Biomedical subjects

K S Kump

Publications and source records attributed to K S Kump.

3 recordsLinked to original sources

PubMed2001

Comparison of algorithms for combining X-ray angiography images.

Using a one-dimensional convective-dispersive model of contrast agent flow in a blood vessel, we optimized and compared algorithms for combining a temporal sequence of X-ray angiography images, each with incomplete arterial filling, into a single-output image with fully opacified arteries. The four algorithms were: maximum opacity (MO) with a maximum over time at each spatial location; matched filtering (MAT); recursive filtering (REC) with a maximum opacity; and an approximate matched filter (AMF) consisting of a correlation with a kernel that approximates the matched filter kernel followed by a maximum opacity operation. Based on the contrast-to-noise ratio (CNR), MAT is theoretically the best algorithm. However, with spatially varying clinical images, a poorly matched MAT kernel greatly degraded CNR to the point of even inverting artery contrast. The practical AMF method maintained uniform CNR values over the entire field of view and gave >90% of the theoretical limit set by MAT. REC and MO created fully opacified arteries, but provided little CNR enhancement. By holding CNR at a nominal reference value, simulations predicted that AMF could be used with a contrast agent volume reduced by as much as 66%. Alternatively, X-ray exposure rate could be lowered. Although MO and REC are more easily implemented, the contrast enhancement with AMF makes it attractive for processing diagnostic angiography images acquired with a reduced contrast agent dose.

Algorithms↗

PubMed2001

Digital subtraction peripheral angiography using image stacking: initial clinical results.

Using clinically acquired x-ray angiography image sequences, we compared three algorithms for creating a single diagnostic quality image that combined input images containing flowing contrast agent. These image-stacking algorithms were: maximum opacity with the minimum gray-scale value across time recorded at each spatial location, (REC) recursive temporal filtering followed by a maximum opacity operation, and (AMF) an approximate matched filter consisting of a convolution with a kernel approximating the matched filter followed by a maximum opacity operation. Eighteen clinical exams of the peripheral arteries of the legs were evaluated. AMF gave 2.7 times greater contrast to noise ratio than the single best subtraction image and 1.3 times improvement over REC, the second best stacking algorithm. This is consistent with previous simulations showing that AMF performs nearly equal to the optimal result from matched filtering without the well-known limitations. For example, unlike matched filtering, AMF filter coefficients were obtained automatically using an image-processing algorithm. AMF effectively brought out small collateral arteries, otherwise difficult to see, without degrading artery sharpness or stenosis grading. Comparing results using reduced and full contrast agent volumes demonstrated that contrast agent load could be reduced to one-third of the conventional amount with AMF processing. By simulating reduced x-ray exposures on clinical exams, we determined that x-ray exposure could be reduced by 80% with AMF processing. We conclude that AMF is a promising, potential technique for reducing contrast agent load and for improving vessel visibility, both very important characteristics for vascular imaging.

Algorithms↗

PubMed1993

Adaptive buffering of breath-by-breath variations of end-tidal CO2 of humans.

We have designed and implemented a computer-controlled system that uses an adaptive control algorithm (generalized minimum variance) to buffer the breath-by-breath variations of the end-tidal CO2 fraction (FETCO2) that occur spontaneously or are exaggerated in certain experimental protocols (e.g., induced hypoxia, any type of induced variations in the ventilatory pattern). Near the end of each breath, FETCO2 of the following breath is predicted and the inspired CO2 fraction (FICO2) of the upcoming breath is adjusted to minimize the difference between the predicted and desired FETCO2 of the next breath. The one-breath-ahead prediction of FETCO2 is based on an adaptive autoregressive with exogenous inputs (ARX) model: FETCO2 of a given breath is related to FICO2, FETCO2 of the previous breath, and inspiratory ventilation. Adequacy of the prediction is demonstrated using data from experiments in which FICO2 was varied pseudorandomly in wakefulness and sleep. The algorithm for optimally buffering changes in FETCO2 is based on the coefficients of the ARX model. We have determined experimentally the frequency of FETCO2 variations that can be buffered adequately by our controller, testing both spontaneous variations in FETCO2 and variations induced by hypoxia in young awake human subjects. The controller is most effective in buffering variations of FETCO2 in the frequency range of <0.1 cycle/breath. Some potential applications are discussed.

Adaptation, Physiological↗