Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are non- specific responses of the brain to many types of insults. The structural abnormalities causing ep...Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are non- specific responses of the brain to many types of insults. The structural abnormalities causing epilepsy can be identified using various state of art imaging methods. Through a combination of brain activity monitoring, imaging and mapping techniques, physicians can locate the specific area in the brain causing epileptic discharges and identify its location in relation to those areas in the brain controlling vital functions. Positron Emission Tomography (PET) has emerged as a useful tool to identify abnormal metabolic activity of the epileptogenic foci. Parameters like asymmetric index, stan- dard uptake value (SUV) etc obtained by PET are processed and analyzed for identifying the origin of epileptic sei- zures. This paper discuss the techniques used to diagnose in general and to localize the epileptogenic regions using post-processing other features on PET imaging.展开更多
Aim: Neurovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arteriovenous Malformation (CAVM) hemo-dynamic in one of the vascular ab...Aim: Neurovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arteriovenous Malformation (CAVM) hemo-dynamic in one of the vascular abnormality condition results changes in the vessels structures and hemodynamics in blood vessels. The challenge is segmenting accurate vessel region to measure hemodynamics of CAVM patients. The clinical procedure is in-vivo method to measure hemodynamics. The catheter-based procedure is difficult, as it is sometimes difficult to reach vessels sub-structures. Methods: In this paper, we have proposed adaptive vessel segmentation based on threshold technique for CAVM patients. We have compared different adaptive methods for vessel segmentation of CAVM structures. The sub-structures are modeled using lumped model to measure hemodynamics non-invasively. Results: Twenty-three CAVM patients with 150 different vessel locations of DSA datasets were studied as part of the adaptive segmentation. 30 simulated data has been evaluated for more than 150 vessels locations for sub-segmentation of vessels. The segmentation results are evaluated with accuracy of 93%. The computed p-value is smaller than the significance level 0.05. Conclusion: The adaptive segmentation using threshold based produces accurate vessel segmentation, results in better accuracy of hemodynamic measurements for DSA images for CAVM patients. The proposed adaptive segmentation helps clinicians to measure hemodynamic non-invasively for the segmented sub-structures of vessels.展开更多
文摘Epilepsy is caused by abnormal excessive electric discharges from the neurons in the brain. Epileptic seizures are non- specific responses of the brain to many types of insults. The structural abnormalities causing epilepsy can be identified using various state of art imaging methods. Through a combination of brain activity monitoring, imaging and mapping techniques, physicians can locate the specific area in the brain causing epileptic discharges and identify its location in relation to those areas in the brain controlling vital functions. Positron Emission Tomography (PET) has emerged as a useful tool to identify abnormal metabolic activity of the epileptogenic foci. Parameters like asymmetric index, stan- dard uptake value (SUV) etc obtained by PET are processed and analyzed for identifying the origin of epileptic sei- zures. This paper discuss the techniques used to diagnose in general and to localize the epileptogenic regions using post-processing other features on PET imaging.
文摘Aim: Neurovascular abnormalities are extremely complex, due to the multitude of factors acting simultaneously on cerebral hemodynamics. Cerebral Arteriovenous Malformation (CAVM) hemo-dynamic in one of the vascular abnormality condition results changes in the vessels structures and hemodynamics in blood vessels. The challenge is segmenting accurate vessel region to measure hemodynamics of CAVM patients. The clinical procedure is in-vivo method to measure hemodynamics. The catheter-based procedure is difficult, as it is sometimes difficult to reach vessels sub-structures. Methods: In this paper, we have proposed adaptive vessel segmentation based on threshold technique for CAVM patients. We have compared different adaptive methods for vessel segmentation of CAVM structures. The sub-structures are modeled using lumped model to measure hemodynamics non-invasively. Results: Twenty-three CAVM patients with 150 different vessel locations of DSA datasets were studied as part of the adaptive segmentation. 30 simulated data has been evaluated for more than 150 vessels locations for sub-segmentation of vessels. The segmentation results are evaluated with accuracy of 93%. The computed p-value is smaller than the significance level 0.05. Conclusion: The adaptive segmentation using threshold based produces accurate vessel segmentation, results in better accuracy of hemodynamic measurements for DSA images for CAVM patients. The proposed adaptive segmentation helps clinicians to measure hemodynamic non-invasively for the segmented sub-structures of vessels.
