OBJECTIVE To understand the infection of Acinetobacter baumannii(ABA) in children and make analysis for its resistance to 15 antibiotics.METHODS The collection of clinical strains of ABA isolated from the hospital.the pathogens were identified by MicroScan WalkAway-40 system.RESULTS Eighty-one(95%) ABA among 85 isolates were from respiratory tract.The result of drug susceptibility showed that ABA was highly sensitive to the 15 antibiotics.Multi-resistant ABA bacteria accounted for 8.2%(7/85).CONCLUSIONS ABA strains isolated from children patients show the trend of multi-drug resistance.we should pay more attention to monitor the susceptibility to antibiotics.

Magnetic resonance imaging (MRI) plays a more and more important role in medical image area for its advantages of nonradiative,multiple imaging and high spatial resolution.This review gives a systematic discussion over a couple of MRI segmentation algorithms that are used widely to help people have an entire knowledge of MRI segmentation methods.On the base of classification and summary of MRI segmentation,the MRI segmentation algorithms have been classified into 5 different categories after preliminary investigation and survey.Based on threshold,pattern recognition,active contours,Markov random field (MRF) and graph cut,separately.After further investigation and survey we summarize the characters and field of applications of the 5 different algorithms,then take a few segment experiments among these algorithms on abdomen MRI and present their distinct characteristics.At last,we take a prospect at the future of the MRI segmentation.

Objective:To combine automatic image segmentation technology and machine learning methods to accurately classify and recognize mammography images.Methods:Taking mammography images with clustered pleomorphic calcification as the research object, which were in BI-RADS4 class from the Digital Mammogram Database (DDSM). The region of interest (ROI) of the images was automatically segmented. The characteristic features extracted by wavelet transform, Gabor filter and gray level co-occurrence matrix method were fused. The fused feature parameters were screened based on sensitivity analysis. Using ensemble learning method, the polynomial kernel SVM, random forest and logistic regression classifiers were integrated to form a classifier for automatic classification of mammography images. The ensemble learning method was soft voting integration.Results:The proposed ensemble classifier can efficiently recognize and classify mammography images, and its classification sensitivity, specificity and accuracy on the training set were 99.1%, 99.6% and 99.3%, respectively.Conclusions:The proposed mammography image processing, classification and recognition method can provide assistant detection basis for doctors' clinical judgment, and provide a technical basis for subdividing BI-RADS4 class images.

Objective:To analyze the characteristics of sleep disordered breathing (SDB) in children with allergic rhinitis (AR), and improve the diagnosis and treatment at AR combined with obstructive sleep apnea (OSA).Methods:The clinical data of 120 patients with AR and OSA (AR and OSA group) admitted to the respiratory department at Shenzhen Children′s Hospital from May 2019 to December 2020 were retrospectively analyzed.A total of 120 children diagnosed with OSA and excluded AR during the same period were selected as control group.The SDB day and night symptoms, sleep structure characteristics and sleep breathing events were compared between two groups.Results:The average course of disease in children with AR and OSA was significantly longer than that in control group ( P=0.030). The main manifestations of children in AR and OSA group were mouth breathing (100.0%), snoring (99.2%), nasal obstruction (88.5%), and restless sleep (68.0%). There was no significant difference in sleep structure between two groups ( P>0.05), but the sleep efficiency of AR and OSA group was significantly lower than that of control group ( P=0.028). The respiratory events apnea hypopnea index, obstructive apnea index, obstructive apnea hypopnea index, hypopnea index and oxygen desaturation index of each sleep period in AR and OSA group were significantly higher than those in control group ( P<0.05). Among the children in AR and OSA group, moderate and severe OSA were the main manifestations, and the difference between two groups was statistically significant ( P<0.001). Conclusion:The combination of AR delayed the course of OSA in children.The main characteristics of sleep disordered breathing in children with AR are mouth opening, restless sleep, snoring and nasal obstruction.The sleep efficiency is decreased.Obstructive hypopnea and apnea are the most common respiratory events, and oxygen deficiency often occurs in rapid eye movement phase.Children with AR are more likely to have moderate or severe obstructive sleep apnea.