Abstract: Techniques are disclosed for measuring the corpus callosum volume of a fetus using magnetic resonance imaging. A scanogram of a fetus is acquired, and a detection area is determined using the corpus callosum position of the fetus in the scanogram. Magnetic resonance scanning is performed on the detection area to obtain a diffusion weighted image, with a gradient direction that is orthogonal or normal to an extending direction of fiber bundles of the corpus callosum. A fetal head image is cropped in the diffusion weighted image, and a predetermined threshold is applied to obtain an image including pixels having a brightness value that is greater than the threshold. Image processing is performed on the binarized image, with the largest region therein being identified as the corpus callosum, and the sum of voxel dimensions associated with the signal of the largest region being calculated as the corpus callosum volume.

Abstract: A brain tumor image segmentation method and device are disclosed. The disclosed method includes acquiring a basic white matter template generated based on brain magnetic resonance images of a plurality of healthy samples, collecting corresponding low, mid and high b-value diffusion weighted images of the brain of a patient, segmenting out a tumor region including the tumor body and the edema on each image based on the signal distribution of each image in a first set image group of the patient, removing the normal white matter region from the tumor region according to the basic white matter template and the high b-value diffusion weighted image, and classifying the value of the voxel in each image in a second set image group and a second apparent diffusion coefficient image obtained through calculations to obtain a tumor body region and an edema region.

Abstract: Techniques are disclosed for measuring the corpus callosum volume of a fetus using magnetic resonance imaging. A scanogram of a fetus is acquired, and a detection area is determined using the corpus callosum position of the fetus in the scanogram. Magnetic resonance scanning is performed on the detection area to obtain a diffusion weighted image, with a gradient direction that is orthogonal or normal to an extending direction of fiber bundles of the corpus callosum. A fetal head image is cropped in the diffusion weighted image, and a predetermined threshold is applied to obtain an image including pixels having a brightness value that is greater than the threshold. Image processing is performed on the binarized image, with the largest region therein being identified as the corpus callosum, and the sum of voxel dimensions associated with the signal of the largest region being calculated as the corpus callosum volume.

Abstract: A brain tumor image segmentation method and device are disclosed. The disclosed method includes acquiring a basic white matter template generated based on brain magnetic resonance images of a plurality of healthy samples, collecting corresponding low, mid and high b-value diffusion weighted images of the brain of a patient, segmenting out a tumor region including the tumor body and the edema on each image based on the signal distribution of each image in a first set image group of the patient, removing the normal white matter region from the tumor region according to the basic white matter template and the high b-value diffusion weighted image, and classifying the value of the voxel in each image in a second set image group and a second apparent diffusion coefficient image obtained through calculations to obtain a tumor body region and an edema region.

Abstract: A method for determining an intracortical working state of a functional network of the brain includes acquiring a number of first blood oxygen saturation level time point vectors of a number of gray matter voxels of a cortex of a brain functional network template, each of the blood oxygen saturation level time point vectors respectively having blood oxygen saturation level signals of each of the gray matter voxels at a number of continuous time points in a particular time period. The method further includes clustering the blood oxygen saturation level time point vectors as a number of gray matter voxel cooperative time point categories by taking the blood oxygen saturation level signals as objects, the gray matter voxel cooperative time point categories being sets of a number of discrete time points of the gray matter voxels respectively in the particular time period.