JOURNAL OF MEDICAL SIGNALS AND SENSORS (JMSS)
Year:2018 | Volume:8 | Issue:1|Papers Count:8

Background: Gene expression data are characteristically high dimensional with a small sample size in contrast to the feature size and variability inherent in biological processes that contribute to difficulties in analysis. Selection of highly discriminative features decreases the computational cost and complexity of the classifier and improves its reliability for prediction of a new class of samples. Methods: The present study used hybrid particle swarm optimization and genetic algorithms for gene selection and a fuzzy support vector machine (SVM) as the classifier. Fuzzy logic is used to infer the importance of each sample in the training phase and decrease the outlier sensitivity of the system to increase the ability to generalize the classifier. A decision-tree algorithm was applied to the most frequent genes to develop a set of rules for each type of cancer. This improved the abilities of the algorithm by finding the best parameters for the classifier during the training phase without the need for trial-and-error by the user. The proposed approach was tested on four benchmark gene expression profiles. Results: Good results have been demonstrated for the proposed algorithm. The classification accuracy for leukemia data is 100%, for colon cancer is 96.67% and for breast cancer is 98%. The results show that the best kernel used in training the SVM classifier is the radial basis function.Conclusions: The experimental results show that the proposed algorithm can decrease the dimensionality of the dataset, determine the most informative gene subset, and improve classification accuracy using the optimal parameters of the classifier with no user interface.

Background: Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. Methods: In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation.Results: Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Conclusions: Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

Background: Accurate delivery of the prescribed dose to moving lung tumors is a key challenge in radiation therapy. Tumor tracking involves real-time specifying the target and correcting the geometry to compensate for the respiratory motion, that’s why tracking the tumor requires caution. This study aims to develop a markerless lung tumor tracking method with a high accuracy.Methods: In this study, four-dimensional computed tomography (4D-CT) images of 10 patients were used, and all the slices which contained the tumor were contoured for all patients. The first four phases of 4D-CT images which contained tumors were selected as input of the software, and the next six phases were considered as the output. A hybrid intelligent method, adaptive neuro-fuzzy inference system (ANFIS), was used to evaluate motion of lung tumor. The root mean square error (RMSE) was used to investigate the accuracy of ANFIS performance for tumor motion prediction. Results: For predicting the positions of contoured tumors, the averages of RMSE for each patient were calculated for all the patients. The results showed that the RMSE did not have a major variation. Conclusions: The data in the 4D-CT images were used for motion tracking instead of using markers that lead to more information of tumor motion with respect to methods based on marker location.

Background: MapCHECK2 is a two-dimensional diode arrays planar dosimetry verification system. Dosimetric results are evaluated with gamma index. This study aims to provide comprehensive information on the impact of various factors on the gamma index values of MapCHECK2, which is mostly used for IMRT dose verification.Methods: Seven fields were planned for 6 and 18 MV photons. The azimuthal angle is defined as any rotation of collimators or the MapCHECK2 around the central axis, which was varied from 5 to -5o. The gantry angle was changed from -8 to 8o. Isodose sampling resolution was studied in the range of 0.5 to 4 mm. The effects of additional buildup on gamma index in three cases were also assessed. Gamma test acceptance criteria were 3%/3 mm. Results: The change of azimuthal angle in 5o interval reduced gamma index value by about 9%. The results of putting buildups of various thicknesses on the MapCHECK2 surface showed that gamma index was generally improved in thicker buildup, especially for 18 MV. Changing the sampling resolution from 4 to 2mmresulted in an increase in gamma index by about 3.7%. The deviation of the gantry in 8° intervals in either directions changed the gamma index only by about 1.6% for 6 MV and 2.1% for 18 MV.Conclusion: Among the studied parameters, the azimuthal angle is one of the most effective factors on gamma index value. The gantry angle deviation and sampling resolution are less effective on gamma index value reduction.

Background: Dosimetric accuracy in intensity-modulated radiation therapy (IMRT) is the main part of quality assurance program. Improper beam modeling of small fields by treatment planning system (TPS) can lead to inaccuracy in treatment delivery. This study aimed to evaluate of the dose delivery accuracy at small segments of IMRT technique using two-dimensional (2D) array as well as evaluate the capability of two TPSs algorithm in modeling of small fields.Methods: Irradiation were performed using 6 MV photon beam of Siemens Artiste linear accelerator. Dosimetric behaviors of two dose calculation algorithms, namely, collapsed cone convolution/superposition (CCCS) and full scatter convolution (FSC) in small segments of IMRT plans were analyzed using a 2D diode array and gamma evaluation. Results: Comparisons of measurements against TPSs calculations showed that percentage difference of output factors of small fields were 2% and 15% for CCCS and FSC algorithm, respectively. Gamma analysis of calculated dose distributions by TPSs against those measured by 2D array showed that in passing criteria of 3 mm/3%, the mean pass rate for all segment sizes is higher than 95% except for segment sizes below 3 cm × 3 cm optimized by TiGRT TPS.Conclusions: High pass rate of gamma index (95%) achieved in planned small segments by Prowess relative to results obtained with TiGRT. This study showed that the accuracy of small fi eld modeling differs between two dose calculation algorithms.

