Mammography is one of the most commonly applied tools for early breast cancer screening. Automatic segmentation masses in mammograms essential but challenging due to low signal-to-noise ratio and wide variety mass shapes sizes. Existing methods deal with these challenges mainly by extracting mass-centered image patches manually or automatically. However, manual patch extraction time-consuming automatic brings errors that could not be compensated following step. In this study, we propose a...

Gliomas are the most common primary brain tumors, and objective grading is of great importance for treatment. This paper presents an automatic computer-aided diagnosis gliomas that combines segmentation radiomics, which can improve diagnostic ability. The MRI data containing 220 high-grade 54 low-grade used to evaluate our system. A multiscale 3D convolutional neural network trained segment whole tumor regions. wide range radiomic features including first-order features, shape texture...

Small cell lung cancer (SCLC) is one of the most common types malignant tumors, characterized by rapid growth and early metastasis spread. Early accurate diagnosis SCLC vital for improved survival. Accurate segmentation helps doctors understand location size make better diagnostic decisions. However, manual cancers from large amounts medical images a time-consuming challenging task. In this paper, we propose hybrid network (referred to as HSN) based on convolutional neural (CNN)...

Abstract Gliomas segmentation is a critical and challenging task in surgery treatment, it also the basis for subsequent evaluation of gliomas. Magnetic resonance imaging extensively employed diagnosing brain nervous system abnormalities. However, tumor remains task, because differentiating tumors from normal tissues difficult, boundaries are often ambiguous there high degree variability shape, location, extent patient. It therefore desired to devise effective image architectures. In past few...

In this study, chitosan (CS) was grafted onto the surface of polylactic acid (PLA) film by covalent immobilization to prepare four kinds CS-grafted PLA (CS-g-PLA) films with different molecular weights. The properties were characterized, and their antibacterial effect mechanism action against Staphylococcus aureus (S. aureus) explored. After being treated CS-g-PLA films, cell morphology destroyed, permeability membrane changed, malate dehydrogenase (MDH) activity decreased. Furthermore,...

Investigations about prevalence of obesity in psoriasis patients are increased nowadays. Higher serum levels leptin with who overweight or obese suggest that may serve as a molecular link between and metabolic comorbidities. However, the pathological functions not clearly understood. We investigated influence being on risk psoriasis, relationship severity Chinese Han patients. also biological effects proliferation secretion pro-inflammatory cytokines by human keratinocytes vitro. Obesity was...

Development of denoising algorithm for 3D acceleration signals is essential to facilitate accurate assessment human movement in body sensor networks (BSN). In this study, firstly were captured by self-developed nine-axis wireless BSN platform during 12 subjects performing regular walking. Then, noise was filtered using four common filters respectively: median filter, Butterworth low-pass discrete wavelet package shrinkage and Kalman filter. Finally, signal-to-noise ratio (SNR) correlation...

Brain tumor segmentation from magnetic resonance images is a critical step for early diagnosis and treatment. However, accurate general of brain still challenging task due to complicated characteristics in images. To solve this problem, we proposed novel method based on features separated local square. The basically consists three steps: superpixel segmentation, feature extraction model construction. In the first step, algorithm was used partition an image into homogeneous regions with...

Electrocardiographic (ECG) signal are often contaminated with different types of noise and base-line drift. A morphological filtering approach was put forward to remove the ECG signals calibrate drift in this paper. Different sizes structuring elements were used process for nature noise. The is simple, fast real-time processing, it keeps shape unchanged while removing An experiment carried out simulate LABVIEW, shown that effective calibrating

In this paper, a two-step segmentation method is developed for segmenting the hematoma area from brain CT images. The volume of calculated after segmentation. During second process, two-dimensional entropy introduced to separate hematoma. using entropy, most important find optional threshold which can be achieved by an improved genetic algorithm (GA) i.e. hierarchical (HGA). HGA more efficient than simple GA in overcoming shortcoming standard local optimal solution and low precision...

