We introduce a general concept of tomographic imaging for the case of an imaging sensor that has a stripelike shape. We first show that there is no difference, in principle, between two-dimensional tomography using conventional electromagnetic or particle radiation and tomography where a stripe sensor is mechanically scanned over a sample at a sequence of different angles. For a single stripe detector imaging, linear motion and angular rotation are required. We experimentally demonstrate single stripe sensor imaging principle using an elongated inductive coil detector. By utilizing an array of parallel stripe sensors that can be individually addressed, two-dimensional imaging can be performed with rotation only, eliminating the requirement for linear motion, as we also experimentally demonstrate with parallel coil array. We conclude that imaging with a stripe-type sensor of particular width and thickness (where the width is much larger than the thickness) is resolution limited only by the thickness (smaller parameter) of the sensor. We give examples of multiple sensor families where this imaging technique may be beneficial such as magnetoresistive, inductive, superconducting quantum interference device, and Hall effect sensors, and, in particular, discuss the possibilities of the technique in the field of magnetic resonance imaging.
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http://dx.doi.org/10.1063/1.2894330 | DOI Listing |
ACS Nano
January 2025
Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Block copolymers (BCPs) can form nanoparticles having different morphologies that can be used as photonic nanocrystals and are a platform for drug delivery, sensors, and catalysis. In particular, BCP nanoparticles having disk-like shape have been recently discovered. Such nanodisks can be used as the next-generation antitumor drug delivery carriers; however, the applicability of the existing nanodisks is limited due to their poor or unknown ability to respond to external stimuli.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Adv Sci (Weinh)
December 2024
IFIMUP Physics for Advanced Materials, Nanotechnology and Photonics, Department of Physics and Astronomy, Faculty of Sciences, University of Porto, Rua do Campo Alegre, Porto, 4169-007, Portugal.
In recent advancements within sensing technology, driven by the Internet of Things (IoT), significant impacts are observed on health sector applications, notably through wearable electronics like electronic tattoos (e-tattoos). These e-tattoos, designed for direct contact with the skin, facilitate precise monitoring of vital physiological parameters, including body heat, a critical indicator for conditions such as inflammation and infection. Monitoring these indicators can be crucial for early detection of chronic conditions, steering toward proactive healthcare management.
View Article and Find Full Text PDFMaterials (Basel)
November 2024
Research Institute for Sustainable Humanosphere, Kyoto University, Uji 611-0011, Japan.
Sensors (Basel)
October 2024
School of Telecommunication Engineering, Xidian University, Xi'an 710126, China.
In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques.
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