{"title":"2024 Index IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Vol. 8","authors":"","doi":"10.1109/JERM.2024.3512633","DOIUrl":"https://doi.org/10.1109/JERM.2024.3512633","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 4","pages":"401-414"},"PeriodicalIF":3.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10781463","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal","authors":"","doi":"10.1109/JERM.2024.3496595","DOIUrl":"https://doi.org/10.1109/JERM.2024.3496595","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 4","pages":"C3-C3"},"PeriodicalIF":3.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10765925","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information","authors":"","doi":"10.1109/JERM.2024.3496599","DOIUrl":"https://doi.org/10.1109/JERM.2024.3496599","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 4","pages":"C2-C2"},"PeriodicalIF":3.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10765930","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal","authors":"","doi":"10.1109/JERM.2024.3442073","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442073","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C3-C3"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information","authors":"","doi":"10.1109/JERM.2024.3442071","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442071","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C2-C2"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Models of Melanoma Growth for Assessment of Microwave-Based Diagnostic Tools","authors":"Jasmine Boparai;Rachel Tchinov;Oliver Miller;Yanis Jallouli;Milica Popović","doi":"10.1109/JERM.2024.3430315","DOIUrl":"https://doi.org/10.1109/JERM.2024.3430315","url":null,"abstract":"Malignant melanoma, the aggressive form of skin cancer, progresses via radial and vertical growth. The aim of this study is to assess the feasibility of microwave-based diagnosis of melanoma at different stages of tumor progression. To this end, we used the physiological data for melanoma progression to develop a theoretical model of melanoma growth, followed by the oil-in-gelatin based tissue phantoms, which aim to mimic the dielectric behavior of the tissues under consideration. The phantoms are then dielectrically characterized using a slim-form open-ended coaxial probe by systematically sampling dielectric values across the mimicked skin surfaces at a range of points over the 0.5 – 26.5 GHz frequency range. The resulting observations revealed that the microwave spectroscopy exhibits the capability not only to distinguish between healthy and malignant skin, but also differentiate between tumors at different stages of vertical growth, which may not be visually discernible from the skin surface. The measured results are compared with the estimated dielectric values of malignant melanoma using Lichteneker's mixing equation obtained from the literature and it was observed that the measured results closely agree with the literature values.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"305-315"},"PeriodicalIF":3.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giuseppe Carluccio;Sukhoon Oh;Sangwoo Kim;Donghyuk Kim;Karthik Lakshmanan;Christopher M. Collins
{"title":"A Fast Method to Estimate the SAR Distribution From Temperature Increased Maps","authors":"Giuseppe Carluccio;Sukhoon Oh;Sangwoo Kim;Donghyuk Kim;Karthik Lakshmanan;Christopher M. Collins","doi":"10.1109/JERM.2024.3418716","DOIUrl":"https://doi.org/10.1109/JERM.2024.3418716","url":null,"abstract":"<bold>Objectives:</b>\u0000 Estimation of Specific energy Absorption Rate (SAR) is critical to assess RF safety for devices that rely on the transmission of electromagnetic energy, such as cellphones or MRI coils. SAR generates local heat which can damage human tissues and it is usually estimated through numerical simulations. We describe a method to estimate the SAR distribution in phantoms that is fast and not computationally demanding, based on the evaluation of temperature increase maps. \u0000<bold>Technology or Method:</b>\u0000 The presented method relies on the inversion of a previously published method to quickly estimate the temperature increase with the knowledge of the SAR distribution and thermal properties. By reversing the process, we can estimate the SAR from temperature increase maps and material thermal properties. To demonstrate the method, we utilize temperature maps measured with MRI-based thermography and compare the estimated SAR maps with those obtained through electromagnetic simulations. We have performed these comparisons with two datasets, one 2D and one 3D, and we have considered the impact of potential sources of errors such as the acquisition time and discontinuities at the interface air/sample. \u0000<bold>Results:</b>\u0000 The method can estimate SAR distribution from experimental temperature increase maps within few seconds, and produces SAR distributions similar to those from simulation of the experimental situation. \u0000<bold>Clinical or Biological Impact</b>\u0000: The method we present can quickly estimate SAR distribution to assess RF safety of radiofrequency devices.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"298-304"},"PeriodicalIF":3.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valeria Mariano;Jorge A. Tobon Vasquez;David O. Rodriguez-Duarte;Francesca Vipiana
