Biomedical Engineering: Applications, Basis and Communications

Simulations for blood hydrodynamic problems have been still largely incomplete despite years of research, especially for the inlet of boundary conditions that served as an essential part in computational fluid dynamics simulations of blood flow in human arteries. In this paper, the four different velocities of inlet boundary conditions were tested and compared in the human arm arterial model developed by us previously. Based on the selected points of nine key areas in the blood model,¹⁴ we analyzed the calculation results of pressure and shear stress distributions in detail. Our results show that they are changeable in different $V_{max}$ (different peak velocities of inlet boundary). The results further show that the static pressure of the aortic tree is higher than the static pressure of the branch, while the shear stress of the aortic tree is lower than the shear stress of the branch. On the other hand, the velocities changed in different $V_{max}$, the vessel walls of max total deformation appear in the middle radial obviously, compared with the equivalent and shear stress show at the entrance and bifurcations. In all, the simulation results of the brachial arteries provide the wall deformation, pressure and shear stress characteristics in different $V_{max}$, and offer a new strategy to study the two-way coupling of hemodynamics in the arm arterial model.

Radiologic technologists face various types of patients during multi-detector computed tomography (CT) examinations. In emergency departments, it is common to have patients who cannot follow instructions for the examinations. The asymmetric axial view of the head CT might affect the correctness of the clinician’s diagnosis. This study aimed to assess the impact of head positioning on the image quality of head CT using two phantoms. All scans were performed on a 16-slice CT scanner. In the control group, the tilted angle of the phantoms was 0${}^{\circ }$, and no multiplanar reconstruction (MPR) was performed. In the experimental groups, the tilted angles of the phantoms were 5${}^{\circ }$, 10${}^{\circ }$ and 15${}^{\circ }$, respectively, and MPR was performed afterwards. The results showed that if the head was tilted during the head CT examinations, image asymmetry and artifacts appeared without MPR. After MPR, one phantom showed that there were significant differences and the other phantom showed no significant differences quantitatively in image symmetry and artifacts between experimental groups and the control group, while both phantoms showed no significant differences qualitatively in image symmetry and artifacts between experimental groups and the control group. Although MPR can correct the image asymmetry and artifacts caused by tilted head positioning to some extent, it consumes time. Therefore, technologists should position the head as exactly as possible when performing head CT examinations.

Colonoscopy has proven to be an active diagnostic tool that examines the lower half of the digestive system’s anomalies. This paper confers a Computer-Aided Detection (CAD) method for polyps from colonoscopy images that helps to diagnose the early stage of Colorectal Cancer (CRC). The proposed method consists primarily of image enhancement, followed by the creation of a saliency map, feature extraction using the Histogram of Oriented-Gradients (HOG) feature extractor, and classification using the Support Vector Machine (SVM). We present an efficient image enhancement algorithm for highlighting clinically significant features in colonoscopy images. The proposed enhancement approach can improve the overall contrast and brightness by minimizing the effects of inconsistent illumination conditions. Detailed experiments have been conducted using the publicly available colonoscopy databases CVC ClinicDB, CVC ColonDB and the ETIS Larib. The performance measures are found to be in terms of precision (91.69%), recall (81.53%), F1-score (86.31%) and F2-score (89.45%) for the CVC ColonDB database and precision (90.29%), recall (61.73%), F1-score (73.32%) and F2-score (82.64%) for the ETIS Larib database. Comparison with the futuristic method shows that the proposed approach surpasses the existing one in terms of precision, F1-score, and F2-score. The proposed enhancement with saliency-based selection significantly reduced the number of search windows, resulting in an efficient polyp detection algorithm.

The COVID-19 pandemic originated in Wuhan, China in December 2019 and has since affected over 200 countries worldwide. The highly contagious Coronavirus primarily affects the respiratory system, causing pulmonary inflammation that can be visualized through medical imaging such as CT and X-rays. Conventional testing methods include PCR and antibody tests. Shortage of test kits in hospitals as well as time taken for results to be received can be compensated through medical imaging. Therefore, there is a need for an automated system, which is accurate and robust in detection of Covid-19 from medical radiographs for clinical practice. The objectives of our study are as follows: (i) To segment the lung CT images using a hybrid watershed and fuzzy c-means algorithm. (2) To extract various textural features using the GLCM algorithm. (iii) To implement machine learning classifiers for classification of COVID and non-COVID image classes. Our dataset consisting of 60 chest CT images of COVID-19 and non-COVID-19 patients was pre-processed and segmented using a hybrid watershed and fuzzy c-means algorithm. Then, textural features were extracted from the segmented ROI using the GLCM algorithm. Finally, the images were classified into COVID and non-COVID classes using three machine learning classifiers namely Naïve Bayes, SVM and K-star. Naïve Bayes classifier achieved the highest accuracy of 95%, while SVM achieved 93% accuracy. The ROC curves were also obtained, with AUC of 0.98. Thus, our proposed system has shown promising results in the classification of lung CT images into the two classes namely COVID and non-COVID.

