Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors
Colored imaging of magnetic nanoparticles (MNP) is a promising noninvasive method for medical applications such as therapy and diagnosis. This study investigates the capability of the magnetoelectric sensor and projected gradient descent (PGD) algorithm for colored particle detection. In the first s...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Nanomaterials |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-4991/13/2/347 |
| _version_ | 1797438116390240256 |
|---|---|
| author | Ron-Marco Friedrich Mohammad Sadeghi Franz Faupel |
| author_facet | Ron-Marco Friedrich Mohammad Sadeghi Franz Faupel |
| author_sort | Ron-Marco Friedrich |
| collection | DOAJ |
| description | Colored imaging of magnetic nanoparticles (MNP) is a promising noninvasive method for medical applications such as therapy and diagnosis. This study investigates the capability of the magnetoelectric sensor and projected gradient descent (PGD) algorithm for colored particle detection. In the first step, the required circumstances for image reconstruction are studied via a simulation approach for different signal-to-noise ratios (SNR). The spatial accuracy of the reconstructed image is evaluated based on the correlation coefficient (CC) factor. The inverse problem is solved using the PGD method, which is adapted according to a nonnegativity constraint in the complex domain. The MNP characterizations are assessed through a magnetic particle spectrometer (MPS) for different types. In the experimental investigation, the real and imaginary parts of the MNP’s response are used to detect the spatial distribution and particle type, respectively. The experimental results indicate that the average phase difference for CT100 and ARA100 particles is 14 degrees, which is consistent with the MPS results and could satisfy the system requirements for colored imaging. The experimental evaluation showed that the magnetoelectric sensor and the proposed approach could be potential candidates for color bio-imaging applications. |
| first_indexed | 2024-03-09T11:32:35Z |
| format | Article |
| id | doaj.art-6cacf8964d434121a77f277cfcd0dd17 |
| institution | Directory Open Access Journal |
| issn | 2079-4991 |
| language | English |
| last_indexed | 2024-03-09T11:32:35Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Nanomaterials |
| spelling | doaj.art-6cacf8964d434121a77f277cfcd0dd172023-11-30T23:48:38ZengMDPI AGNanomaterials2079-49912023-01-0113234710.3390/nano13020347Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric SensorsRon-Marco Friedrich0Mohammad Sadeghi1Franz Faupel2Chair for Multicomponent Materials, Institute of Materials Science, Kiel University, Kaiserstr. 2, D-24143 Kiel, GermanyChair for Multicomponent Materials, Institute of Materials Science, Kiel University, Kaiserstr. 2, D-24143 Kiel, GermanyChair for Multicomponent Materials, Institute of Materials Science, Kiel University, Kaiserstr. 2, D-24143 Kiel, GermanyColored imaging of magnetic nanoparticles (MNP) is a promising noninvasive method for medical applications such as therapy and diagnosis. This study investigates the capability of the magnetoelectric sensor and projected gradient descent (PGD) algorithm for colored particle detection. In the first step, the required circumstances for image reconstruction are studied via a simulation approach for different signal-to-noise ratios (SNR). The spatial accuracy of the reconstructed image is evaluated based on the correlation coefficient (CC) factor. The inverse problem is solved using the PGD method, which is adapted according to a nonnegativity constraint in the complex domain. The MNP characterizations are assessed through a magnetic particle spectrometer (MPS) for different types. In the experimental investigation, the real and imaginary parts of the MNP’s response are used to detect the spatial distribution and particle type, respectively. The experimental results indicate that the average phase difference for CT100 and ARA100 particles is 14 degrees, which is consistent with the MPS results and could satisfy the system requirements for colored imaging. The experimental evaluation showed that the magnetoelectric sensor and the proposed approach could be potential candidates for color bio-imaging applications.https://www.mdpi.com/2079-4991/13/2/347magnetic particle mappingnanoparticlemagnetoelectricinverse optimizationprojected gradient descent |
| spellingShingle | Ron-Marco Friedrich Mohammad Sadeghi Franz Faupel Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors Nanomaterials magnetic particle mapping nanoparticle magnetoelectric inverse optimization projected gradient descent |
| title | Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors |
| title_full | Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors |
| title_fullStr | Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors |
| title_full_unstemmed | Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors |
| title_short | Numerical and Experimental Study of Colored Magnetic Particle Mapping via Magnetoelectric Sensors |
| title_sort | numerical and experimental study of colored magnetic particle mapping via magnetoelectric sensors |
| topic | magnetic particle mapping nanoparticle magnetoelectric inverse optimization projected gradient descent |
| url | https://www.mdpi.com/2079-4991/13/2/347 |
| work_keys_str_mv | AT ronmarcofriedrich numericalandexperimentalstudyofcoloredmagneticparticlemappingviamagnetoelectricsensors AT mohammadsadeghi numericalandexperimentalstudyofcoloredmagneticparticlemappingviamagnetoelectricsensors AT franzfaupel numericalandexperimentalstudyofcoloredmagneticparticlemappingviamagnetoelectricsensors |