Non-invasive imaging of roots with high resolution X-ray micro-tomography

ray micro-tomography is a well-established technique for non-invasive imaging and evaluation of heterogeneous materials. An inexpensive X-ray micro-tomography system has been designed and built for the specific purposes of examining root growth and root/soil interactions. The system uses a silver target X-ray source with a focal spot diameter of 80 mum, an X-ray image intensifier with a sampling aperture of about 100 mum, and a sample with a diameter of 25 mm. Pre-germinated wheat and rape seeds were grown for up to 8-10 days in plastic containers in a sandy loam soil sieved to < 250 μm, and imaged with the X-ray system at regular intervals. The quality of 3 D image obtained was good allowing the development and growth of both root axes and some first-order laterals to be observed. The satisfactory discrimination between soil and roots enabled measurements of root diameter (wheat values were 0.48-1.22 mm) in individual tomographic slices and, by tracking from slice to slice, root lengths were also measured. The measurements obtained were generally within 10% of those obtained from destructive samples measured manually and with a flat-bed scanner. Further developments of the system will allow more detailed examination of the root: soil interface.

An X-ray micro-tomography system optimised for the low-dose study of living organisms

An X-ray micro-tomography system has been designed that is dedicated to the low-dose imaging of radiation sensitive living organisms and has been used to image the early development of the first few days of plant development immediately after germination. The system is based on third-generation X-ray micro-tomography system and consists of an X-ray tube, two-dimensional X-ray detector and a mechanical sample manipulation stage. The X-ray source is a 50 kVp X-ray tube with a silver target with a filter to centre the X-ray spectrum on 22 keV.A 100 mm diameter X-ray image intensifier (XRII) is used to collect the two-dimensional projection images. The rotation tomography table incorporates a linear translation mechanism to eliminate ring artefact that is commonly associated with third-generation tomography systems' Developing maize seeds (Triticum aestivum) have been imaged using the system with a cubic voxel linear dimension of 100 mum, over a diameter of 25 mm and the root lengths and volumes measured. The X-ray dose to the plants was also assessed and found to have no effect on the plant root development. (C) 2003 Elsevier Science Ltd. All rights reserved.

Ventilation rates in schools and pupil’s performance using computerized assessment tests

Research shows that poor indoor air quality (IAQ) in school buildings can cause a reduction in the students’ performance assessed by short-term computer-based tests; whereas good air quality in classrooms can enhance children's concentration and also teachers’ productivity. Investigation of air quality in classrooms helps us to characterise pollutant levels and implement corrective measures. Outdoor pollution, ventilation equipment, furnishings, and human activities affect IAQ. In school classrooms, the occupancy density is high (1.8–2.4 m2/person) compared to offices (10 m2/person). Ventilation systems expend energy and there is a trend to save energy by reducing ventilation rates. We need to establish the minimum acceptable level of fresh air required for the health of the occupants. This paper describes a project, which will aim to investigate the effect of IAQ and ventilation rates on pupils’ performance and health using psychological tests. The aim is to recommend suitable ventilation rates for classrooms and examine the suitability of the air quality guidelines for classrooms. The air quality, ventilation rates and pupils’ performance in classrooms will be evaluated in parallel measurements. In addition, Visual Analogue Scales will be used to assess subjective perception of the classroom environment and SBS symptoms. Pupil performance will be measured with Computerised Assessment Tests (CAT), and Pen and Paper Performance Tasks while physical parameters of the classroom environment will be recorded using an advanced data logging system. A total number of 20 primary schools in the Reading area are expected to participate in the present investigation, and the pupils participating in this study will be within the age group of 9–11 years. On completion of the project, based on the overall data recommendations for suitable ventilation rates for schools will be formulated.

Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms

Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.

