Eclampsia is a common complication of hypertensive disorders of pregnancy and in the puerperium with the attendant risk to both the mother and baby. Although it is a multi-systemic disorder, its manifestation that aff...Eclampsia is a common complication of hypertensive disorders of pregnancy and in the puerperium with the attendant risk to both the mother and baby. Although it is a multi-systemic disorder, its manifestation that affects the brain and resulting in altered sensorium demands brain imaging to define the possible brain lesions and the implications for critical care management and outcome. We evaluated the CT brain lesions in the patients with eclampsia who were admitted in the intensive care unit, University of Port Harcourt, Port Harcourt Nigeria. Objective: To analyse the CT brain images of eclamptic parturients and the outcome following their admission in the intensive care unit. Methods: We undertook this observational study after obtaining ethical exemption from the University of Portharcourt Teaching Hospital ethical review board, and commenced the review between March 2021 to February 2023. We included all parturients that were admitted into the intensive care unit of the University of Portharcourt Teaching Hospital, a nine-bedded open intensive care unit with the clinical diagnosis of eclampsia. Every admitted parturient was required to obtain a brain computed tomography (CT) by local protocol. The brain CT images were retrieved for review from the parturients’ relatives, radiology department and the ICU. Parturients included were aged ≥ 18 years. The radiological reports of these brain images which were also reviewed by a neurosurgeon in case of any need for secondary opinion were subjected to statistical analysis. Result: Thirty-one parturients were admitted with eclampsia with a mean age of 30 years ± 5.29. Sixteen (16) parturients died representing 52%. Only twenty-four (24) CT brain images were retrieved for review (77%). The following brain lesions were identified from the brain CT and they comprised the following: intracerebral haemorrhage, including extensions into the ventricles 7 (29.17%), cerebral oedema 12 (50%), subdural hematoma 1 (4.17%) and normal imaging 4 (16.66%). The subdural haematoma was promptly evacuated with a good outcome. Conclusion: Neuro imaging comprising computed tomography and magnetic resonance imaging of the brain are basic ancillary investigations for patients with eclampsia presenting with neurologic deficits and low GCS. Early presentation and access to brain CT could influence outcome as it was demonstrated in the prompt intervention in the patient with subdural haematoma which was evacuated with a satisfactory outcome.展开更多
In order to effectively improve the pathological diagnosis capability and feature resolution of 3D human brain CT images,a threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel ...In order to effectively improve the pathological diagnosis capability and feature resolution of 3D human brain CT images,a threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is proposed in this paper.In this method,first,original 3D human brain image information is collected,and CT image filtering is performed to the collected information through the gradient value decomposition method,and edge contour features of the 3D human brain CT image are extracted.Then,the threshold segmentation method is adopted to segment the regional pixel feature block of the 3D human brain CT image to segment the image into block vectors with high-resolution feature points,and the 3D human brain CT image is reconstructed with the salient feature point as center.Simulation results show that the method proposed in this paper can provide accuracy up to 100%when the signal-to-noise ratio is 0,and with the increase of signal-to-noise ratio,the accuracy provided by this method is stable at 100%.Comparison results show that the threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is signicantly better than traditional methods in pathological feature estimation accuracy,and it effectively improves the rapid pathological diagnosis and positioning recognition abilities to CT images.展开更多
文摘Eclampsia is a common complication of hypertensive disorders of pregnancy and in the puerperium with the attendant risk to both the mother and baby. Although it is a multi-systemic disorder, its manifestation that affects the brain and resulting in altered sensorium demands brain imaging to define the possible brain lesions and the implications for critical care management and outcome. We evaluated the CT brain lesions in the patients with eclampsia who were admitted in the intensive care unit, University of Port Harcourt, Port Harcourt Nigeria. Objective: To analyse the CT brain images of eclamptic parturients and the outcome following their admission in the intensive care unit. Methods: We undertook this observational study after obtaining ethical exemption from the University of Portharcourt Teaching Hospital ethical review board, and commenced the review between March 2021 to February 2023. We included all parturients that were admitted into the intensive care unit of the University of Portharcourt Teaching Hospital, a nine-bedded open intensive care unit with the clinical diagnosis of eclampsia. Every admitted parturient was required to obtain a brain computed tomography (CT) by local protocol. The brain CT images were retrieved for review from the parturients’ relatives, radiology department and the ICU. Parturients included were aged ≥ 18 years. The radiological reports of these brain images which were also reviewed by a neurosurgeon in case of any need for secondary opinion were subjected to statistical analysis. Result: Thirty-one parturients were admitted with eclampsia with a mean age of 30 years ± 5.29. Sixteen (16) parturients died representing 52%. Only twenty-four (24) CT brain images were retrieved for review (77%). The following brain lesions were identified from the brain CT and they comprised the following: intracerebral haemorrhage, including extensions into the ventricles 7 (29.17%), cerebral oedema 12 (50%), subdural hematoma 1 (4.17%) and normal imaging 4 (16.66%). The subdural haematoma was promptly evacuated with a good outcome. Conclusion: Neuro imaging comprising computed tomography and magnetic resonance imaging of the brain are basic ancillary investigations for patients with eclampsia presenting with neurologic deficits and low GCS. Early presentation and access to brain CT could influence outcome as it was demonstrated in the prompt intervention in the patient with subdural haematoma which was evacuated with a satisfactory outcome.
文摘In order to effectively improve the pathological diagnosis capability and feature resolution of 3D human brain CT images,a threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is proposed in this paper.In this method,first,original 3D human brain image information is collected,and CT image filtering is performed to the collected information through the gradient value decomposition method,and edge contour features of the 3D human brain CT image are extracted.Then,the threshold segmentation method is adopted to segment the regional pixel feature block of the 3D human brain CT image to segment the image into block vectors with high-resolution feature points,and the 3D human brain CT image is reconstructed with the salient feature point as center.Simulation results show that the method proposed in this paper can provide accuracy up to 100%when the signal-to-noise ratio is 0,and with the increase of signal-to-noise ratio,the accuracy provided by this method is stable at 100%.Comparison results show that the threshold segmentation method of multi-resolution 3D human brain CT image based on edge pixel grayscale feature decomposition is signicantly better than traditional methods in pathological feature estimation accuracy,and it effectively improves the rapid pathological diagnosis and positioning recognition abilities to CT images.
