| Acute brain injury is a type of brain disease with intracranial hemorrhage or ischemic as the main clinical manifestations.It has the characteristics of acute onset,complicated and rapid disease progression,and dangerous conditions.Clinically,both trauma and stroke can cause an acute head injury.Real-time dynamic monitoring and early detection of changes in brain injury is an important prerequisite for the timely and accurate treatment in clinical practice,which is also the key to saving the lives of patients with brain injury and improving their prognosis and quality of life.However,current medical imaging technologies such as CT and MRI have low temporal resolution,which can be hard to perform dynamic imaging monitoring of brain injury.Therefore,there is an urgent need for a dynamic imaging monitoring technique with a higher time resolution.Electrical Impedance Tomography,or EIT in abbreviation,uses the principle of different electrical impedances of biological tissues under different physiological and pathological conditions to compute the distribution of electrical impedance and its changes related to the physiology and pathology of human tissues.With portable,fast,functional imaging and other advantages,it is expected to become a novel effective technique of brain injury detection and dynamic imaging monitoring.At present,the electrode systems used in the main EIT studies are mostly more than 16 electrodes.However,in special situations such as pre-hospital care and brain trauma treatment,it is necessary to reduce the number of electrodes in order to improve system operation efficiency and achieve equipment availability in wearable equipment.How to ensure the accurate characterization of brain injury changes,which should be as much as possible,in dynamic images while electrodes are sparse is the key issue for sparse electrodes in EIT systems.The main challenges of imaging after the sparse EIT system electrodes focus on two aspects: Firstly,the perturbation target may result in the reduction of the amount of information represented in the boundary voltage measurement due to the reducing number of the electrode;Secondly,the sparse electrodes effect on image reconstruction quality.The main effect is that there can exist many artifacts in reconstructed images,which affects the recognition of perturbation targets.In view of the above problems in sparse electrodes EIT research,with the need taken into account to reduce the number of current EIT device electrodes in special application scenarios,and in order to improve the quality of the reconstructed image after sparse electrodes,this paper analyzed the variation of information obtained from the boundary voltage measurement data after the reducing number of electrodes,and proposed an sparse electrodes dynamic algorithm for cranial Electrical Impedance Tomography.The main work includes:1.Quantitative analysis of the amount of information obtained from boundary measurement data in electrodes reducing process: A realistic three-dimensional brain simulation model was established to quantitatively study the change of distinguishability about intracranial disturbance target that can be characterized by boundary voltage measurements in electrodes reducing process;2.Research on sparse electrodes dynamic imaging algorithm of cranial Electrical Impedance Tomography: The algorithm is mainly based on the training target method to solve the optimal reconstruction matrix and sub-domain weighting method to optimize the imaging algorithm.In the reconstruction matrix solution,the training targets in different positions are introduced to calculate the optimal reconstruction matrix,and the distribution of intracranial impedance information is preliminarily reconstructed,and the region where the impedance change is most likely to occur is judged.In judged region,the subdomain weighting method is used and the solution to the inverse problem tends to be in this area,which can highlight the target,reducing artifacts,and enhancing the quality of the EIT reconstruction images;3.Verification of the new dynamic algorithm of cranial Electrical Impedance Tomography: Based on the real human brain impedance distribution,a three-dimensional simulation model and a physical model of reducing electrodes were constructed,combined with EIT imaging software and reconstruction image quality evaluation methods,a cranial EIT algorithm performance test system was created.The system comprehensively compares and evaluates the optimization of dynamic imaging algorithms for brain electrical impedance after sparse electrodes.Research indicates:1.In the electrode reducing process,the information contained in the boundary voltage measurement rapidly decreases when the number of electrodes is less than 8 electrodes,and can only retain about 20% of the distinguishability in the measured value of the original 16 electrodes.When the number of electrodes is not less than 8 electrodes,at least 50% amount of information can be kept;2.After the optimization of cranial Electrical Impedance Tomography algorithm for sparse electrode,the reconstruction image error is reduced by about 41.3% compared to directly applying the original 16-electrode dynamic imaging algorithm,and the reconstruction image quality is greatly improved..This article focuses on the challenges faced by sparse electrodes in dynamic EIT imaging of the brain,and has initially achieved the following innovations:(1)Calculate the amount of information represented by the EIT boundary voltage measurement from a mathematical point of view,and study in detail the change in the distinguishability obtained from the EIT boundary voltage measurement after electrode reducing;(2)Successfully proposed and implemented an electrode sparse optimization dynamic algorithm for cranial Electrical Impedance Tomography.After the physical model experimental verification,the qualities of reconstructed images after electrode reducing were improved.This article aims to explore the development of sparse electrode cranial Electrical Impedance Tomography,to promote the application of electrical impedance imaging in special fields such as pre-hospital care and brain trauma treatment for patients with brain injury,and provide important theoretical and experimental foundations for the research of wearable electrical impedance imaging equipment. |
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