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M A MacCollum

Publications and source records attributed to M A MacCollum.

4 recordsLinked to original sources
PubMed1984

A count-dependent filter for smoothing flow cytometric histograms.

An adaptive count-dependent algorithm for smoothing statistically limited histograms has been developed. It considers both the spatial frequency limitations of the measurement system (described by the measurement system point spread function) and the reliability of the measured data (indicated by the effective number of counts influencing each channel of the histogram. Windows for smoothing flow cytometric histograms are derived from an assumed Gaussian-shaped point spread function (PSF) with a constant coefficient of variation. The windows are developed by scaling the variances of the Gaussian functions inversely with the statistical reliability of the data contained in each channel of the measured histogram. The reliability of this data is determined by taking the square root of the number of counts influencing the value tabulated for each channel. Using the algorithm, a smoothed version of the measured histogram may be developed from a linear sum of the products of the individual scaled Gaussian functions and the original measured histogram. Data are presented demonstrating the advantages of count-dependent smoothing over non-count-dependent smoothing using synthesized DNA histograms as a function of sample size.

Cell Cycle↗
PubMed1984

Design of flow chamber with electronic cell volume capability and light detection optics for multilaser flow cytometry.

A multibeam optical detection system has been developed with a high optical efficiency, achieved through a reduction in the number of optical interfaces employed in the system. This reduction is made possible by a combination of employing simple lenses, gluing the objective lens directly upon the face of the flow cuvette and the extraction of only one fluorescence signal from each laser beam. A modified flow chamber is also described that includes fluidic resistance elements for the elimination of most of the electric shielding normally associated with electronic cell volume measurements.

Animals↗
PubMed1983

High resolution method for the analysis of DNA histograms that is suitable for the detection of multiple aneuploid G1 peaks in clinical samples.

The DNA histogram obtained by flow cytometry can be considered as the product of an "ideal" measurement column vector and a measurement distortion matrix. In order to extract the ideal histogram from the real data, the measurement distortion matrix is commonly presumed to be a family of Gaussian coefficients that are centered on the diagonal. We have designed a feedback-controlled curve-fitting procedure that reconstructs the ideal histogram from the real data through successive iterations. The optimum coefficient of variation (cv) for the family of Gaussians in the measurement distortion matrix is determined from an analysis of the sums of squares of fits of the computed DNA histogram to the real data over an appropriate range of trial cv. Since this method assigns a Gaussian to each and every data channel, it permits the resolution of closely spaced multiple aneuploid G1 peaks in clinical samples. The effects of high frequency noise that may be present in the data can be attenuated by multiplying the real data histogram by a Gaussian matrix with cv close to but smaller than that of the measurement distortion matrix.

Aneuploidy↗