Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Klebsiella pneumoniae(KPn),as a conditioned pathogen that causes calf pneumonia,has caused serious harm to cattle industry,but the harm of Klebsiella pneumoniae to calves in Xin-jiang region is still unclear.In this study,to investigate the prevalence of KPn,its harm and some biological characteristics of pneumonia calves in Xinjiang,nasal swabs of pneumonia calves in some areas were collected aseptically,KPn isolation and identification were performed by routine meth-od,and 16S rDNA sequence evolutionary tree analysis was performed.The drug resistance was de-tected by K-B method,and a strain carrying multiple virulence was selected for mice median lethal dose test.The serotype,virulence gene and drug resistance gene of the strain were detected by PCR.The results showed that the detection rate of Klebsiella pneumoniae in nasal swabs of 218 pneumonia calves from Aksu,Changji and Yili regions of Xinjiang was as follows:14.68％(32/218),including 28.33％(17/60)in Aksu Prefecture,24.00％(6/25)in Changji Prefecture and 6.77％(9/133)in Yili Prefecture,they were divided into two serotypes,namely K1(7/32)and K5(5/32).A total of 13 KPn virulence genes were detected,mainly mrkD,ureA,wabG,uge and en-tB.LD50 was 2.38X 107cfu/mL.Drug susceptibility test and drug resistance gene detection showed that the isolated strain showed multiple drug resistance,and the resistance genes mainly carried blasHv and floR.16S rDNA sequence evolutionary tree results showed that the isolated strain had high homology with the isolates from Italy,Beijing and Shanghai of China.The detection rate of KPn in nasal swabs of pneumonia calves in Xinjiang region is high.The dominant serotypes are K1 and K5.The isolates carry a variety of virulence genes and have strong virulence.All of them are KPn strains producing ESBLs,suggesting that Klebsiella pneumoniae in Xinjiang region of China have a certain potential harm to calves.

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Objective:To explore the influence of storage and delivery conditions of the peripheral blood samples from patients with chronic myeloid leukemia (CML) on the real-time quantitative PCR (RQ-PCR) detection of the BCR-ABL (P210) transcript levels.Methods:The peripheral blood samples of 84 CML patients were collected. The same sample was divided into different groups according to storage time (0, 6, 12, 24, 48, and 72 h) , temperature (room temperature, 18-24 ℃; low temperature, 2-8 ℃) , and vibration conditions (3, 6, and 12 h) . RQ-PCR was used to detect BCR-ABL (P210) transcript levels of the different groups. This study logarithmically transformed (log 10N) the original data [BCR-ABL copy number, ABL copy number, and BCR-ABL (P210) transcript levels]. Results:①Agarose gel electrophoresis showed significant RNA degradation of samples after storage for 48 and 72 h at room temperature. ②Among the overall samples, the BCR-ABL copy number of the samples stored at room temperature for 48 and 72 h was significantly lower than that of the samples stored at low temperature ( P<0.05) . However, the BCR-ABL (P210) transcript levels had no significant difference between samples stored at low temperature and room temperature. ③No significant changes were noted in the BCR-ABL (P210) transcript levels at different storage times (6, 12, 24, 48, and 72 h) regardless of storage temperature ( P>0.05) compared with that at baseline (0 h, -0.56±1.51) . ④ The BCR-ABL copy number of the overall sample only decreased significantly ( P<0.05) at 48 h (2.93±1.59) and 72 h (2.79±1.42) compared with that at baseline (0 h, 3.35±1.60) when stored at room temperature. The ABL copy number in the overall sample decreased significantly at 48 and 72 h (whether low and room temperature; P<0.05) . However, no significant changes were noted in the BCR-ABL (P210) transcript levels after vibration for 3 h (-1.29±1.81) , 6 h (-1.24±1.72) , and 12 h (-1.18±1.68; P>0.05) compared with that at baseline (0 h, -0.60±1.37) . Conclusion:Sample storage time, storage temperature, and vibration can interfere with the results of BCR-ABL and ABL copy number but have no significant effect on the quantitative determination of BCR-ABL (P210) transcript levels. This study provides strong support for the feasibility of transregional transportation of peripheral blood samples from patients with CML.

