scholarly journals Compact Wideband Microstrip Patch Antenna Design for Breast Cancer Detection

2021 ◽  
Vol 71 (03) ◽  
pp. 352-358
Author(s):  
Rakesh Singh ◽  
Naina Narang ◽  
Dharmendra Singh ◽  
Manoj Gupta
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Detection System ◽  
Breast Cancer Detection ◽  
Compact Antenna ◽  
Detection Techniques ◽  
Non Invasive ◽  
Impedance Contrast ◽  
Breast Phantom ◽  
Safety Limit

The current breast cancer detection techniques are mostly invasive and suffer from high cost, high false rate and inefficacy in early detection. These limitations can be subdued by development of non-invasive microwave detection system whose performance is predominantly dependent on the antenna used in the system. The designing of a compact wideband antenna and matching its impedance with breast phantom is a challenging task. In this paper, we have designed a compact antenna matched with the breast phantom operating in wideband frequency from 1 to 6 GHz capable to detect the dielectric (or impedance) contrast of the benign and malignant tissue. The impedance of the antenna is matched to a cubically shaped breast phantom and a very small tumor (volume=1 cm3). The antenna is tuned to the possible range of electrical properties of breast phantom and tumour (permittivity ranging from 10 to 20 and conductivity from 1.5 to 2.5 S/m). The return loss (S11), E-field distribution and specific absorption rate (SAR) are simulated. The operating band of antenna placed near the phantom without tumor was found to be (1.11-5.47)GHz and with tumor inside phantom is (1.29-5.50)GHz. Results also show that the SAR of the antenna is within the safety limit.

scholarly journals Breast Ultrasound Elastography is the Most Mature and Well-documented Method for the Measurement of Tissue Stiffness: A Review

2021 ◽  
Vol 16 (1) ◽  
pp. 42-44
Author(s):  
Hafizur Rahman
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Cancer Diagnosis ◽  
Imaging Technique ◽  
Breast Cancer Diagnosis ◽  
Breast Cancer Detection ◽  
Ultrasound Elastography ◽  
Tissue Stiffness ◽  
Detection Techniques ◽  
Non Invasive

Breast cancer is the most common malignancy and one of the leading causes of death in females worldwide. North America has one of the highest incidence breast cancer rates in the world, making breast cancer awareness a high priority. Only in the USA, 527 women are expected to be diagnosed with breast cancer while 110 women will die of it per day. Central to the importance of breast cancer diagnosis is the fact that almost one-third of the latter group could survive if their cancer is detected and treated early. In a worldwide context, this translates into nearly 400,000 lives that could be saved every year as a result of early detection. As such; developing technique that can help to detect and diagnose breast cancer at early stage can have a great impact on survival and quality of life of breast cancer patients. Conventional breast cancer screening and detection techniques such as clinical breast examination and X- ray mammography are known to have low sensitivity. Breast magnetic resonance imaging (MRI) is more sensitive modality for breast cancer detection, however, MRI is costly and has been shown to have low specificity for breast cancer diagnosis. Dynamic contrast-enhanced MRI has been demonstrated to provide a good sensitivity and specificity for differentiation of benign versus malignant lesions, due to altered angiogenesis mechanisms in tumors. However, in addition to being costly, requires injection of exogenous contrast agents to provide such contrast. An alternate imaging technique for breast cancer detection employs tissue stiffness as contrast mechanism. The technique is founded on the fact that alterations in breast tissue stiffness are frequently associated with pathology. Ultrasound elastography is the most mature and well-documented method for the measurement of tissue stiffness. Elastographybased imaging technique has received substantial attention in recent years for non-invasive assessment of tissue mechanical properties. These techniques take advantage of changed soft tissue elasticity in various pathologies to yield qualitative and quantitative information that can be used for diagnostic purpose. Measurements are acquired in specialized imaging modes that can detect tissue stiffness in response to an applied mechanical force. Ultrasoundbased methods are of particular interest due to its many inherent advantages, such as wide availability including at the bedside and relatively low cost. While ultrasound elastography has shown promising results for non-invasive assessment of breast stiffness is emerging. Faridpur Med. Coll. J. 2021;16(1):42-44

scholarly journals Complex Dielectric Coefficient of Breast Phantom Prepared for Breast Cancer Detection

