An Investigation of Microwave Tomography Technique to Image Brain Tumour Through Cross-Section Imaging with Different Number of Electrode

Brain tumours resulted from the irregular growth and cell division within the skull, indicating a high risk for malignancies to develop and can lead to brain injury or even death. The brain tumour can affect nervous system’s function based on the tumour’s growth rate and location. Early detection of brain tumour is essential to improve patients’ survival rates through appropriate medical care. As the current clinical imaging has a few impediments e.g.  radiation-based and expensive, tomography technique is seen possible to provide safe and inexpensive technology. The aim of this research is to investigate the feasibility of brain tumour detection using microwave tomography technique with different numbers of electrodes. The 2D finite element modelling approach is applied, and the images are reconstructed using a linear back projection (LBP) algorithm in MATLAB. A different number of rectangular sensing electrodes are arranged around the head phantom in an elliptical array, working in pairs as transmitters and receivers. The simulation shows that the system is able to detect the permittivity difference, thus detecting the existence of the tumour in the head phantom.Theimage reconstruction presented promising tumour images with an 8-antenna microwave tomography system at all locations, i.e. left, right, top, centre, and bottom, in comparison to 4-antenna and 12-antenna systems. &nbsp

An Investigation of Microwave Tomography Technique to Image Brain Tumour Through Cross-Section Imaging with Different Number of Electrode

Brain tumours resulted from the irregular growth and cell division within the skull, indicating a high risk for malignancies to develop and can lead to brain injury or even death. The brain tumour can affect nervous system’s function based on the tumour’s growth rate and location. Early detection of brain tumour is essential to improve patients’ survival rates through appropriate medical care. As the current clinical imaging has a few impediments e.g.  radiation-based and expensive, tomography technique is seen possible to provide safe and inexpensive technology. The aim of this research is to investigate the feasibility of brain tumour detection using microwave tomography technique with different numbers of electrodes. The 2D finite element modelling approach is applied, and the images are reconstructed using a linear back projection (LBP) algorithm in MATLAB. A different number of rectangular sensing electrodes are arranged around the head phantom in an elliptical array, working in pairs as transmitters and receivers. The simulation shows that the system is able to detect the permittivity difference, thus detecting the existence of the tumour in the head phantom.Theimage reconstruction presented promising tumour images with an 8-antenna microwave tomography system at all locations, i.e. left, right, top, centre, and bottom, in comparison to 4-antenna and 12-antenna systems. &nbsp

Investigation of relaxation factor in landweber iterative algorithm for electrical capacitance tomography

It is crucial to select a suitable relaxation factor in iterative image reconstruction algorithms (e.g. Landweber iterative algorithm) for electrical capacitance tomography (ECT) because it affects the convergence. By simulation, it is found notably that the relaxation factor should be selected adaptively according to the sensor structure (e.g. the number of electrodes) and the permittivity distribution in capacitance measurements. With different number of electrodes and four typical permittivity distributions, the relaxation factor and the related convergence are investigated in consideration of the change in relative image error. It is shown that the relaxation factor can be chosen based on the upper boundary of all relaxation factors. The conclusions in this paper can be used for practical industrial processes, regarding the adaptive selection of relaxation factor and the number of iterations needed

Accident prediction model by relating integrated design consistency model

The number road accident kept rising in every year in Malaysia. In early 2016, Johor has been mentioned as the among highest-ranking road accident at hazard road locations. The main accidents occur are a road accident with passenger cars, road accident with other motorcycles and single-motorcycle road accidents. Furthermore, the problem road accident on hazard road location are still unsolved, especially for main road accident types of vehicle; motorcycles and cars. The study location segments were selected at Johor Federal Route 50; KM1- KM5. Therefore, this study using an accident prediction model by relating integrated design consistency model, through a comprehensive speed characteristic using a global positioning system and based on an operating profile to develop a continuous speed profile between motorcycles and cars and to determine design consistency models. Poisson model is used to relate road design consistency models and accident rates to evaluate the impact of design consistency with road safety

An Investigation of Microwave Tomography Technique to Detect Brain Tumour Through Cross-Section Imaging at Frequency 0.5 GHz to 1.5 GHz

The growing significance of cancerous tissue including brain tumour requires a fast and efficient technology detection. The most current technologies being applied for brain imaging system are Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI). Whilst these two detection applications are very well established, both systems are expensive, time and space consuming, and raise safety issues to patients due to the radiation and strong magnetic effects. This research aims to assess the feasibility and potential performance of microwave tomography (MWT) for brain imaging with a particular focus on brain tumour detection. The study was conducted using Finite Element Model software, COMSOL Multiphysics to develop a 2D modelling of an antenna array and measure the scattered electric field by solving forward problem. MATLAB software will be used as an inverse problem solver to reconstruct 2D images of the tumour by using Linear Back Projection (LBP) algorithm