Objective To validate a cell infection-based quantitative RT-PCR for evaluating the potency of rotavirus vaccine. Methods According to the ICH ( the International Council for Harmonization) Harmonised Tripartite Guideline, the method was validated for its specificity, accuracy, precision, linearity and robustness. Results The method had good specificity as it could only amplify and detect the corre-sponding type of rotavirus strain. The recovery rates for determining the potency against rotaviruses of G2, G3 and G4 types were 97％ to 108％. The percent coefficient of variation ( CV) of both intra-plate and in-ter-plate precision was≤2. 62％, while the intraday and interday CV was≤1. 76％ and≤2. 27％, respec-tively. The CV between the two experimenters was≤7. 68％. The linearity range of the method was 4. 4-6. 5 UI for G2 type rotavirus, 3. 9-8. 3 UI for G3 type and 3. 5-8. 1 UI for G4 type. Good robustness was observed using the cells of 140 to 160 generations. Conclusions The cell infection-based quantitative RT-PCR was shown to have satisfactory specificity, accuracy, precision, linearity and robustness, suggesting that it was a suitable method for evaluating the potency of multivalent rotavirus live vaccines.

OBJECTIVE: To develop a digital breast tomosynthesis (DBT) imaging system with optimizes imaging chain. METHODS: Based on 3D tomography and DBT imaging scanning, we analyzed the methods for projection data correction, geometric correction, projection enhancement, filter modulation, and image reconstruction, and established a hardware testing platform. In the experiment, the standard ACR phantom and high-resolution phantom were used to evaluate the system stability and noise level. The patient projection data of commercial equipment was used to test the effect of the imaging algorithm. RESULTS: In the high-resolution phantom study, the line pairs were clear without confusing artifacts in the images reconstructed with the geometric correction parameters. In ACR phantom study, the calcified foci, cysts, and fibrous structures were more clearly defined in the reconstructed images after filtering and modulation. The patient data study showed a high contrast between tissues, and the lesions were more clearly displayed in the reconstructed image. CONCLUSIONS This DBT imaging system can be used for mammary tomography with an image quality comparable to that of commercial DBT systems to facilitate imaging diagnosis of breast diseases.
Algorithms ; Artifacts ; Breast ; diagnostic imaging ; Female ; Humans ; Mammography ; methods ; Phantoms, Imaging ; Radiographic Image Enhancement ; methods

OBJECTIVE: To develop a deep features-based model to classify benign and malignant breast lesions on full- filed digital mammography. METHODS: The data of full-filed digital mammography in both craniocaudal view and mediolateral oblique view from 106 patients with breast neoplasms were analyzed. Twenty-three handcrafted features (HCF) were extracted from the images of the breast tumors and a suitable feature set of HCF was selected using -test. The deep features (DF) were extracted from the 3 pre-trained deep learning models, namely AlexNet, VGG16 and GoogLeNet. With abundant breast tumor information from the craniocaudal view and mediolateral oblique view, we combined the two extracted features (DF and HCF) as the two-view features. A multi-classifier model was finally constructed based on the combined HCF and DF sets. The classification ability of different deep learning networks was evaluated. RESULTS: Quantitative evaluation results showed that the proposed HCF+DF model outperformed HCF model, and AlexNet produced the best performances among the 3 deep learning models. CONCLUSIONS The proposed model that combines DF and HCF sets of breast tumors can effectively distinguish benign and malignant breast lesions on full-filed digital mammography.
Breast Neoplasms ; classification ; diagnostic imaging ; Deep Learning ; Diagnosis, Computer-Assisted ; methods ; Female ; Humans ; Mammography ; methods

