scholarly journals Review article of microwave imaging techniques and dielectric properties for lung tumor detection

2020 ◽  
Author(s):  
Siti Nuranis Muhammad ◽  
Muammar Mohamad Isa ◽  
Faizal Jamlos
Keyword(s):  
Dielectric Properties ◽  
Lung Tumor ◽  
Imaging Techniques ◽  
Tumor Detection ◽  
Review Article ◽  
Microwave Imaging

scholarly journals A Review Article on Brain Tumor Detection and Optimization using Hybrid Classification Algorithm

2021 ◽  
Vol 9 (11) ◽  
pp. 763-768
Author(s):  
Nitesh Yadav
Keyword(s):  
Brain Tumor ◽  
Imaging Techniques ◽  
Critical Evaluation ◽  
Tumor Detection ◽  
Review Article ◽  
Processing Method ◽  
Computational Results ◽  
X Ray ◽  
Hybrid Classification ◽  
The Brain

Abstract: This review focuses on different imaging techniques such as MRI. This survey identifies a different approach with better accuracy for tumor detection. This further includes the image processing method. In most applications, machine learning shows better performance than manual segmentation of the brain tumors from MRI images as it is a difficult and timeconsuming task. For fast and better computational results, radiology used a different approach with MRI, CT-scan, X-ray, and PET. Furthermore, summarizing the literature, this paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. Keywords: Brain tumor, data mining techniques, filtering techniques, MRI, classifiers, feature selection.

Trends in Nanotechnology for in vivo Cancer Diagnosis: Products and Patents

2020 ◽  
Vol 26 (18) ◽  
pp. 2167-2181
Author(s):  
Tatielle do Nascimento ◽  
Melanie Tavares ◽  
Mariana S.S.B. Monteiro ◽  
Ralph Santos-Oliveira ◽  
Adriane R. Todeschini ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Quantum Dots ◽  
Magnetic Resonance ◽  
Metal Nanoparticles ◽  
Cancer Diagnosis ◽  
Imaging Techniques ◽  
Tumor Detection ◽  
Abnormal Growth ◽  
Pharmaceutical Nanotechnology

Background: Cancer is a set of diseases formed by abnormal growth of cells leading to the formation of the tumor. The diagnosis can be made through symptoms’ evaluation or imaging tests, however, the techniques are limited and the tumor detection may be late. Thus, pharmaceutical nanotechnology has emerged to optimize the cancer diagnosis through nanostructured contrast agent’s development. Objective: This review aims to identify commercialized nanomedicines and patents for cancer diagnosis. Methods: The databases used for scientific articles research were Pubmed, Science Direct, Scielo and Lilacs. Research on companies’ websites and articles for the recognition of commercial nanomedicines was performed. The Derwent tool was applied for patent research. Results: This article aimed to research on nanosystems based on nanoparticles, dendrimers, liposomes, composites and quantum dots, associated to imaging techniques. Commercialized products based on metal and composite nanoparticles, associated with magnetic resonance and computed tomography, have been observed. The research conducted through Derwent tool displayed a small number of patents using nanotechnology for cancer diagnosis. Among these patents, the most significant number was related to the use of systems based on metal nanoparticles, composites and quantum dots. Conclusion: Although few systems are found in the market and patented, nanotechnology appears as a promising field for the development of new nanosystems in order to optimize and accelerate the cancer diagnosis.

A Review of Various Machine Learning Techniques for Brain Tumor Detection from MRI Images

2020 ◽  
Vol 16 (8) ◽  
pp. 937-945
Author(s):  
Aaishwarya Sanjay Bajaj ◽  
Usha Chouhan
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Ct Scan ◽  
Imaging Techniques ◽  
Critical Evaluation ◽  
Tumor Detection ◽  
Machine Learning Techniques ◽  
X Rays ◽  
Detection Techniques ◽  
The Brain

Background: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based on i) review of the machine learning approach for the identification of brain tumor and ii) review of a suitable approach for brain tumor detection. Discussion: This review focuses on different imaging techniques such as X-rays, PET, CT- Scan, and MRI. This survey identifies a different approach with better accuracy for tumor detection. This further includes the image processing method. In most applications, machine learning shows better performance than manual segmentation of the brain tumors from MRI images as it is a difficult and time-consuming task. For fast and better computational results, radiology used a different approach with MRI, CT-scan, X-ray, and PET. Furthermore, summarizing the literature, this paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. Conclusion: The problem faced by the researchers during brain tumor detection techniques and machine learning applications for clinical settings have also been discussed.

Development of MRI‐based Axillary Numerical Models and Estimation of Axillary Lymph Nodes Dielectric Properties for Microwave Imaging

2021 ◽  
Author(s):  
Daniela M. Godinho ◽  
João M. Felício ◽  
Tiago Castela ◽  
Nuno A. Silva ◽  
M. Lurdes Orvalho ◽  
...  
Keyword(s):  
Dielectric Properties ◽  
Lymph Nodes ◽  
Numerical Models ◽  
Microwave Imaging ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph

scholarly journals Fast, Robust, and Low-Cost Microwave Imaging of Multiple Non-Metallic Pipes

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1762
Author(s):  
Yuki Gao ◽  
Maryam Ravan ◽  
Reza K. Amineh
Keyword(s):  
Antenna Arrays ◽  
Oil And Gas ◽  
Imaging System ◽  
Imaging Techniques ◽  
Low Cost ◽  
Microwave Imaging ◽  
Airport Security ◽  
Destructive Testing ◽  
Security Screening ◽  
Industrial Sectors

The use of non-metallic pipes and composite components that are low-cost, durable, light-weight, and resilient to corrosion is growing rapidly in various industrial sectors such as oil and gas industries in the form of non-metallic composite pipes. While these components are still prone to damages, traditional non-destructive testing (NDT) techniques such as eddy current technique and magnetic flux leakage technique cannot be utilized for inspection of these components. Microwave imaging can fill this gap as a favorable technique to perform inspection of non-metallic pipes. Holographic microwave imaging techniques are fast and robust and have been successfully employed in applications such as airport security screening and underground imaging. Here, we extend the use of holographic microwave imaging to inspection of multiple concentric pipes. To increase the speed of data acquisition, we utilize antenna arrays along the azimuthal direction in a cylindrical setup. A parametric study and demonstration of the performance of the proposed imaging system will be provided.

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