Diabetes causes higher levels of blood glucose and often leads to complications like foot ulcers. Hemoglobin present within the red blood cells (RBCs) combines with blood glucose to form glycated hemoglobin (HbA1c) and its higher levels lead to serious life-threatening conditions. The aim of this study was to investigate the shape and texture features of RBCs among various grades of diabetic foot ulcers (DFUs). The study population ($n=41$, age: $52.61\pm 8.33$ years) was grouped based on Wagner classification. Blood samples (5mL) were collected to determine the blood glucose and lipid profiles. A gray-level co-occurrence matrix (GLCM) was applied to obtain the textural information from the microscopic blood smear images. The Pearson test exhibited a negative correlation for HDL ($r=-0.69$, $p<0.01$) against HbA1c. A statistically significant correlation ($p<0.01$) was observed for area, perimeter, equiv-diameter, convex area, major AL and minor AL against HbA1c. The HDL and RBC morphological features (area, perimeter, equiv-diameter, convex area, major AL and minor AL) exhibited statistically significant differences ($p<0.01$) between the control and grade-2 groups. The texture features namely contrast ($F=3.4$, $p<0.05$) and homogeneity ($F=3.7$, $p<0.05$) exhibited statistically significant differences between the grade-2 and grade-0 subjects, depicting larger texture variations among the DFU subjects. The results affirmed that the features extracted from RBCs differ among various grades of DFUs.

CpG Island (CGI) is considered to be one of the important segments of deoxyribonucleic acid (DNA) sequences. Out of the various epigenetic events which are associated with CGIs, some such events are like: CGIs are useful in the prediction of promoter region and subsequently for gene prediction, CGIs’ contribution in finding the epigenetic reasons of cancer is of great importance, CGIs can be used to identify chromosome inactivation. Therefore, the exact and maximum number of CGIs hidden in DNA sequences need to explored. A lot of computational, transform-based approaches have been developed and reported in literature for the identification of CGIs in DNA sequences since last many years. The problem associated with transform-based approaches is that the domain of functioning of algorithm requires to be changed which can probably lead to biasing and result in loss of important information in terms of CGIs. Hence, to provide a solution to this issue, a modified P-spectrum-based approach has been proposed here which does not suffer from domain transformation issue. Also, the performance of proposed algorithm has been tested on a large data set of 100 DNA sequences of human species and the performance has been compared with other recently reported methods of CGIs identification in DNA sequences. The results obtained prove that the proposed algorithm is better than the existing methods in terms of identification of more number of CGIs in DNA sequences. Therefore, the proposed algorithm has been considered as an efficient approach to enhance the sensitivity of CGIs identification.

Yeast cultures of Saccharomyces cerevisiae were exposed to pulsed magnetic fields of low intensity. Field intensities from 0.92 mT to 2.73mT and frequencies of 20, 77.5, 135, 192.5 and 250Hz were employed. Proliferation and cell viability measurements were made in exposed and control cultures. For the frequency of 20Hz, statistically significant differences were found ($p<0.001$) in cell proliferation using field intensities of 1.81 and 2.71mT. No changes were observed at this frequency for lower field strengths. At 77.5Hz, only changes in proliferation were observed for 0.92mT ($p<0.001$). No changes were observed to any other frequency or intensity of the magnetic field. The cell viability studies were performed at different times, from 4 to 12h of exposure. At 1.81mT and 20Hz, an increase in colony-forming units (CFUs) of 26.1% was observed ($p<0.024$) at 4h, and after 10h of exposure the increase in CFUs was 51.5% ($p<0.001$). But when exposing the cells for 9h to a magnetic field of 2.71mT at 20Hz, the CFUs decreased by 25.9% ($p<0.003$), and at 0.92mT and 77.5Hz, a decrease in CFUs of 18.6% was observed ($p<0.019$) at 4h, while after 12 h of exposure an increase in CFU of 23.5% ($p<0.010$) was determined. These results suggest the presence of a frequency window between 20Hz and 77.5Hz, where the effects of the magnetic field are significant.

Abnormal flow in the ductus venosus can indicate fetal diseases such as chromosomal abnormalities, heart defects, hypoxia, and intrauterine growth restriction. However, the circulating blood flow to the fetus has not been studied in great detail, and doctors have obtained the necessary information to make the right decision about abortion before or even after birth using the data. In this paper, a comparative study is performed to determine blood velocity in ductus venosus using a combined method based on three-dimensional computational simulation and Doppler measurement. For this purpose, a model is proposed that has three paths, and the ratio of pressure to displacement in each path is calculated separately. The obtained results illustrate a linear relationship between the pressure and distance in first path and the greater the distance from the junction of the vessels, the lower the pressure in the path. Also, the greater the distance, the more pressure is created in the arteries in the second path. However, there is no linear relationship with pressure in the next path, although as the distance increases, the pressure decreases. The results demonstrate that the ductus venosus tolerates a higher level of displacement and pressure in comparison to the two other paths of the proposed model. The obtained results and velocity values can be considered as an indicator of any disease in the fetus.