Background: Long-term healing tissue engineering scaffolds must hold its full mechanical strength at least for 12 weeks. Nano-micro scaffolds consist of electrospinning nanofibers and textile microfibers to support cell behavior and mechanical strength, respectively.Methods: The new nano-micro hybrid scaffold was fabricated by electrospinning poly 3-hydroxybutyrate-chitosan-multi-walled carbon nanotube (MWNT functionalized by COOH) solution on knitted silk in a random manner with different amounts of MWNT. The physical, mechanical, and biodegradation properties were assessed through scanning electron microscopy, Fourier-transform infrared (FTIR) spectroscopy, water contact angle test, tensile strength test, and weight loss test. The scaffold without MWNT was chosen as control sample.Results: An increase in the amount of MWNT up to 1 wt% leads to better fiber diameter distribution, more hydrophilicity, biodegradation rate, and higher tensile strength in comparison with other samples. The porosity percentage of all scaffolds is more than 80%. According to FTIR spectra, the nanofibrous coat on knitted silk did not have any effect on silk fibroin crystallinity structures, and according to tensile strength test, the coat had a significant effect on tensile strength in comparison with pure knitted silk (P≤0.05). The average fiber diameter decreased due to an increase in electrical conductivity of the solution and fiber stretch in electrical field due to MWNTs. The scaffold containing 1 wt% MWNT was more hydrophilic due to the presence of many COOH groups of functionalized MWNT, thus an increase in the hydrolysis and degradation rate of this sample.Conclusions: High intrinsic tensile strength of MWNTs and improvement of nano-micro interface connection lead to an increase in tensile strength in scaffolds containing MWNT.

The operational transconductance amplifier-capacitor (OTA-C) filter is one of the best structures for implementing continuous-time filters. It is particularly important to design a universal OTA-C filter capable of generating the desired filter response via a single structure, thus reducing the filter circuit power consumption as well as noise and the occupied space on the electronic chip. In this study, an inverter-based universal OTA-C filter with very low power consumption and acceptable noise was designed with applications in bioelectric and biomedical equipment for recording biomedical signals. The very low power consumption of the proposed filter was achieved through introducing bias in subthreshold MOSFET transistors. The proposed filter is also capable of simultaneously receiving favorable low-, band-, and high-pass filter responses. The performance of the proposed filter was simulated and analyzed via HSPICE software (level 49) and 180 nm complementary metal-oxide-semiconductor technology. The rate of power consumption and noise obtained from simulations are 7.1 nW and 10.18 nA, respectively, so this filter has reduced noise as well as power consumption. The proposed universal OTA-C filter was designed based on the minimum number of transconductance blocks and an inverter circuit by three transconductance blocks (OTA).

Computed tomography coronary angiography (CTCA) has generated a great interest over the past two decades, due to its high diagnostic accuracy and efficacy in the assessment of patients having coronary artery disease. This method is associated with high radiation dose and this has raised serious concerns in the literature. Effective dose (E) is a single parameter meant to reflect the relative risk from exposure to ionizing radiation. Therefore, it is necessary to calculate this parameter to indicate ionizing radiation relative risk. The aim of this study was to calculate the effective dose from 64-slice CTCA in Isfahan. To calculate the effective dose, an ionization chamber and a body phantom with diameter of 32 cm and length of 15 cm were used. CTCA radiation conditions commonly used in two centers were applied for this work. For all scans, computed tomography volume dose index (CTDIv), dose-length product (DLP), and effective dose were obtained using dose-length-product method. The obtained CTDIv, DLP, and effective dose were compared in two centers, and mean, maximum, and minimum values of effective dose for heart coronary CT angiography (CCTA) examinations and calcium score were compared with other studies. The amount of average, maximum, and minimum effective doses for heart CCTA examinations in two centers are 4.65 ± 0.06, 6.0489, and 3.492 mSv, respectively, and for calcium score test are, 1.04 ± 0.04, 2.155, and 0.98 mSv, respectively. CTDIv, DLP, and effective dose values did not show any significant difference in two centers. Although the effective dose of CTCA and calcium score was lower than that of other studies, it is reasonable to reduce the effective dose to the minimum possible value to reduce the risk of cancer associated with ionizing radiation. The results of this study can be used to introduce the effective dose as a local diagnostic reference dose (DRL) for CTCA examinations in Isfahan Province.