Value of fusion of MRI texture features in diagnosis of prostate cancer / 中国医学影像技术

Objective: To explore the value of three-dimensional optimization of threshold local ternary pattern (LTP) texture features, conventional texture features and grayscale statistical features fusion features for diagnosis of prostate cancer. Methods The peripheral zone of prostate was segmented from multi-sequence MR images. The optimization of the threshold LTP texture features, the conventional texture features and the grayscale statistical features was extracted. The fusion features were classified with Adaboost algorithm. The diagnostic efficacy was analyzed. Results: AUC of three-dimensional optimization of the threshold LTP fusion texture feature for predicting prostate cancer was 0.79±0.04, and the sensitivity, specificity and accuracy was 78.31% (65/83), 80.81% (80/99) and 79.67% (145/182), respectively. The AUC of conventional texture features for predicting prostate cancer was 0.71±0.04, and the sensitivity, specificity and accuracy was 72.29% (60/83), 81.82% (81/99), 77.47% (141/182), respectively. The AUC of grayscale statistical features for predicting prostate cancer was 0.80±0.04, and the sensitivity, specificity and accuracy was 78.31% (65/83), 82.83% (82/99), 80.77% (147/182), respectively. The AUC of fusion features for predicting prostate cancer was 0.87±0.04, and the sensitivity, specificity and accuracy was 86.75% (72/83), 88.89% (88/99) and 87.91% (160/182), respectively. Conclusion: The diagnostic efficacy of prostate cancer can be effectively improved by fusing local ternary patterns features, conventional texture features and grayscale statistical texture features.

Real-time Event Recognition and Analysis System for Nanopore Study / 分析化学

To achieve fast and accurate analysis of weak current signal of nanopore-based single molecule detection, we designed a real-time adaptive threshold data processing algorithm with data buffering technique and finite impulse response filtering. The system, which is designed based on the data processing algorithm, could realize real-time recognition and analysis of nanopore events during the data recording process. In order to verify the performance of the system, the ideal signals with different noise level (20-100 pA) and recording bandwidth (3 - 100 kHz) was generated. The results showed that the system was stable to analyze the generated signals even at high noise. In addition, the system was also suitable for the data recording conditions of low bandwidth and high sampling rate (250 kHz). The proposed nanopore data processing system was further applied in the Aerolysin nanopore experiment for the detection of poly(dA) 4 molecules. The results showed that the data processing system could be applied in real nanopore recording system with high accuracy and speed.

Quantitative Assessment Technology of Small Animal Myocardial Infarction PET Image Using Gaussian Mixture Model / 의학물리

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq 18F-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, em leader MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were 7.04+/-3.44%, 3.87+/-2.09% and 2.15+/-2.07%, respectively. Otsu verse reference infarct size was 3.56+/-4.16%. MGMM methods verse reference infarct size was 2.29+/-1.94%. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.