Objective To explore the self-experience of burying seeds at auricular points in depressive patients with sleep disorder,so as to seek possible approaches to improve the quality of care.Methods Eleven patients involve...Objective To explore the self-experience of burying seeds at auricular points in depressive patients with sleep disorder,so as to seek possible approaches to improve the quality of care.Methods Eleven patients involved in a three-week randomized controlled clinical trial were purposefully interviewed by the experienced,qualified counselor.The process of thematic analysis was applied in this study,the self-experience was discussed and recorded,transcribed,and analyzed accordingly.Results Four themes related to self-experience were extracted,these included the deficiency in relevant support,passive acceptance,distrust,expectation and further advice.Conclusion There was an urgent demand of humane care and emotional support,which might improve compliance of the treatment to some extent in terms of health education.Additionally,medical practitioners should provide the patient with comprehensive support,professional health education,as well as standardize training program for TCM operator and control the operation’s quality.展开更多
Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography(CT)images.The segmentation of hepatic organ is more intricate task,owing to the fact that it posses...Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography(CT)images.The segmentation of hepatic organ is more intricate task,owing to the fact that it possesses a sizeable quantum of vascularization.This paper proposes an algorithm for automatic seed point selection using energy feature for use in level set algorithm for segmentation of liver region in CT scans.The effectiveness of the method can be determined when used in a model to classify the liver CT images as tumorous or not.This involves segmentation of the region of interest(ROI)from the segmented liver,extraction of the shape and texture features from the segmented ROI and classification of the ROIs as tumorous or not by using a classifier based on the extracted features.In this work,the proposed seed point selection technique has been used in level set algorithm for segmentation of liver region in CT scans and the ROIs have been extracted using Fuzzy C Means clustering(FCM)which is one of the algorithms to segment the images.The dataset used in this method has been collected from various repositories and scan centers.The outcome of this proposed segmentation model has reduced the area overlap error that could offer the intended accuracy and consistency.It gives better results when compared with other existing algorithms.Fast execution in short span of time is another advantage of this method which in turns helps the radiologist to ascertain the abnormalities instantly.展开更多
基金Scientific Research Project of Twelfth Five-year Plan Internal Medicine of the Affiliated Brain Hospital of Guangzhou Medical University(GBH2014-HL05)Scientific Research Project of Traditional Chinese Medicine Bureau of Guangdong Province(20161192)
文摘Objective To explore the self-experience of burying seeds at auricular points in depressive patients with sleep disorder,so as to seek possible approaches to improve the quality of care.Methods Eleven patients involved in a three-week randomized controlled clinical trial were purposefully interviewed by the experienced,qualified counselor.The process of thematic analysis was applied in this study,the self-experience was discussed and recorded,transcribed,and analyzed accordingly.Results Four themes related to self-experience were extracted,these included the deficiency in relevant support,passive acceptance,distrust,expectation and further advice.Conclusion There was an urgent demand of humane care and emotional support,which might improve compliance of the treatment to some extent in terms of health education.Additionally,medical practitioners should provide the patient with comprehensive support,professional health education,as well as standardize training program for TCM operator and control the operation’s quality.
文摘Liver Segmentation is one of the challenging tasks in detecting and classifying liver tumors from Computed Tomography(CT)images.The segmentation of hepatic organ is more intricate task,owing to the fact that it possesses a sizeable quantum of vascularization.This paper proposes an algorithm for automatic seed point selection using energy feature for use in level set algorithm for segmentation of liver region in CT scans.The effectiveness of the method can be determined when used in a model to classify the liver CT images as tumorous or not.This involves segmentation of the region of interest(ROI)from the segmented liver,extraction of the shape and texture features from the segmented ROI and classification of the ROIs as tumorous or not by using a classifier based on the extracted features.In this work,the proposed seed point selection technique has been used in level set algorithm for segmentation of liver region in CT scans and the ROIs have been extracted using Fuzzy C Means clustering(FCM)which is one of the algorithms to segment the images.The dataset used in this method has been collected from various repositories and scan centers.The outcome of this proposed segmentation model has reduced the area overlap error that could offer the intended accuracy and consistency.It gives better results when compared with other existing algorithms.Fast execution in short span of time is another advantage of this method which in turns helps the radiologist to ascertain the abnormalities instantly.