{"title":"Field-Based Discretization of the 3-D Contrast Source Inversion Method Applied to Brain Stroke Microwave Imaging","authors":"Valeria Mariano;Jorge A. Tobon Vasquez;David O. Rodriguez-Duarte;Francesca Vipiana","doi":"10.1109/JERM.2024.3414196","DOIUrl":"https://doi.org/10.1109/JERM.2024.3414196","url":null,"abstract":"The contrast source inversion method is an iterative non-linear algorithm, and, in this paper, it works in combination with a finite element method solver for the reconstruction of the dielectric properties' distribution in the head with the aim to diagnose brain stroke. Here, the involved contrast source variables are discretized through a novel field-based discretization that allows a linear variation of the variables, leading to their more accurate description, and therefore to a final dielectric properties' reconstruction closer to the expected scenario. Moreover, we propose a new approach to compute the imaging algorithm initial guess, based on the truncated singular value decomposition technique, that appears more effective in the case of noisy measured data. Finally, the developed algorithm is applied to sets of data, measured with a microwave imaging system to reconstruct brain stroke scenarios.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"290-297"},"PeriodicalIF":3.0,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142084501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Electromagnetic Modeling of the Implantable Electrode for Transfer Function Calibration in MRI RF-Induced Heating Assessment","authors":"Tiangang Long;Changqing Jiang;Luming Li","doi":"10.1109/JERM.2024.3414830","DOIUrl":"https://doi.org/10.1109/JERM.2024.3414830","url":null,"abstract":"Radiofrequency-induced heating represents a significant and intricate challenge during the combined use of magnetic resonance imaging and active implantable medical devices. The coupling of the transfer function (TF) determination process and radiofrequency (RF) exposure experiment is a perennial problem in the field. In this study, the tip electrode was separated from the lead and numerically modeled for analysis. The current induced at the electrode in the TF measurement scenario was estimated by analyzing the electromagnetic (EM) fields near the electrode. The magnitude of TF was calibrated according to the estimated current source. The tip response under RF exposure is independently predicted with an error of less than 10% using the obtained scaled TF in simulation studies. Near-electrode EM fields analysis introduces a novel perspective in RF-induced heating evaluation study.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"259-264"},"PeriodicalIF":3.0,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Numerical Modeling for Shoulder Injury Detection Using Microwave Imaging","authors":"Sahar Borzooei;Pierre-Henri Tournier;Victorita Dolean;Christian Pichot;Nadine Joachimowicz;Helene Roussel;Claire Migliaccio","doi":"10.1109/JERM.2024.3411799","DOIUrl":"https://doi.org/10.1109/JERM.2024.3411799","url":null,"abstract":"Rotator cuff tear (RCT) is one of the most common shoulder injuries, which can be irreparable if it develops to a severe condition. A portable imaging system for the on-site detection of RCT is necessary to identify its extent for early diagnosis. We introduce a microwave tomography system, using state-of-the-art numerical modeling and parallel computing for detection of RCT. The results show that the proposed method is capable of accurately detecting and localizing this injury in different size. In the next step, an efficient design in terms of computing time and complexity is proposed to detect the variations in the injured model with respect to the healthy model. The method is based on finite element discretization and uses parallel preconditioners from the domain decomposition method to accelerate computations. It is implemented using the open source FreeFEM software.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"282-289"},"PeriodicalIF":3.0,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10564578","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}