Assessing the accuracy of a computerized decision support system for digoxin dosing in primary care: an observational study

Background: This study was carried out as part of a European Union funded project (PharmDIS-e+), to develop and evaluate software aimed at assisting physicians with drug dosing. A drug that causes particular problems with drug dosing in primary care is digoxin because of its narrow therapeutic range and low therapeutic index. Objectives: To determine (i) accuracy of the PharmDIS-e+ software for predicting serum digoxin levels in patients who are taking this drug regularly; (ii) whether there are statistically significant differences between predicted digoxin levels and those measured by a laboratory and (iii) whether there are differences between doses prescribed by general practitioners and those suggested by the program. Methods: We needed 45 patients to have 95% Power to reject the null hypothesis that the mean serum digoxin concentration was within 10% of the mean predicted digoxin concentration. Patients were recruited from two general practices and had been taking digoxin for at least 4 months. Exclusion criteria were dementia, low adherence to digoxin and use of other medications known to interact to a clinically important extent with digoxin. Results: Forty-five patients were recruited. There was a correlation of 0·65 between measured and predicted digoxin concentrations (P < 0·001). The mean difference was 0·12 μg/L (SD 0·26; 95% CI 0·04, 0·19, P = 0·005). Forty-seven per cent of the patients were prescribed the same dose as recommended by the software, 44% were prescribed a higher dose and 9% a lower dose than recommended. Conclusion: PharmDIS-e+ software was able to predict serum digoxin levels with acceptable accuracy in most patients.

On discrimination algorithms for ill-posed problems with an application to magnetic tomography

In this paper we explore classification techniques for ill-posed problems. Two classes are linearly separable in some Hilbert space X if they can be separated by a hyperplane. We investigate stable separability, i.e. the case where we have a positive distance between two separating hyperplanes. When the data in the space Y is generated by a compact operator A applied to the system states ∈ X, we will show that in general we do not obtain stable separability in Y even if the problem in X is stably separable. In particular, we show this for the case where a nonlinear classification is generated from a non-convergent family of linear classes in X. We apply our results to the problem of quality control of fuel cells where we classify fuel cells according to their efficiency. We can potentially classify a fuel cell using either some external measured magnetic field or some internal current. However we cannot measure the current directly since we cannot access the fuel cell in operation. The first possibility is to apply discrimination techniques directly to the measured magnetic fields. The second approach first reconstructs currents and then carries out the classification on the current distributions. We show that both approaches need regularization and that the regularized classifications are not equivalent in general. Finally, we investigate a widely used linear classification algorithm Fisher's linear discriminant with respect to its ill-posedness when applied to data generated via a compact integral operator. We show that the method cannot stay stable when the number of measurement points becomes large.

Computerized short-term memory treatment for older adults with aphasia

We report on a software prototype designed to deliver a novel term memory treatment for older adults with aphasia. We conducted a review of the prototype with 14 speech and language therapists, to elicit feedback on the potential usefulness of the ultimate application and, particularly, the prototype in terms of its main design features and use by older adults with aphasia. The clinicians’ feedback highlights a number of design considerations relating to the usability, training methods, and appeal of treatment software, which can help engage patients more fully in computerized treatments and improve treatment outcomes.

Reduced-order modeling of light transport in tissue for real-time monitoring of brain hemodynamics using diffuse optical tomography

This paper proposes a new reconstruction method for diffuse optical tomography using reduced-order models of light transport in tissue. The models, which directly map optical tissue parameters to optical flux measurements at the detector locations, are derived based on data generated by numerical simulation of a reference model. The reconstruction algorithm based on the reduced-order models is a few orders of magnitude faster than the one based on a finite element approximation on a fine mesh incorporating a priori anatomical information acquired by magnetic resonance imaging. We demonstrate the accuracy and speed of the approach using a phantom experiment and through numerical simulation of brain activation in a rat's head. The applicability of the approach for real-time monitoring of brain hemodynamics is demonstrated through a hypercapnic experiment. We show that our results agree with the expected physiological changes and with results of a similar experimental study. However, by using our approach, a three-dimensional tomographic reconstruction can be performed in ∼3  s per time point instead of the 1 to 2 h it takes when using the conventional finite element modeling approach

Three dimensional analysis of cardiovascular development in mouse embryos using X-ray microcomputed tomography

Micro-computed tomography (μCT) has been successfully used to study the cardiovascular system of mouse embryos in situ. With the use of barium as a suitable contrast agent, blood vessels have been imaged and analysed quantitatively such as blood volume and vessel sizes on embryos of ages 14.5 to 16.5 days old. The advantage of using this imaging modality is that it has provided three dimensional information whilst leaving samples intact for further study.