An introduction to medical imaging with coherent terahertz frequency radiation

Methods have recently been developed that make use of electromagnetic radiation at terahertz (THz) frequencies, the region of the spectrum between millimetre wavelengths and the infrared, for imaging purposes. Radiation at these wavelengths is non-ionizing and subject to far less Rayleigh scatter than visible or infrared wavelengths, making it suitable for medical applications. This paper introduces THz pulsed imaging and discusses its potential for in vivo medical applications in comparison with existing modalities.

Do in vivo terahertz imaging systems comply with safety guidelines?

Techniques for the coherent generation and detection of electromagnetic radiation in the far infrared, or terahertz, region of the electromagnetic spectrum have recently developed rapidly and may soon be applied for in vivo medical imaging. Both continuous wave and pulsed imaging systems are under development, with terahertz pulsed imaging being the more common method. Typically a pump and probe technique is used, with picosecond pulses of terahertz radiation generated from femtosecond infrared laser pulses, using an antenna or nonlinear crystal. After interaction with the subject either by transmission or reflection, coherent detection is achieved when the terahertz beam is combined with the probe laser beam. Raster scanning of the subject leads to an image data set comprising a time series representing the pulse at each pixel. A set of parametric images may be calculated, mapping the values of various parameters calculated from the shape of the pulses. A safety analysis has been performed, based on current guidelines for skin exposure to radiation of wavelengths 2.6 µm–20 mm (15 GHz–115 THz), to determine the maximum permissible exposure (MPE) for such a terahertz imaging system. The international guidelines for this range of wavelengths are drawn from two U.S. standards documents. The method for this analysis was taken from the American National Standard for the Safe Use of Lasers (ANSI Z136.1), and to ensure a conservative analysis, parameters were drawn from both this standard and from the IEEE Standard for Safety Levels with Respect to Human Exposure to Radio Frequency Electromagnetic Fields (C95.1). The calculated maximum permissible average beam power was 3 mW, indicating that typical terahertz imaging systems are safe according to the current guidelines. Further developments may however result in systems that will exceed the calculated limit. Furthermore, the published MPEs for pulsed exposures are based on measurements at shorter wavelengths and with pulses of longer duration than those used in terahertz pulsed imaging systems, so the results should be treated with caution.

Prediction of Parkinson's disease tremor onset using artificial neural networks

In this paper we present the initial results using an artificial neural network to predict the onset of Parkinson's Disease tremors in a human subject. Data for the network was obtained from implanted deep brain electrodes. A tuned artificial neural network was shown to be able to identify the pattern of the onset tremor from these real time recordings.

Outthinking and enhancing biological brains

In this paper an attempt has been made to take a look at. how the use of implant and electrode technology can now be employed to create biological brains for robots, to enable human enhancement and to diminish the effects of certain neural illnesses. In all cases the end result is to increase the range of abilities of the recipients. An indication is given of a number of areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking the human brain directly with a computer. An overview of some of the latest developments in the field of Brain to Computer Interfacing is also given in order to assess advantages and disadvantages. The emphasis is clearly placed on practical studies that have been and are being undertaken and reported on, as opposed to those speculated, simulated or proposed as future projects. Related areas are discussed briefly only in the context of their contribution to the studies being undertaken. The area of focus is notably the use of invasive implant technology, where a connection is made directly with the cerebral cortex and/or nervous system. Tests and experimentation which do not involve human subjects are invariably carried out a priori to indicate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies from this area are discussed including our own involving neural growth. The paper goes on to describe human experimentation, in which neural implants have linked the human nervous system bi-directionally with technology and the internet. A view is taken as to the prospects for the future for this implantable computing in terms of both therapy and enhancement.

Differences in the activity of the muscles in the forearm of individuals with a congenital absence of the hand

The spectral content of the myoelectric signals from the muscles of the remnant forearms of three persons with congenital absences (CA) of their forearms was compared with signals from their intact contra-lateral limbs, similar muscles in three persons with acquired losses (AL) and seven persons without absences [no loss (NL)]. The observed bandwidth for the CA subjects was broader with peak energy between 200 and 300 Hz. While the signals from the contra-lateral limbs and the AL and NL subjects was in the 100-150 Hz range: The mean skew of the signals from the AL subjects was 46.3 +/- 6.7 and those with NL of 45.4 +/- 8.7, while the signals from those with CAs had a skew of 11.0 +/- 11. The structure of the muscles of one CA subject was observed ultrasonically. The muscle showed greater disruption than normally developed muscles. It is speculated that the myographic signal reflects the structure of the muscle. which has developed in a more disorganized manner as a result of the muscle not being stretched by other muscles across the missing distal joint, even in the muscles that are used regularly to control arm prostheses.

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological selforganization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modelling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.

An eye for an eye: robust motion segmentation by applying the latest in human vision research

Automatically extracting interesting objects from videos is a very challenging task and is applicable to many research areas such robotics, medical imaging, content based indexing and visual surveillance. Automated visual surveillance is a major research area in computational vision and a commonly applied technique in an attempt to extract objects of interest is that of motion segmentation. Motion segmentation relies on the temporal changes that occur in video sequences to detect objects, but as a technique it presents many challenges that researchers have yet to surmount. Changes in real-time video sequences not only include interesting objects, environmental conditions such as wind, cloud cover, rain and snow may be present, in addition to rapid lighting changes, poor footage quality, moving shadows and reflections. The list provides only a sample of the challenges present. This thesis explores the use of motion segmentation as part of a computational vision system and provides solutions for a practical, generic approach with robust performance, using current neuro-biological, physiological and psychological research in primate vision as inspiration.