OBJECTIVE: We propose a sparse-view helical CT iterative reconstruction algorithm based on projection of convex set tensor total generalized variation minimization (TTGV-POCS) to reduce the X-ray dose of helical CT scanning. METHODS: The three-dimensional volume data of helical CT reconstruction was viewed as the third-order tensor. The tensor generalized total variation (TTGV) was used to describe the structural sparsity of the three-dimensional image. The POCS iterative reconstruction framework was adopted to achieve a robust result of sparse-view helical CT reconstruction. The TTGV-POCS algorithm fully used the structural sparsity of first-order and second-order derivation and the correlation between the slices of helical CT image data to effectively suppress artifacts and noise in the image of sparse-view reconstruction and better preserve image edge information. RESULTS: The experimental results of XCAT phantom and patient scan data showed that the TTGVPOCS algorithm had better performance in reducing noise, removing artifacts and maintaining edges than the existing reconstruction algorithms. Comparison of the sparse-view reconstruction results of XCAT phantom data with 144 exposure views showed that the TTGV-POCS algorithm proposed herein increased the PSNR quantitative index by 9.17%-15.24% compared with the experimental comparison algorithm; the FSIM quantitative index was increased by 1.27%-9.30%. CONCLUSIONS The TTGV-POCS algorithm can effectively improve the image quality of helical CT sparse-view reconstruction and reduce the radiation dose of helical CT examination to improve the clinical imaging diagnosis.

Objective: To analyze the correlation between circumcision and incidence and clearance of male genital HPV infection. Methods: From May to July 2014, 18-55 year old men who had sexual behavior history were recruited from the general population in Liuzhou, Guangxi to set up a cohort. Totally, 113 circumcised and 560 uncircumcised men were enrolled and interviewed using a questionnaire (including information on demographic characteristics and sexual behaviors), then they were followed-up with 6-month interval for 2 times. On each visit, specimens of male external genitalia were collected and genotyped for HPV DNA. The differences of incidence and clearance of genital HPV infections between circumcised and uncircumcised men were analyzed by Log-rank test. Cox regression was used to analyze the relationship between circumcision and incidence and clearance of HPV infection. Results: The median age (P₂₅, P₇₅) of circumcised and uncircumcised men were 28 (24, 35) and 32 (24, 31), respectively. The incidences of any HPV infections were 9.1 (95%CI: 2.4-15.7) and 8.4 (95% CI: 5.6-11.2) per 1 000 person-months (χ²=0.10, P=0.758), respectively. The clearance of circumcised men [136.3 (95%CI: 70.0-202.7) per 1 000 person-months] was higher than that in uncircumcised men [89.6 (95%CI: 65.9-113.3) per 1 000 person-months] (χ²=8.19, P=0.004). In multivariate COX regression analysis, compared with uncircumcised men, circumcised men had higher possibility to clear any HPV infections (HR: 2.41, 95%CI: 1.30-4.46). Compared with men having one sexual partner, people having more than 4 sexual partners had lower possibility to clear any HPV infections (HR: 0.49, 95%CI: 0.25-0.96). Compared with 18-25 years old men, men aged 26-35 years old had higher possibility to clear high-risk HPV infections (HR: 2.14, 95%CI: 1.08-4.23). Conclusion Circumcised and uncircumcised men had similar incidence of genital HPV infection, whereas, men conducted circumcision and having fewer sexual partners could increase the clearance of genital HPV infections.

OBJECTIVE: To establish a cone beam computed tomography (ECBCT) system for high-resolution imaging of the extremities. METHODS: Based on three-dimensional X-Ray CT imaging and high-resolution flat plate detector technique, we constructed a physical model and a geometric model for ECBCT imaging, optimized the geometric calibration and image reconstruction methods, and established the scanner system. In the experiments, the pencil vase phantom, image quality (IQ) phantom and a swine feet were scanned using this imaging system to evaluate its effectiveness and stability. RESULTS: On the reconstructed image of the pencil vase phantom, the edges were well preserved with geometric calibrated parameters and no aliasing artifacts were observed. The reconstructed images of the IQ phantom showed a uniform distribution of the CT number, and the noise power spectra were stable in multiple scanning under the same condition. The reconstructed images of the swine feet had clearly displayed the bones with a good resolution. CONCLUSIONS The ECBCT system can be used for highresolution imaging of the extremities to provide important imaging information to assist in the diagnosis of bone diseases.
Algorithms ; Animals ; Artifacts ; Calibration ; Cone-Beam Computed Tomography ; instrumentation ; methods ; Equipment Design ; Extremities ; diagnostic imaging ; Image Processing, Computer-Assisted ; methods ; Phantoms, Imaging ; Radiographic Image Enhancement ; instrumentation ; methods ; Swine