As the standard especially for storage and transmission of medical images, Digital Imaging Communications in Medicine (DICOM) is popular to people world. And as a result, almost all outputs computerized tomography (CT), magnetic resonance (MR), digital subtraction angiography (DSA) ultrasonography (US) are saved DICOM format. However, format files can be opened by original programs windows OS, which not convenient with further research image processing. The paper mainly does some conversion...

This paper mainly does some research on the problem of information exchange between HIS and PACS, which is starving for solution in construction hospital digitalization. system deals with patient information, it follows standard HL7.While PACS manages image DICOM 3.0. Because deal different follow standards, difficult to directly communicate. presents a method establishing HL7/DICOM gateway realize PACS. The designed this made up three modules. First, HL7 messages triggered events are...

According to the features of configuration and color information on cancer cells, an adaptive automatic threshold segmentation based RGB HIS spaces is presented, which available segment suspected cells nucleus from complex backgrounds in microscopic images. The edges are detected by using Canny operator. Using technology eight-chain code tracking, feature values extracted. consists perimeter, area, height, width, circularity, rectangularity, extension area ratio between cytolympth. Based...

A wearable monitoring system with multiple physiological parameter is studied in this paper. It a terminal of Home Assistant Robot. Non-invasive technology used system. The details ECG monitoring, blood pressure glucose and temperature are discussed This for home application. small size, easy to use. plays positive role promoting the level health care first aid emergency illness.

Feature classification is one of the important aspects in Brain-computer interfaces (BCI) system. It has been known that a higher precision can be achieved if use neutral networks proper way for feature classification. In this paper, three identification ways were introduced and discussed. experiment left-right hand classification, arithmetic small mean square difference proposed studied, so as to get good converging task The design method input output layer BP neural network was Experiment...

Abstract A double-layer metal-insulation method using brass sheets as the insulators is proposed in this paper. It can enhance contact resistivity while preserving greater thermal conductivity merit. The underlying mechanism of enhancement to increase number surfaces and degrade quality between insulators. Then, we wound a single-layer brass-insulation coil compare their resistivities, confirmed effectiveness method. Furthermore, since capacity withstand overcurrent weakened with increasing...

Mammography is one of the most commonly applied tools for early breast cancer screening. Automatic segmentation masses in mammograms essential but challenging due to low signal-to-noise ratio and wide variety mass shapes sizes. Existing methods deal with these challenges mainly by extracting mass-centered image patches manually or automatically. However, manual patch extraction time-consuming automatic brings errors that could not be compensated following step. In this study, we propose a...

In order to improve the analysis accuracy of PMSM control performance, this paper improves mathematical model considering SVPWM modulation index and actual integrated voltage loss. And it presents an analytic method performance based on saturated parameters PMSM. By compared with experimental results, we verified kind quantitative applying both Maximum Torque per Ampere (MTPA) strategy vector in flux weakening region has higher accuracy. Combined original can be used jointly designed for...

Identification and classification technology plays an important part in study of the BCI system. There are many algorithms to classify event different task related. Here, finger movement was used as basic typical tasks be identified experiments. The ideas BP ERD were introduced discussed. CSSD (common spatial subspace decomposition) algorithm for classifying single-trial EEG during preparation left-right movements after two kinds phenomena expounded detail this paper. Experiment simulating...

An EEG analyzing system based on advanced RISC machines (ARM) and μC/os-II real time operating is discussed in this paper. The detailed design including the producing of event signals synchronization between described. details data acquisition, preprocessing, transmitting through USB configurations are also contained design. In paper high capability amplifier software embedded subsystem discussed. Also realizing multi-task μC/os-II, definition communicating protocols PC equipment detail...

For many years brain-computer interfaces research programs have been very popular. The classification algorithm of the EEG signals has attracted much attention. In this paper, an experiment is designed on imaginary left or right hand movements and a new proposed to identify different patterns. Butterworth filter applied retrieve useful signals. Interference noise eliminated using digital filter. wavelet entropy treated as one feature in our approach. adaptive autoregressive model combined...