2017, 6(5):1-7. DOI: 10.12146/j.issn.2095-3135.201705001
Abstract:In this paper, magnetic polymer microspheres were prepared via emulsion-solvent evaporation method, with magnetic Fe3O4 nanoparticles and biodegradable polymer poly(lactic-co-glycolic acid). The structures and properties of microspheres were characterized with Fourier transform infrared spectroscopy, thermogravimetric analysis, transmission electron microscopy and vibrating sample magnetometer, and the electromagnetic induction heating property was also investigated. The obtained two magnetic polymer microspheres with Fe3O4 content of 10.1% and 18.8% exhibited saturation magnetization values of 2.3 emu/g and 6.8 emu/g, and temperature increased 9℃ and 16.5℃ under the electromagnetic induction. Results suggest that the obtained magnetic polymer microspheres meet the heating requirement of hyperthermia and have potential applications in magnetic hyperthermia or thermochemotherapy of cancer.
2017, 6(5):8-18. DOI: 10.12146/j.issn.2095-3135.201705002
Abstract:In recent years, with the continuous development of GPU general computing power, more efficient processing technologies have been for image processing. At present, some image processing algorithms have been transplanted to GPU and have good effect in acceleration. However these algorithms do not make full use of the computing power of each processing unit in a hybrid systems composed by CPU/GPU. Based on GPU programming model and parallel algorithm design, we proposed image collaborative parallel processing model at CPU/GPU heterogeneous environment in this paper. The effectiveness of this model in high resolution grayscale image processing was verified by the image median filtering algorithm, which was based on the computing power of each processing unit in heterogeneous system. The experimental results show that the model performs well in CPU/GPU heterogeneous environment and is easy to execute other image processing algorithms.
2017, 6(5):19-31. DOI: 10.12146/j.issn.2095-3135.201705003
Abstract:Epilepsy refers to a set of chronic neurological syndromes characterized by transient and unexpected electrical disturbances of the brain. There are a large number of patients suffering from epilepsy in the world. Epilepsy cannot be cured eventually, but 70% of seizures can be kept under control by drugs. Electronic health records (EHRs) of epileptics contain a wealth of information for personalized medicine prescription, providing a large number of data resources. Based on real medical electronic cases for large data analysis, this paper proposes a drug recommendation system based on implicit feedback and crossing recommendation (IFCR) to help doctorschoose right drugs. The proposed system aims to analyze the patients’ medical history and similar patients’ in order to find the relationships between syndromes and drugs. Comparing our system with the one based on artificial neural network (ANN), the proposed algorithm performs much better than ANN in terms of the recall rate with a 30% improvement. However, two algorithms have different performance on the precision rate. In general, the performance of IFCR is better than that of ANN. Finally, we analyze the recommendation results of two algorithms and discover it is possible to propose an ensemble model to compile IFCR with ANN.
2017, 6(5):32-39. DOI: 10.12146/j.issn.2095-3135.201705004
Abstract:The Chan-Vese (CV) model has been widely investigated for breast ultrasound (BUS) image segmentation. However, the traditional CV model can not meet the requirement of high precision and speed for BUS segmentation. To address this issue, an improved CV model based on the ratio of exponentially weighted averages (ROEWA) operator was proposed in this paper. Firstly, the ROEWA of the BUS image was calculated. Then, a ROEWA-based edge indicator function was built to replace the Dirac term of traditional CV model. Finally, the smoothing term was removed to improve the speed of curve evolution. Experimental results show that the advantages of the proposed model in terms of computational efficiency and accuracy.
2017, 6(5):40-54. DOI: 10.12146/j.issn.2095-3135.201705005
Abstract:In recent years, due to the rapid development of 3D modeling technology, 3D model databases have been increasingly available on the Internet. More and more 3D models can be easily downloaded through the Internet. This has directly led to the development of 3D shape retrieval technology, in which the system needs to return a similar 3D model according to the user requirement. This paper presents a new 3D shape retrieval method, which takes a 3D model as input and the system automatically returns some models that are most similar to the input shape from the model database. For a given input model and every model in the database, first, generated a magnitude of 2D sketch images of the model from different perspectives by the computer. Next, foreach 2D sketch image generated, the algorithm applies Gabor filter to extract the local features of the image, and quantifies the features in order to obtain a histogram representing the sketch image. For each 3D model, we then obtain a number of histograms representing the model. Thus, by comparing the histograms of every two models, we can compute the similarity value between the two models, and so retrieve the most similar shape to the input shape. In brief, the proposed method is capable of extracting effective features of 3D model through 2D image analysis method and evaluating the similarity between models. Experimental results show that the proposed algorithm performs well on some public datasets.
2017, 6(5):55-68. DOI: 10.12146/j.issn.2095-3135.201705006
Abstract:Repetitive sequences are prevalent in genomes. A large number of experiments have confirmed that they play an important role in biological evolution. At present, the discovery and detection of the repetitive sequences have been becoming a hot topic of genomics. This paper summarizes the research progress in this regard, and briefly analyses the associated tools. Finally, the development of repetitive sequences in future is prospected.
2017, 6(5):69-75. DOI: 10.12146/j.issn.2095-3135.201705007
Abstract:In this study, transcriptome analysis was conducted on the microarray data sets of peripheral blood collected from patients with ischemic cardiomyopathy and controls. The analysis was carried out in two phases. In phase 1, by comparing three sets of ischemic cardiomyopathy samples versus healthy controls, we identified three key genes—fibroblast growth factor binding protein 2 (FGFBP2), glucose-fructose oxidoreductase domain containing 1 (GFOD1), and megalencephalic leukoencephalopathy with subcortical cysts 1 (MLC1). These were considered as the potential mRNA biomarkers candidates. In phase 2, two gene expression data sets were collected on three points in time (the day of attack, 4-6 days of recovery, and 6 months of recovery). Differential analysis of gene pathways revealed that the seizure and recovery group were involved in the inflammatory and immune pathways compared with the control group. The seizure and recovery group (4-6 days) were involvedin the metabolic pathways or nerve secretion compared with the 6 months of recovery group. The experimental results show that the three potential mRNA biomarkers (FGFBP2, GFOD1 and MLC1) can be involved different pathways of ischemic cardiomyopathy, exhibiting continuous changes in the biological process.
2017, 6(5):76-82. DOI: 10.12146/j.issn.2095-3135.201705008
Abstract:Infrared physiotherapy is a new method with the application of infrared light to human body parts, whose effect has been widely reported in the treatment of various diseases. Nowadays, the effectiveness of the infrared physiotherapy was generally assessed by the experience of the medical staff qualitatively. As the parameters of blood flow is the key of physiotherapy evaluation, using a noninvasive, safe, and real time monitoring way on blood flow during therapy will benefit guiding the physiotherapy arrangement to enhance the therapy effect. This paper proposes a method based on bioimpedance technology for infrared physiotherapy evaluation in human arm. Firstly, we choose the BIOPAC physiological information recorder as the core of measure system, with double-probe method to measure ECG signal, and four-probe way to synchronously measure the bioimpedance change of human arm before, during and after the infrared irradiation. Then removing baseline drift and extracting feature points by using wavelet transform, applying simple Bayesian model to ensure the stability of the feature points. The experimental results show that (1) The arm bioimpedance signal characteristic frequency matches the heart rate with an average difference 0.09%-1.60%. (2) After the infrared irradiation, the ratio between secondary and the main wave peaks of arm bioimpedance rises 3.91%-13.05%, namely, bioimpedance can represent the change in arm blood flow, and sensitive enough to make an evaluation of infrared physiotherapy.