| 摘要 |
Methods and apparatus to diagnostic techniques which programmatically generate N-dimensional histograms from data obtained from volumetric data sets, such as those obtained using particle analyzers and flow cytometers. Received data is processed utilizing data shaping techniques such as noise and outlier filtering, segregation and amplification of desired data, and thresholding of data sets, to aid in the detection of abnormalities. In biological samples, such abnormalities are often indicative of disease, and therefore it is important to provide consistently accurate results. Populations of biological abnormalities may be detected and enumerated using multiple parameters, such as fluorescence, optical, and electrical parameters, and displayed in a manner which maximizes information content. |