2013 ◽  
Vol 123 (2) ◽  
pp. 464-466 ◽  
Author(s):  
A. Sayinti ◽  
E. Açikalin ◽  
K. Çoban ◽  
A. Vertii
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Cancer Detection ◽  
Breast Phantom ◽  
Dielectric Coefficient

scholarly journals Deep learning model for fully automated breast cancer detection system from thermograms

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262349
Author(s):  
Esraa A. Mohamed ◽  
Essam A. Rashed ◽  
Tarek Gaber ◽  
Omar Karam
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Cancer Detection ◽  
Detection System ◽  
Diagnostic Technique ◽  
Learning Model ◽  
The Body ◽  
Breast Cancer Detection ◽  
Benchmark Database ◽  
Deep Learning Model

Breast cancer is one of the most common diseases among women worldwide. It is considered one of the leading causes of death among women. Therefore, early detection is necessary to save lives. Thermography imaging is an effective diagnostic technique which is used for breast cancer detection with the help of infrared technology. In this paper, we propose a fully automatic breast cancer detection system. First, U-Net network is used to automatically extract and isolate the breast area from the rest of the body which behaves as noise during the breast cancer detection model. Second, we propose a two-class deep learning model, which is trained from scratch for the classification of normal and abnormal breast tissues from thermal images. Also, it is used to extract more characteristics from the dataset that is helpful in training the network and improve the efficiency of the classification process. The proposed system is evaluated using real data (A benchmark, database (DMR-IR)) and achieved accuracy = 99.33%, sensitivity = 100% and specificity = 98.67%. The proposed system is expected to be a helpful tool for physicians in clinical use.

scholarly journals Compact Reflectometers for a Wideband Microwave Breast Cancer Detection System

2006 ◽  
Vol 2 (3) ◽  
Author(s):  
Marek Bialkowski ◽  
Norhudah Seman ◽  
Amin Abbosh ◽  
Wee Chang Khor
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Detection System ◽  
Synthesis Method ◽  
Breast Cancer Detection ◽  
Power Divider ◽  
Frequency Synthesis ◽  
Step Frequency ◽  
Power Dividers ◽  
Time Space

The design of compact wideband microwave reflectometers for the purpose of inclusion in a breast cancer detection system is presented. In this system, a wideband frequency source is used to synthesize a narrow pulse via the step-frequency synthesis method. The reflectometer undertakes measurements in the frequency domain and the collected data is transformed into the time/space domain using IFFT. In order to accomplish reflection coefficient measurements over a large frequency band, compact wideband couplers and power dividers are used to form the reflectometer. Two compact six-port reflectometer configurations are investigated. One uses the Lange coupler and the Gysel power divider and the other one employs a 3dB slot-coupled microstrip coupler and a 2-stage Wilkinson power divider. The reflectometer employing the slot-coupled coupler and the Wilkinson divider provides a wider operational bandwidth, as shown by simulation results performed with Agilent ADS.

scholarly journals Review of Microwaves Techniques for Breast Cancer Detection

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2390 ◽  
Author(s):  
Maged A. Aldhaeebi ◽  
Khawla Alzoubi ◽  
Thamer S. Almoneef ◽  
Saeed M. Bamatraf ◽  
Hussein Attia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Cost Effective ◽  
Breast Tumour ◽  
Microwave Imaging ◽  
Breast Cancer Detection ◽  
Alternative Methods ◽  
Breast Cancer Imaging ◽  
Detection Techniques ◽  
Microwave Techniques

Conventional breast cancer detection techniques including X-ray mammography, magnetic resonance imaging, and ultrasound scanning suffer from shortcomings such as excessive cost, harmful radiation, and inconveniences to the patients. These challenges motivated researchers to investigate alternative methods including the use of microwaves. This article focuses on reviewing the background of microwave techniques for breast tumour detection. In particular, this study reviews the recent advancements in active microwave imaging, namely microwave tomography and radar-based techniques. The main objective of this paper is to provide researchers and physicians with an overview of the principles, techniques, and fundamental challenges associated with microwave imaging for breast cancer detection. Furthermore, this study aims to shed light on the fact that until today, there are very few commercially available and cost-effective microwave-based systems for breast cancer imaging or detection. This conclusion is not intended to imply the inefficacy of microwaves for breast cancer detection, but rather to encourage a healthy debate on why a commercially available system has yet to be made available despite almost 30 years of intensive research.

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