PMID- 37687861
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230911
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 23
IP  - 17
DP  - 2023 Aug 25
TI  - Quantitative Analysis of Super Resolution in Electromagnetic Inverse Scattering 
      for Microwave Medical Sensing and Imaging.
LID - 10.3390/s23177404 [doi]
LID - 7404
AB  - Microwave medical sensing and imaging (MMSI) has been a research hotspot in the 
      past years. Imaging algorithms based on electromagnetic inverse scattering (EIS) 
      play a key role in MMSI due to the super-resolution phenomenon. EIS problems 
      generally employ far-field scattered data to reconstruct images. However, the 
      far-field data do not include information outside the Ewald's sphere, so 
      theoretically it is impossible to achieve super resolution. The reason for super 
      resolution has not been clarified. The majority of the current research focuses 
      on how nonlinearity affects the super-resolution phenomena in EIS. However, the 
      mechanism of super-resolution in the absence of nonlinearity is routinely 
      ignored. In this research, we address a prevalent yet overlooked problem where 
      the image resolution due to scatterers of extended structures is incorrectly 
      analyzed using the model of point scatterers. Specifically, the classical 
      resolution of EIS is defined by the Rayleigh criterion which is only suitable for 
      point-like scatterers. However, the super-resolution in EIS is often observed for 
      general scatterers like cylinders, squares or Austria shapes. Subsequently, we 
      provide theoretical results for the Born approximation framework in EIS, and 
      employ the Sparrow criteria to quantify the resolution for symmetric objects of 
      extended structures. Furthermore, the modified Sparrow criterion is proposed to 
      calculate the resolution of asymmetric scatterers. Numerical examples show that 
      the proposed approach can better explain the super-resolution phenomenon in EIS.
FAU - Ding, Yahui
AU  - Ding Y
AUID- ORCID: 0000-0002-6988-2393
AD  - School of Electronic Science and Engineering, University of Electronic Science 
      and Technology of China, Chengdu 611731, China.
FAU - Gong, Zheng
AU  - Gong Z
AUID- ORCID: 0000-0002-0616-8141
AD  - Yangtze Delta Region Institute (Quzhou), University of Electronic Science and 
      Technology of China, Quzhou 324003, China.
FAU - Chen, Yifan
AU  - Chen Y
AD  - School of Life Sciences and Technology, University of Electronic Science and 
      Technology of China, Chengdu 611731, China.
FAU - Hu, Jun
AU  - Hu J
AD  - School of Electronic Science and Engineering, University of Electronic Science 
      and Technology of China, Chengdu 611731, China.
FAU - Chen, Yongpin
AU  - Chen Y
AD  - School of Electronic Science and Engineering, University of Electronic Science 
      and Technology of China, Chengdu 611731, China.
LA  - eng
PT  - Journal Article
DEP - 20230825
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC10490563
OTO - NOTNLM
OT  - Rayleigh criterion
OT  - Sparrow criterion
OT  - electromagnetic inverse problems
OT  - point spread function
OT  - resolution
OT  - super-resolution
COIS- The authors declare no conflict of interest.
EDAT- 2023/09/09 11:47
MHDA- 2023/09/09 11:48
PMCR- 2023/08/25
CRDT- 2023/09/09 01:22
PHST- 2023/06/15 00:00 [received]
PHST- 2023/08/21 00:00 [revised]
PHST- 2023/08/22 00:00 [accepted]
PHST- 2023/09/09 11:48 [medline]
PHST- 2023/09/09 11:47 [pubmed]
PHST- 2023/09/09 01:22 [entrez]
PHST- 2023/08/25 00:00 [pmc-release]
AID - s23177404 [pii]
AID - sensors-23-07404 [pii]
AID - 10.3390/s23177404 [doi]
PST - epublish
SO  - Sensors (Basel). 2023 Aug 25;23(17):7404. doi: 10.3390/s23177404.