Microwave cancer diagnosis

Töpfer, Fritzi; Oberhammer, Joachim

doi:10.1016/b978-0-12-802903-9.00003-5

Cited by 5 publications

(2 citation statements)

References 161 publications

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“…MWI uses electromagnetic waves at frequencies ranging from 0.5 GHz to 9.0 GHz to detect dielectric contrast that scatters from the tissue of the imaging domain [ 104 ]. Microwave (MW) technology can potentially help diagnose malignant tumors and other pathologies using the evaluation of complex permittivity of the tissue [ 105 , 106 ]. MW are safe diagnostic tools that generate images based on differences in dielectric properties.…”

Section: Discussionmentioning

confidence: 99%

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Sethi

Muddaloor

Anvekar

et al. 2023

Sensors

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Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device. Respiratory sounds result from the intra-pulmonary collision of molecules contained in the air, leading to turbulent flow and subsequent sound production. These sounds have been recorded via an electronic stethoscope and analyzed using back-propagation neural networks, wavelet transform models, Gaussian mixture models and recently with machine learning and deep learning models with possible use in asthma, COVID-19, asbestosis and interstitial lung disease. The purpose of this review was to summarize lung sound physiology, recording technologies and diagnostics methods using AI for digital pulmonology practice. Future research and development in recording and analyzing respiratory sounds in real time could revolutionize clinical practice for both the patients and the healthcare personnel.

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Section: Discussionmentioning

confidence: 99%

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Sethi

Muddaloor

Anvekar

et al. 2023

Sensors

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“…Compared with the above methods, microwave detection has many advantages, such as low-cost, nonionizing radiation, high sensitivity, widely available and more comfort application. These are expected to make microwave detection breast cancer more widely used in clinical [4,5].…”

Section: Introductionmentioning

confidence: 99%

Experiment and simulation of microwave detection using IQ demodulation method for breast tumor screening

Yao

et al. 2022

J. Inst.

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Breast cancer has become the most diagnosed cancer in the world. Microwave detection the breast tumor is attractive due to its high dielectric property contrast between different tissues of tumor. In this paper, we proposed an In-phase-Quadrature (IQ) demodulation-based method to detect the breast tumor with microwave at a frequency of 1.3 GHz. The microwave detection system consists of two signal generators, 12 transmitting/receiving antennas, two talent switches, a phantom and an IQ-Mixer. The amplitude information at the receiving antennas can be obtained by analyzing the difference frequency signals generated with two microwave signal generators. We also use the finite-difference time-domain (FDTD) method for simulation verification, which can simulate the propagation of the electromagnetic wave. Through experiments and simulations of microwave hardware system and FDTD method, it can be proved that the results are consistent. The experimental and simulation results show that when the tumor phantom diameter decreases or its depth from the receiving antenna increases, whether there is a tumor phantom can be clearly distinguished. Moreover, we also explore the effects of different tumor phantom locations on the receiving antennas. The results show that it is feasible to detect the breast tumor with the IQ demodulation method based on microwave.

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Improving UWB Image Reconstruction for Breast Cancer Diagnosis by Doing an Iterative Analysis of Radar Signals

Torres-Quispe,

Patino-Escarcina

2022

Pattern Recognition and Artificial Intelligence

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Microwave cancer diagnosis

Cited by 5 publications

References 161 publications

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Experiment and simulation of microwave detection using IQ demodulation method for breast tumor screening

Improving UWB Image Reconstruction for Breast Cancer Diagnosis by Doing an Iterative Analysis of Radar Signals

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