IEEE AP-S/URSI 2023 || Portland, Oregon, USA || 23-28 July 2023

Institute of Electrical and Electronics Engineers (IEEE)

International Union of Radio Science

IEEE APS

U.S. NATIONAL COMMITTEE FOR URSI

National Academies Sciences Engineering Medicine

IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

July 23–28, 2023 • Portland, Oregon, USA

23-28 July 2023 • Portland, Oregon, USA

IEEE AP-S/URSI 2023

23-28 July 2023 • Portland, Oregon, USA

WE-UK.1A.4

Removing Antenna Effects using an Invertible Neural Network for Improved Estimation of Multilayered Tissue Profiles using UWB Radar

Yuyi Chang, Nithin Sugavanam, Emre Ertin, The Ohio State University, United States

Session:

Human Body Interactions with Electromagnetic Fields

Track:

K: Human-body interactions with antennas and other electromagnetic devices

Location:

C 123 (OCC)

Session Time:

Wed, 26 Jul, 08:00 - 09:40 PDT (UTC -8)

Presentation Time:

Wed, 26 Jul, 09:00 - 09:20 PDT (UTC -8)

Session Co-Chairs:

Erdem Topsakal, Virginia Commonwealth University and Giuseppe Carluccio, New York University

Session WE-UK.1A

WE-UK.1A.1: The Role of Skin in mm-Wave Exposure of Human Body

Gerardo Di Martino, Alessio Di Simone, Antonio Iodice, Daniele Riccio, Giuseppe Ruello, University of Napoli Federico II, Italy

WE-UK.1A.2: High Gain, Incognito, On-Body Passive RFID Design

Michael Suche, Erdem Topsakal, Virginia Commonwealth University, United States

WE-UK.1A.3: Deep Learning-Based Estimation of Specific Absorption Rate Induced by High-Field MRI RF Head Coils

Xi Wang, Xiaofan Jia, Nanyang Technological University, Singapore; Shaoying Huang, Singapore University of Technology and Design, Singapore; Abdulkadir C. Yucel, Nanyang Technological University, Singapore

WE-UK.1A.4: Removing Antenna Effects using an Invertible Neural Network for Improved Estimation of Multilayered Tissue Profiles using UWB Radar

Yuyi Chang, Nithin Sugavanam, Emre Ertin, The Ohio State University, United States

WE-UK.1A.5: Optimization of the Permittivity of the Transfer Medium in MRgFUS to Maximize SNR and Transmit Efficiency for MRI

Giuseppe Carluccio, Karthik Lakshmanan, Ryan Brown, Christopher Collins, New York University, United States