Previous studies have shown that vagus nerve stimulation can improve the prognosis of trau- matic brain injury. The aim of this study was to elucidate the mechanism of the neuroprotective effects of vagus nerve stimul...Previous studies have shown that vagus nerve stimulation can improve the prognosis of trau- matic brain injury. The aim of this study was to elucidate the mechanism of the neuroprotective effects of vagus nerve stimulation in rabbits with brain explosive injury. Rabbits with brain ex- plosive injury received continuous stimulation （10 V, 5 Hz, 5 ms, 20 minutes） of the right cervical vagus nerve. Tumor necrosis factor-a, interleukin-l~ and interleukin-10 concentrations were detected in serum and brain tissues, and water content in brain tissues was measured. Results showed that vagus nerve stimulation could reduce the degree of brain edema, decrease tumor necrosis factor-a and interleukin-1β concentrations, and increase interleukin-10 concentration after brain explosive injury in rabbits. These data suggest that vagus nerve stimulation may exert neuroprotective effects against explosive injury via regulating the expression of tumor necrosis factor-a, interleukin-1 β and interleukin-10 in the serum and brain tissue.展开更多
A new method for the denoising,extraction and tumor detection on MRI images is presented in this paper.MRI images help physicians study and diagnose diseases or tumors present in the brain.This work is focused towards...A new method for the denoising,extraction and tumor detection on MRI images is presented in this paper.MRI images help physicians study and diagnose diseases or tumors present in the brain.This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis.The ambiguity of Magnetic Resonance(MR)image features is solved in a simpler manner.The MRI image acquired from the machine is subjected to analysis in the work.The real-time data is used for the analysis.Basic preprocessing is performed using various filters for noise removal.The de-noised image is segmented,and the feature extractions are performed.Features are extracted using the wavelet transform.When compared to other methods,the wavelet transform is more suitable for MRI image feature extraction.The features are given to the classifier which uses binary tree support vectors for classification.The classification process is compared with conventional methods.展开更多
文摘Previous studies have shown that vagus nerve stimulation can improve the prognosis of trau- matic brain injury. The aim of this study was to elucidate the mechanism of the neuroprotective effects of vagus nerve stimulation in rabbits with brain explosive injury. Rabbits with brain ex- plosive injury received continuous stimulation （10 V, 5 Hz, 5 ms, 20 minutes） of the right cervical vagus nerve. Tumor necrosis factor-a, interleukin-l~ and interleukin-10 concentrations were detected in serum and brain tissues, and water content in brain tissues was measured. Results showed that vagus nerve stimulation could reduce the degree of brain edema, decrease tumor necrosis factor-a and interleukin-1β concentrations, and increase interleukin-10 concentration after brain explosive injury in rabbits. These data suggest that vagus nerve stimulation may exert neuroprotective effects against explosive injury via regulating the expression of tumor necrosis factor-a, interleukin-1 β and interleukin-10 in the serum and brain tissue.
文摘A new method for the denoising,extraction and tumor detection on MRI images is presented in this paper.MRI images help physicians study and diagnose diseases or tumors present in the brain.This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis.The ambiguity of Magnetic Resonance(MR)image features is solved in a simpler manner.The MRI image acquired from the machine is subjected to analysis in the work.The real-time data is used for the analysis.Basic preprocessing is performed using various filters for noise removal.The de-noised image is segmented,and the feature extractions are performed.Features are extracted using the wavelet transform.When compared to other methods,the wavelet transform is more suitable for MRI image feature extraction.The features are given to the classifier which uses binary tree support vectors for classification.The classification process is compared with conventional methods.
