Image Fusion Using Fuzzy Logic Pixel Fusion for Dual Modality Tomography System

2014 ◽  
Vol 70 (3) ◽  
Author(s):  
Jaysuman Pusppanathan ◽  
Mahdi Faramarzi ◽  
Fazlul Rahman Yunus ◽  
Nor Muzakkir Nor Ayob ◽  
Ruzairi Abdul Rahim ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Multiphase Flow ◽  
Image Fusion ◽  
Simulation Analysis ◽  
Sensor Arrays ◽  
Fusion Model ◽  
Cross Sectional ◽  
Dual Modality ◽  
Tomography System ◽  
Multisensory System

Process tomography has been widely investigated and developed over time. The aim of this method is to measure the cross-sectional distribution of multiphase flow parameters based on its sensing technique. These single modality approaches has its own limitation whereby combination of two or more modality could overcome this issue. Therefore, a dual modality tomography (DMT) emergence of electrical capacitance sensors and ultrasonic sensor arrays for multiphase liquid mixture measurement was proposed. This paper presents an image fusion model using fuzzy logic pixel fusion method to integrate information for multisensory system such as DMT. A simulation analysis was carried out to perform image fusion on both ECT and UT input images. The developed fusion model proven to be successful in visualizing multiphase flow measurement. Thus, further validation and assessments were employed on the acquired results.

A Novel Electrical Cpacitance Sensor Design For Dual Modality Tomography Multiphase Measurement

2013 ◽  
Vol 64 (5) ◽  
Author(s):  
Muhammad Jaysuman Pusppanathan ◽  
Fazlul Rahman Yunus ◽  
Nor Muzakkir Nor Ayob ◽  
Ruzairi Abdul Rahim ◽  
Fatin Aliah Phang ◽  
...  
Keyword(s):  
Multiphase Flow ◽  
Flow Measurement ◽  
Ultrasonic Tomography ◽  
Pipe Surface ◽  
Dual Modality ◽  
Tomography System ◽  
Imaging Result ◽  
Process Tomography ◽  
Single Sensor ◽  
Capacitance Tomography

Electrical capacitance tomography (ECT) is one of process tomography technique which is developed rapidly in recent years. ECT is an imaging technique to obtain the internal permittivity distribution of a vessel or pipe by using capacitance electrodes sensor. This method has been integrated with ultrasonic tomography as multimodality system to perform multiphase flow measurement such as crude oil separation and oil process industry. In the present paper, a novel type of ECT sensor was developed using copper FR4 material. The electrode sensors can be flexibly bend or curve to fit the pipe surface for optimum measurement. Thus, every single sensor strip is designed to be functioned independently. Such system has lower sensing capability in the central of the sensing area which often contributes to poor imaging result. This problem can be overcome by combining the ECT with ultrasonic tomography to form a dual modality tomography system. By implementing the new ECT sensor, multiphase flow measurement image results can be achieved. The reconstructed image results are presented in this paper.

scholarly journals Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Jing Yan ◽  
Bin Zhang ◽  
Shuaitong Zhang ◽  
Jingliang Cheng ◽  
Xianzhi Liu ◽  
...  
Keyword(s):  
Image Fusion ◽  
Molecular Subtypes ◽  
Progression Free Survival ◽  
Quantitative Mri ◽  
Promoter Mutation ◽  
Fusion Model ◽  
Free Survival ◽  
Contrast Enhanced ◽  
Apparent Diffusion ◽  
The Status

AbstractGliomas can be classified into five molecular groups based on the status of IDH mutation, 1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by biopsy or surgery. Thus, we aimed to use MRI-based radiomics to noninvasively predict the molecular groups and assess their prognostic value. We retrospectively identified 357 patients with gliomas and extracted radiomic features from their preoperative MRI images. Single-layered radiomic signatures were generated using a single MR sequence using Bayesian-regularization neural networks. Image fusion models were built by combing the significant radiomic signatures. By separately predicting the molecular markers, the predictive molecular groups were obtained. Prognostic nomograms were developed based on the predictive molecular groups and clinicopathologic data to predict progression-free survival (PFS) and overall survival (OS). The results showed that the image fusion model incorporating radiomic signatures from contrast-enhanced T1-weighted imaging (cT1WI) and apparent diffusion coefficient (ADC) achieved an AUC of 0.884 and 0.669 for predicting IDH and TERT status, respectively. cT1WI-based radiomic signature alone yielded favorable performance in predicting 1p/19q status (AUC = 0.815). The predictive molecular groups were comparable to actual ones in predicting PFS (C-index: 0.709 vs. 0.722, P = 0.241) and OS (C-index: 0.703 vs. 0.751, P = 0.359). Subgroup analyses by grades showed similar findings. The prognostic nomograms based on grades and the predictive molecular groups yielded a C-index of 0.736 and 0.735 in predicting PFS and OS, respectively. Accordingly, MRI-based radiomics may be useful for noninvasively detecting molecular groups and predicting survival in gliomas regardless of grades.

Image Fusion of ECT/ERT for Oil-Gas-Water Three-Phase Flow

2011 ◽  
Vol 3 (2) ◽  
pp. 29-34 ◽  
Author(s):  
Lifeng Zhang
Keyword(s):  
Image Fusion ◽  
Electrical Capacitance Tomography ◽  
Phase Flow ◽  
Electrical Capacitance ◽  
Cross Sectional ◽  
Three Phase ◽  
Three Phase Flow ◽  
Capacitance Tomography ◽  
Oil Gas ◽  
Image Fusion Method

The tomographic imaging of process parameters for oil-gas-water three-phase flow can be obtained through different sensing modalities, such as electrical resistance tomography (ERT) and electrical capacitance tomography (ECT), both of which are sensitive to specific properties of the objects to be imaged. However, it is hard to discriminate oil, gas and water phases merely from reconstructed images of ERT or ECT. In this paper, the feasibility of image fusion based on ERT and ECT reconstructed images was investigated for oil-gas-water three-phase flow. Two cases were discussed and pixel-based image fusion method was presented. Simulation results showed that the cross-sectional reconstruction images of oil-gas-water three-phase flow can be obtained using the presented methods.

scholarly journals Dynamic Simulation and Control of a New Parallel Hybrid Power System

2020 ◽  
Vol 10 (16) ◽  
pp. 5467
Author(s):  
Po-Tuan Chen ◽  
Cheng-Jung Yang ◽  
Kuohsiu David Huang
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Internal Combustion Engine ◽  
Dynamic Simulation ◽  
Electric Motor ◽  
Fuzzy Logic Controller ◽  
Simulation Analysis ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Power Sources

To avoid unnecessary power loss during switching between the various power sources of a composite electric vehicle while achieving smooth operation, this study focuses on the development and dynamic simulation analysis of a control system for the power of a parallel composite vehicle. This system includes a power integration and distribution mechanism, which enables the two power sources of the internal combustion engine and electric motor to operate independently or in coordination to meet the different power-output requirements. The integration of the electric motor and battery-charging engine reduces the system complexity. To verify the working efficiency of the energy control strategy for the power system, the NEDC2000 cycle is used for the vehicle driving test, a fuzzy logic controller is established using Matlab/Simulink, and the speed and torque analysis of the components related to power system performance are conducted. Through a dynamic simulation, it is revealed that this fuzzy logic controller can adjust the two power sources (the motor and internal combustion engine) appropriately. The internal combustion engine can be maintained in the optimal operating region with low, medium, and high driving speeds.

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