Abstract
In this paper, we analyzed the application value and effect of deep learn-based image segmentation model of convolutional neural network (CNN) algorithm combined with 3D brain magnetic resonance imaging (MRI) in diagnosis of cerebral palsy in children. 3D brain model was segmented based on CNN algorithm to obtain the segmented MRI images of brain tissue, and the validity was verified. Then, 70 children with cerebral palsy were rolled into the observation group (n = 35), which received MRI for diagnosis after segmentation of brain tissue, and control group (n = 35), which were diagnosed by computed tomography (CT). The diagnosis results of the two groups were compared. The validity experiment verified that the image segmentation method based on CNN algorithm can obtain effective style graphics. In clinical trials, the diagnostic accuracy of 88.6% in the observation group was evidently superior to that of 80% in the control group (P < 0.05). In the observation group, one patient was diagnosed as normal, four patients had white matter lesions, 17 patients had corpus callosum lesions, and five patients had basal ganglia softening foci. In the control group, two patients were diagnosed as normal, two patients had white matter lesions, 19 patients had corpus callosum lesions, and four patients had basal ganglia softening foci. No notable difference was found between the two groups (P > 0.05). According to the research results, in the diagnosis of cerebral palsy in children, the image segmentation of brain 3D model based on CNN to obtain the MRI image of segmented brain tissue can effectively improve the detection accuracy. Moreover, the specific symptoms can be diagnosed clearly. It can provide the corresponding diagnostic basis for clinical diagnosis and treatment and was worthy of clinical promotion.
Highlights
Pediatric cerebral palsy is a common central nervous disorder syndrome in children. e lesions are in the brain, involving limbs, causing serious burden on patients, families, and society, and are one of the important diseases leading to disability in children [1]
Patients in the observation group used brain magnetic resonance imaging (MRI) scan modeling technology to establish a 3D brain, and deep learning-based convolutional neural network (CNN) image segmentation was performed on the established 3D brain model. e instrument was the Domestic Wandong Cang Qiong I Magnate 1.5T Superconducting MRI System. e parameters were set as layer thickness of 6 mm, layer spacing of 1 mm, and field of view of 220 × 220. e transverse and sagittal T1-weighted images (SE 500/30) and the transverse T2-weighted images (300/120) were not enhanced scans
MRI Image Data of Some Patients. e examinations in Figures 5(a)–5(c) showed mild basal ganglia and thalamus lesions, the middle area was not involved, and the clinical diagnosis was dyskinesia cerebral palsy. e examinations in Figures 5(d)–5(f ) showed moderate basal ganglia and good thalamic lesions accompanied by central cortex and subcortical lesions, and the hippocampus was not involved. e clinical diagnosis was dyskinesia cerebral palsy with spasticity or spastic cerebral palsy with dyskinesia characteristics
Summary
Pediatric cerebral palsy is a common central nervous disorder syndrome in children. e lesions are in the brain, involving limbs, causing serious burden on patients, families, and society, and are one of the important diseases leading to disability in children [1]. Pediatric cerebral palsy is a common central nervous disorder syndrome in children. E lesions are in the brain, involving limbs, causing serious burden on patients, families, and society, and are one of the important diseases leading to disability in children [1]. It can lead to the occurrence of cerebral paralysis, which belongs to the severe disability. E main clinical manifestations are movement lag or active movement reduction, especially the reduction of upper limb activities. In terms of abnormal muscle tone, cerebral palsy children often show tension or soft limbs. In terms of abnormal posture, cerebral palsy children often head back. Some children with cerebral palsy may be accompanied by mental retardation, epilepsy, behavior disorder, visual, and hearing impairment, which seriously
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