Optimum receiver array design for magnetic induction tomography

A New Method of Haemorrhagic Stroke Detection Via Deep Magnetic Induction Tomography

Hemorrhage imaging is one of the most common applications of magnetic induction tomography (MIT). Depth and the mass of stroke stimulated (MSS) are the most important issues that need to be solved for this application. Transcranial magnetic stimulation (TMS) is a technique belonging to the deep brain stimulation (DBS) field, which aims at overcoming human diseases such as depression. TMS coils, namely, circular, figure-8, and H-coils, play an important role in TMS. Among these, H-coils individually focus on the issues of achieving effective stimulation of deep region. MIT and TMS mechanisms are similar. Herein, for the first time, improved TMS coils, including figure-8 and H-coils, are applied as MIT excitation coils to study the possibility of achieving the mass of stroke stimulated and deep detection through MIT. In addition, the configurations of the detection coils are varied to analyze their influence and determine the optimal coils array. Finally, MIT is used to detect haemorrhagic stroke occurring in humans, and the application of deep MIT to the haemorrhagic stroke problem is computationally explored. Results show that among the various coils, the improved H-coils have MSS and depth characteristics that enable the detection of deep strokes through MIT. Although the detecting depth of the figure-8 coil is weaker, its surface signal is good. The deep MIT technique can be applied to haemorrhagic detection, providing a critical base for deeper research.

Screening and Biosensor-Based Approaches for Lung Cancer Detection

Early diagnosis of lung cancer helps to reduce the cancer death rate significantly. Over the years, investigators worldwide have extensively investigated many screening modalities for lung cancer detection, including computerized tomography, chest X-ray, positron emission tomography, sputum cytology, magnetic resonance imaging and biopsy. However, these techniques are not suitable for patients with other pathologies. Developing a rapid and sensitive technique for early diagnosis of lung cancer is urgently needed. Biosensor-based techniques have been recently recommended as a rapid and cost-effective tool for early diagnosis of lung tumor markers. This paper reviews the recent development in screening and biosensor-based techniques for early lung cancer detection.

Advancements in transmitters and sensors for biological tissue imaging in magnetic induction tomography

Magnetic Induction Tomography (MIT), which is also known as Electromagnetic Tomography (EMT) or Mutual Inductance Tomography, is among the imaging modalities of interest to many researchers around the world. This noninvasive modality applies an electromagnetic field and is sensitive to all three passive electromagnetic properties of a material that are conductivity, permittivity and permeability. MIT is categorized under the passive imaging family with an electrodeless technique through the use of excitation coils to induce an electromagnetic field in the material, which is then measured at the receiving side by sensors. The aim of this review is to discuss the challenges of the MIT technique and summarize the recent advancements in the transmitters and sensors, with a focus on applications in biological tissue imaging. It is hoped that this review will provide some valuable information on the MIT for those who have interest in this modality. The need of this knowledge may speed up the process of adopted of MIT as a medical imaging technology.

Adaptation and focusing of optode configurations for fluorescence optical tomography by experimental design methods

Fluorescence tomography excites a fluorophore inside a sample by light sources on the surface. From boundary measurements of the fluorescent light, the distribution of the fluorophore is reconstructed. The optode placement determines the quality of the reconstructions in terms of, e.g., resolution and contrast-to-noise ratio. We address the adaptation of the measurement setup. The redundancy of the measurements is chosen as a quality criterion for the optodes and is computed from the Jacobian of the mathematical formulation of light propagation. The algorithm finds a subset with minimum redundancy in the measurements from a feasible pool of optodes. This allows biasing the design in order to favor reconstruction results inside a given region. Two different variations of the algorithm, based on geometric and arithmetic averaging, are compared. Both deliver similar optode configurations. The arithmetic averaging is slightly more stable, whereas the geometric averaging approach shows a better conditioning of the sensitivity matrix and mathematically corresponds more closely with entropy optimization. Adapted illumination and detector patterns are presented for an initial set of 96 optodes placed on a cylinder with focusing on different regions. Examples for the attenuation of fluorophore signals from regions outside the focus are given.