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Biomedical subjects

B H Blott

Publications and source records attributed to B H Blott.

7 recordsLinked to original sources
PubMed1992

Review of neural network applications in medical imaging and signal processing.

The current applications of neural networks to in vivo medical imaging and signal processing are reviewed. As is evident from the literature neural networks have already been used for a wide variety of tasks within medicine. As this trend is expected to continue this review contains a description of recent studies to provide an appreciation of the problems associated with implementing neural networks for medical imaging and signal processing.

Diagnostic Imaging↗
PubMed1992

Light scattering study of irradiated lipid bilayer.

Vesicular phospholipid bilayer membranes in the form of giant unilamellar vesicles (GUVs) of dipalmitoylphosphatidylcholine (DPPC) were irradiated with fast neutron fluences ranging from 10(4) to 10(7) n cm-2. The phase behaviour of both non-irradiated and irradiated GUVs was investigated using an angular light scattering technique. A model independent size distribution of the samples and their optical anisotropy (delta) were determined using a maximum entropy technique and the theory of light scattering from spherical shells composed of anisotropic cylindrical molecules arranged radially in the shells. The structural changes in the lipid bilayer exposed to fission neutrons are discussed on the basis of the damaging mechanisms of fast neutrons to both the hydrophobic and hydrophilic regions of the lipid bilayer.

1,2-Dipalmitoylphosphatidylcholine↗
PubMed1992

Neural networks for electrical impedance tomography image characterisation.

The Southampton electrical impedance tomography (EIT) system used a Sheffield data acquisition unit and a PC based 'Harlequin' transputer card to reconstruct and display images of the distribution of internal conductivity within the thorax. The system produces real-time images relating to both cardiac and pulmonary function. As a first step towards diagnosis using these images neural nets have been applied to the identification of regions of interest in the EIT images for which some activity with time, such as ventricular ejection, is sought. This paper addresses the use of a back-projection network to identify characteristic regions within the images. The network facilitates the production of automated real-time activity plots by defining their effective extent in the images of specific organs. The application is novel within the medical imaging field as the aim is to use neural networks for real-time image analysis.

Electric Conductivity↗
PubMed1992

Pulmonary perfusion and ventricular ejection imaging by frequency domain filtering of EIT (electrical impedance tomography) images.

While EIT images can produce clinically useful qualitative information, the extraction of quantitative data is essential in clinical monitoring. In the case of imaging of the thorax the parameters available relate to cardiac activity and pulmonary perfusion. Imaging the relatively small changes in the resistivity of the lungs due to pulmonary perfusion in the presence of noise and the larger ventilation component is difficult. Suggested solutions involve multiple time averaging of cardiac gated data or reconstructed images. The required number of data frames for this type of processing is large (at least 100 cardiac cycles). Because the ventilation and perfusion components of the resistivity signals are well separated in the frequency domain, they can be differentiated by filtering. We report the results of this analysis which requires a data collection period of typically 15 s.

Blood Flow Velocity↗
PubMed1991

The spectral expansion of a head model in electrical impedance tomography.

This paper examines whether electrical impedance tomography (EIT) can provide information of use to magneto-encephalographic modelling (MEG). The EIT image domain is expanded in a complete set of orthogonal basis images, the number of which is given by the number of independent measurements (104 for 16 electrodes). They are ordered according to their sensitivity to data noise, with more centrally located features and higher spatial frequency components appearing towards the higher terms in the series, in the case of uniform resistivity distribution. This indicates that the resolution can be improved at the expense of degrading signal-to-noise in the reconstructed image. Applied to an approximate model of the head, the technique generates a set of basis images that emphasises central features of the head.

Brain↗
PubMed1990

A transputer implemented algorithm for electrical impedance tomography.

Electrical impedance tomography (EIT) offers a non-invasive technique of great scope for producing clinically important information in a number of medical applications. Initial work by Brown used an isopotential approach to solving the complex backprojection problem. In this study a less restrictive algorithm for EIT has been developed based on the work of Yorkey and of Kaczmarz. Since considerably more processing is required this has been implemented on a transputer in Occam 2 with the aim of achieving real-time imaging. Data were collected, using a Sheffield prototype EIT system, from a test object and a human thorax. Image processing used both the 'Sheffield' and the Yorkey/Kaczmarz algorithms. Our initial results indicate that the images generated using the latter approach were more representative of the source impedance distributions.

Adult↗