation correction are performed on the raw diffusion-weighted image to generate a pre-processed diffusion-weighted image based on the processing parameter set and the image processing data. Therefore, the image processing data can be automatically set based on the raw diffusion-weighted image, to achieve the effect of lowering difficulty for analyzing DWI and saving setup time of image processing data.

Abstract: A neurovascular age prediction system based on white matter and a method thereof are disclosed. An analysis device generates an individual space periventricular area mask and an individual space deep white matter mask by nonlinear space counterpoint technology and MNI152 brain template, and reversely transforms individual coordinates into a transition matrix, performs white matter hyperintensity (WMH) signal image processing on the T1 weighted image and the T2 fluid attenuated inversion recovery (FLAIR) image to generate a T1 weighted WMH signal image and a T2 FLAIR WMH signal image, then converts the Ti WMH signal image and the T2 FLAIR WMH signal image into logarithms of a periventricular white matter volume and a deep WMH volume based on the individual space periventricular area mask and the individual space deep white matter mask, and substitutes the logarithms into a neurovascular age prediction model to obtain a neurovascular age prediction result.

Abstract: A model training method and an electronic device are provided. The method includes the following steps: establishing a brain age prediction model according to a training set; adjusting a parameter in the brain age prediction model according to a validation set; inputting a test set into the brain age prediction model with the adjusted parameter to obtain a plurality of first predicted brain ages; determining whether the first predicted brain ages satisfy a first specific condition; and completing training of the brain age prediction model when the first predicted brain ages satisfy the first specific condition.

Abstract: A connection module for protecting battery cells includes a plurality of conductive sheets, a plurality of conductive wires, or a conductive mesh. The conductive sheets are connected with at least one battery cell. The conductive wires or the conductive mesh is connected to the conductive sheets. An electrical conductivity of the conductive wires or the conductive mesh is higher than that of the conductive sheets. When the battery cells connected to the conductive sheets damages, it may cause an electrolyte ejected from the battery cells, or a large current passing through the conductive wires or the conductive mesh, such that the conductive wires or the conductive mesh is burned and melted to achieve the purpose of protecting other battery cells.

Abstract: A model training method and an electronic device are provided. The method includes the following steps: establishing a brain age prediction model according to a training set; adjusting a parameter in the brain age prediction model according to a validation set; inputting a test set into the brain age prediction model with the adjusted parameter to obtain a plurality of first predicted brain ages; determining whether the first predicted brain ages satisfy a first specific condition; and completing training of the brain age prediction model when the first predicted brain ages satisfy the first specific condition.

Abstract: The present disclosure illustrates a method and an apparatus of fiber tracking, and non-transitory computer-readable medium thereof. In an embodiment, a fiber tracking process is performed on a diffusion magnetic resonance image of a subject's brain based on validated and better tracking parameters, so as to obtain first tracking images, nerve fibers between two first regions of interest in each of the first tracking images are extracted, a nerve fasciculus skeleton is established based on an overlapping process performed on the plurality of nerve fibers extracted from the first tracking images, and the nerve fibers more similar to the structure of the nerve fasciculus skeleton are selected to obtain a specific fasciculus of the subject. Thus, the technical solution of the present disclosure can be used to improve the sensitivity of fiber tracking and be useful for improvement of preoperative assessment and surgical navigation.

Abstract: The present disclosure illustrates a method and an apparatus of fiber tracking, and non-transitory computer-readable medium thereof. In an embodiment, a fiber tracking process is performed on a diffusion magnetic resonance image of a subject's brain based on validated and better tracking parameters, so as to obtain first tracking images, nerve fibers between two first regions of interest in each of the first tracking images are extracted, a nerve fasciculus skeleton is established based on an overlapping process performed on the plurality of nerve fibers extracted from the first tracking images, and the nerve fibers more similar to the structure of the nerve fasciculus skeleton are selected to obtain a specific fasciculus of the subject. Thus, the technical solution of the present disclosure can be used to improve the sensitivity of fiber tracking and be useful for improvement of preoperative assessment and surgical navigation.