Biomedical subjects

W Philips

Publications and source records attributed to W Philips.

6 recordsLinked to original sources

PubMed2000

An imaging system with calibrated color image acquisition for use in dermatology.

We propose a novel imaging system useful in dermatology, more precisely, for the follow-up of patients with an increased risk of skin cancer. The system consists of a Pentium PC equipped with an RGB frame grabber, a three-chip charge coupled devices (CCD) camera controlled by the serial port and equipped with a zoom lens and a halogen annular light source. Calibration of the imaging system provides a way to transform the acquired images, which are defined in an unknown color space, to a standard, well-defined color space called sRGB. sRGB has a known relation to the CIE1 XYZ and CIE L*a*b* colorimetric spaces. These CIE color spaces are based on the human vision, and they allow the computation of a color difference metric called CIE deltaE*ab, which is proportional to the color difference, as seen by a human observer. Several types of polynomial RGB to sRGB transforms will be tried, including some optimized in perceptually uniform color spaces. The use of a standard and well-defined color space also allows meaningful exchange of images, e.g., in teledermatology. The calibration procedure is based on 24 patches with known color properties, and it takes about 5 minutes to perform. It results in a number of settings called a profile that remains valid for tens of hours of operation. Such a profile is checked before acquiring images using just one color patch, and is adjusted on the fly to compensate for short-term drift in the response of the imaging system. Precision or reproducibility of subsequent color measurements is very good with (deltaE*ab) = 0.3 and deltaE*ab < 1.2. Accuracy compared with spectrophotometric measurements is fair with (deltaE*ab) = 6.2 and deltaE*ab < 13.3.

Calibration↗

PubMed1996

Adaptive noise removal from biomedical signals using warped polynomials.

This paper presents the time-warped polynomial filter (TWPF), a new interval-adaptive filter for removing stationary noise from nonstationary biomedical signals. The filter fits warped polynomials to large segments of such signals. This can be interpreted as low-pass filtering with a time-varying cut-off frequency. In optimal operation, the filter's cut-off frequency equals the local signal bandwidth. However, the paper also presents an iterative filter adaptation algorithm, which does not rely on the (complicated) computation of the local bandwidth. The TWPF has some important advantages over existing adaptive noise removal techniques: it reacts immediately to changes in the signal's properties, independently of the desired noise reduction; it does not require a reference signal and can be applied to nonperiodical signals. In case of quasiperiodical signals, applying the TWPF to the individual signal periods leads to an optimal noise reduction. However, the TWPF can also be applied to intervals of fixed size, at the expense of a slightly lower noise reduction. This is the way nonquasiperiodical signals are filtered. The paper presents experimental results which demonstrate the usefulness of the interval-adaptive filter in several biomedical applications: noise removal from ECG, respiratory and blood pressure signals, and base line restoration of electro-encephalograms (EEG's).

Algorithms↗

PubMed1993

ECG data compression with time-warped polynomials.

This paper presents a new adaptive compression method for ECG's. The method represents each R-R interval by an optimally time-warped polynomial. It achieves a high-quality approximation at less than 250 bits/s. The article shows that the corresponding rates for other transform based schemes (the DCT and the DLT) are always higher. Also, the new method is less sensitive to errors in QRS detection and it removes more (white) noise from the signal. The reconstruction errors are distributed more uniformly in the new scheme and the peak error is usually lower. The reconstruction method is also useful for adaptive filtering of noisy ECG signals.

Algorithms↗

PubMed1992

Data compression of ECG's by high-degree polynomial approximation.

A method for the compression of ECG data is presented. The method is based on high-degree polynomial expansions. Data rates of about 350 bits per second are achievable at an acceptable signal quality. The high compression is obtained by a carefully selected subdivision of the ECG signal into intervals that make optimal use of the special properties of the polynomial base functions. Each interval corresponds to one ECG period. The method is compared to the discrete cosine transform and is found to yield a significantly higher data compression for a given signal quality (quantified by mean squared error and peak error).

Electrocardiography↗

PubMed1983

Intermittent positive pressure ventilation and high frequency ventilation in dogs with experimental bronchopleural fistulae.

This study evaluated respiratory and cardiovascular responses of canines in whom bilateral bronchopleural fistulae were created surgically, and in whom ventilation was varied between intermittent positive pressure ventilation (IPPV) and high frequency ventilation (HFV). An Emerson prototype ventilator was used for HFV at rates of 300-1400/min at driving pressures of 2.5, 5.0, and 10 psi. Gas exchange was judged by arterial and mixed venous blood gases. Cardiac performance was measured by cardiac index, heart rate, stroke index, stroke work index, systemic and pulmonary vascular pressures and resistances. Ventilation during IPPV with the fistula open resulted in a statistically significant increase in PaCO2 and a decrease in PaO2 when compared to both HFV modes. Variations in cardiac function in these open-chested animals were insignificant for all variables tested except pulmonary artery pressures which rose significantly in the IPPV group.

Animals↗

PubMedDate not supplied

Quantitative analysis of the neonatal brain by ultrasound.

Clinical research has shown a clear correlation between white matter disorders of the neonatal brain and neuromotoric handicap at a later age. Ultrasound imaging is a proven method to detect the white matter damage at an early stage. However, since subjective visual examination of the images by neonatologists not always leads to an unambiguous diagnosis, a need for quantitative characterization is felt. Reproducibility is the first requirement in order to be able to perform objective quantitative analysis. This paper proposes a software-based method to compensate for variable acquisition factors that negatively affect the reproducibility of the measurements. The results of some basic experiments will illustrate the usefulness of the developed compensation algorithm.

Algorithms↗