The Core of Medical Imaging: State of the Art and Perspectives on the Detectors

A New Combination of Radio-Frequency Coil Configurations Using High-Permittivity Materials and Inductively Coupled Structures for Ultrahigh-Field Magnetic Resonance Imaging

In ultrahigh-field (UHF) magnetic resonance imaging (MRI) system, the RF power required to excite the nuclei of the target object increases. As the strength of the main magnetic field (B0 field) increases, the improvement of the RF transmit field (B1+ field) efficiency and receive field (B1- field) sensitivity of radio-frequency (RF) coils is essential to reduce their specific absorption rate and power deposition in UHF MRI. To address these problems, we previously proposed a method to simultaneously improve the B1+ field efficiency and B1- field sensitivity of 16-leg bandpass birdcage RF coils (BP-BC RF coils) by combining a multichannel wireless RF element (MCWE) and segmented cylindrical high-permittivity material (scHPM) comprising 16 elements in 7.0 T MRI. In this work, we further improved the performance of transmit/receive RF coils. A new combination of RF coil with wireless element and HPM was proposed by comparing the BP-BC RF coil with the MCWE and the scHPM proposed in the previous study and the multichannel RF coils with a birdcage RF coil-type wireless element (BCWE) and the scHPM proposed in this study. The proposed 16-ch RF coils with the BCWE and scHPM provided excellent B1+ field efficiency and B1- field sensitivity improvement.

Photon-Counting Detectors in Computed Tomography: A Review

Photon-counting computed tomography (CT) is a new technique that has the potential to revolutionize clinical CT and is predicted to be the next significant advancement. In recent years, tremendous research has been conducted to demonstrate the developments in hardware assembly and its working principles. The articles in this review were obtained by conducting a search of the MEDLINE database. Photon-counting detectors (PCDs) provide excellent quality diagnostic images with high spatial resolution, reduced noise, artifacts, increased contrast-to-noise ratio, and multienergy data acquisition as compared with conventionally used energy-integrating detector (EID). The search covered articles published between 2011 and 2021. The title and abstract of each article were reviewed as determined by the search strategy. From these, eligible studies and articles that provided the working and clinical application of PCDs were selected. This article aims to provide a systematic review of the basic working principles of PCDs, emphasize the uses and clinical applications of PCDs, and compare it to EIDs. It provides a nonmathematical explanation and understanding of photon-counting CT systems for radiologists as well as clinicians.

A Comparative Study of Birdcage RF Coil Configurations for Ultra-High Field Magnetic Resonance Imaging

Improvements in transmission and reception sensitivities of radiofrequency (RF) coils used in ultra-high field (UHF) magnetic resonance imaging (MRI) are needed to reduce specific absorption rates (SAR) and RF power deposition, albeit without applying high-power RF. Here, we propose a method to simultaneously improve transmission efficiency and reception sensitivity of a band-pass birdcage RF coil (BP-BC RF coil) by combining a multi-channel wireless RF element (MCWE) with a high permittivity material (HPM) in a 7.0 T MRI. Electromagnetic field (EM-field) simulations, performed using two types of phantoms, viz., a cylindrical phantom filled with oil and a human head model, were used to compare the effects of MCWE and HPM on BP-BC RF coils. EM-fields were calculated using the finite difference time-domain (FDTD) method and analyzed using Matlab software. Next, to improve RF transmission efficiency, we compared two HPM structures, namely, a hollow cylinder shape HPM (hcHPM) and segmented cylinder shape HPM (scHPM). The scHPM and MCWE model comprised 16 elements (16-rad BP-BC RF coil) and this coil configuration demonstrated superior RF transmission efficiency and reception sensitivity along with an acceptable SAR. We expect wider clinical application of this combination in 7.0 T MRIs, which were recently approved by the United States Food and Drug Administration.

Tutorial on the Use of Deep Learning in Diffuse Optical Tomography

Diffuse optical tomography using deep learning is an emerging technology that has found impressive medical diagnostic applications. However, creating an optical imaging system that uses visible and near-infrared (NIR) light is not straightforward due to photon absorption and multi-scattering by tissues. The high distortion levels caused due to these effects make the image reconstruction incredibly challenging. To overcome these challenges, various techniques have been proposed in the past, with varying success. One of the most successful techniques is the application of deep learning algorithms in diffuse optical tomography. This article discusses the current state-of-the-art diffuse optical tomography systems and comprehensively reviews the deep learning algorithms used in image reconstruction. This article attempts to provide researchers with the necessary background and tools to implement deep learning methods to solve diffuse optical tomography.