SummaryDetection of anomalous cells such as cancer cells from normal blood cells has the potential to contribute greatly to cancer diagnosis and therapy. Conventional methods for the detection of cancer cells are usually tedious and cumbersome. Herein, we report on the use of a particle size analyzer for the convenient size-based differentiation of cancer cells from normal cells. Measurements made using a particle size analyzer revealed that size parameters for cancer cells are significantly greater (e.g., inner diameter and width) than the corresponding values for normal cells (white blood cells (WBC), lymphocytes and splenocytes), with no significant difference in shape parameters (e.g., circularity and convexity). The inner diameter of many cancer cell lines is greater than 10 μm, in contrast to normal cells. For the detection of WBC having similar size to that of cancer cells, we developed a PC software "Cancer Cell Finder" that differentiates them from cancer cells based on brightness inflection points on a cell surface. Furthermore, the aforementioned method was validated for cancer cell/clusters detection in spiked mouse blood samples (a B16 melanoma mouse xenograft model) and circulating tumor cell cluster-like particles in the cat and dog (diagnosed with cancer) blood samples. These results provide insights into the possible applicability of the use of a particle size analyzer in conjunction with PC software for the convenient detection of cancer cells in experimental and clinical samples for theranostics.
Objective The aim of this study was to evaluate the usefulness of reconstructed computed tomography (CT) images using OsiriX software in detecting wooden and bamboo foreign bodies. Methods Four sizes of wet and dry wooden and bamboo foreign bodies were selected to be analyzed. Those in the air and in the head of edible swine were scanned with a multidetector row CT scanner. The images were evaluated with OsiriX software in the bone and the abdomen window setting as unprocessed images. Three-dimensional rendered images assigned colors and opacity by a 16-bit color look-up table (CLUT) editor in OsiriX software were evaluated as processed images. Results In the unprocessed images, dry and wet foreign bodies in the air were not detected except a part of wet wooden foreign bodies, and all the dry and wet foreign bodies in the swine's head mimicked air with linear shapes. In the processed images, all the dry and wet foreign bodies in the air were detected clearly, and all the wooden and some of the bamboo foreign bodies in the swine's head were detected clearly. Conclusions CT images processed using OsiriX software, especially with a CLUT editor, were useful in detecting wooden and bamboo foreign bodies.
SUMMARYIt is known that linear phase FIR digital filters fall into four types considering the symmetry of impulse response. For example, filters of type 2 can be used at the time of partitioning and reconstruction of signals in multirate signal processing, and other types have similar special applications. Moreover, the linear phase FIR digital filters with flat passband and equiripple stopband characteristics are very important filters in practice because they have better time domain characteristics and less ringing than Chebyshev filters with equiripple stopband and passband characteristics. However, conventional design methods are restricted to type 1. In this paper, we therefore propose a method of design of linear phase FIR digital filters with flat passband and equiripple stopband characteristics for all four types. The proposed function is composed of two functions, one with a flat characteristic in the passband and the second with equiripple characteristics in the stopband. The latter function is obtained by using the well-known Remez algorithm only for the stopband.
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