Smart Data Recognition System For Seven Segment LED Display

The automatic data capturing system provides an alternative and effective way of data collection instead of manual data collection in the laboratory, especially for experiments that need to be carried out for a long period. It can solve common mistakes made by humans, like misreading or mistyping data. Thus, a new smart data recognition system for a seven-segment LED display is developed to sort the whole process of data collection to become more systematic and accurate. An image is captured and saved automatically in an image file, and then it is processed through MATLAB software to identify the digits displayed on the LED display. Once the image is preprocessed, analyzed, and recognized, the final output values obtained are transferred to an existing Excel file for a further process according to the user’s requirement. From the results obtained, it was proven that binary thresholding is the best preprocessing method, and the brightness of the image should be set to ‘0’ for better recognition output

Smart bus terminal using infrared identification

Significant increase in vehicles inside city areas results in adding more troubles to that section of citizens using public transportation network as their primary source of travelling. This specific section of society is a victim of this rapid growing traffic volume and causing a huge waste of time due to not having proper information of required bus current position. The problem results in not only wasting of time but also mentally unhappy and tensed citizens. Nowadays, passengers want to get the clear information of their desired buses at station, like the position and estimated time of arrival of bus etc. The implementation of Intelligent Transportation Systems (ITS) nowadays has developed to the incredible extent. This system is proved that is to be very useful not only in the safety purpose but also it eases to any users. The combination with infrared can use to monitor and identify the location of certain bus and present it the information to the bus passenger on LCD at terminal by using the simulation. The tag and the reader of the infrared devices are wirelessly connected and control station can authorize not only to monitor the bus but can also identify the particular of the bus such as bus registration number and bus company names

Review of wire-mesh tomography in different experiments

Wire-mesh tomography is completely new to the tomography field. First founded in 1998, the wire-mesh tomography had been used in several sectors as secondary optional sensors. This sensor can be used to gain void fraction distribution in multiphase flow visualization. By using tomography techniques, several measurements like velocity or phase fraction boundaries can be determined and analysed. The sensor basically built perpendicularly as transmitter and receiver layer located above and below respectively. With wires made of tinned copper and 16 sensors for each layer, the tomography is considered low-cost, easy built and can sustain in a harsh environment to investigate multiphase flow. As an instantaneous tomography method, wire-mesh tomography has advantage in speed but has less image resolution because classic wire-mesh tomography image reconstruction methods only provide same amount of pixels as measurement number. In order to increase image resolution, a new image reconstruction method based on sensitivity map is proposed, which is of providing more pixels (sub pixels) by solving inverse problem with capacitive wire-mesh tomography image reconstruction. The image reconstruction algorithms, including the traditional wire-mesh direct image reconstruction algorithm, the linear back projection, the projected Landweber iteration, and the total variation based iteration, are conducted and the results are compared each other

Wire-mesh tomography sensors for multiphase flow investigations

Wire-mesh tomography is new to the tomography field. First founded in 1998, the wire-mesh tomography had been used in several sectors as secondary optional sensors. The wire-mesh sensor can be used to gain void fraction distribution in multiphase flow visualization. By using tomography techniques, several measurements like velocity or phase fraction boundaries can be determined and analysed. The sensor basically built perpendicularly as transmitter and receiver layer located above and below respectively. The sensor wires are made of copper and 16 sensors for each layer, those sensors are considered low-cost, easy built and withstand a harsh environment to investigate multiphase flow. Traditional wire-mesh tomography image reconstruction methods only supply the same number of pixels as the measurement number, therefore wire-mesh sensors have a speed benefit but a lower image resolution. The findings from the previous experiments indicate difference in capacitance and other factors on the output

Wire mesh tomography system for horizontal two-phase fluid flow investigation

Simultaneous flow of liquid and gas is commonly found in process industries, such as petroleum pipeline transport, chemical process, oil and gas pipeline transport and many more. Phase distribution monitoring and visualizing for such flow is important to ensure the operation safeness and effectiveness. This study aims to investigate wire-mesh tomography system on solid-free two-phase flow monitoring and visualization. Experiment was conducted on a horizontal liquid/gas flow with an inner diameter of 84mm. A 16 x 16 wire-mesh sensor was designed and applied in this study to obtained the raw data from the target flow. The sensor worked together with transceiver circuit and data acquisition and image reconstruction software to visualize the flow condition and void fraction. Tomogram images were resulted as the final results of this experiment