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Automated classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. We have investigated this possibility experimentally and numerically using a diffraction imaging approach. A fast image analysis software based on the gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images. The results of GLCM analysis and subsequent classification demonstrate the potential for rapid classification among six types of cultured cells. Combined with numerical results we show that the method of diffraction imaging flow cytometry has the capacity as a platform for high-throughput and label-free classification of biological cells.

We appreciate the authors' comments in their reply: "On the identification of chromosomes with Raman spectroscopy: a critical comment" [Opt. Express 15, 5997 (2007)]. Their main concern with our paper is asking if the collected spectra have shown the identification or differentiation between three human chromosomes. We think this comment is flawed because the authors misunderstood the main points of the original paper and interpreted the presented spectra data (Fig. 3 and Table 1) incorrectly.

The ability to identify specific chromosomes with certainty has been established by the development of several cytogenetic techniques based on staining. Here, we report the use of a new optical technique, laser tweezers and Raman spectroscopy (LTRS), to capture and manipulate chromosomes in order to obtain their spectral patterns for molecular analysis without the need for staining. The purpose of this study was to obtain Raman spectroscopy patterns for chromosomes number 1, 2, and 3 and to test if the Raman spectroscopy pattern could be used to distinguish these three chromosomes. In our experiment, optical tweezers were used to capture the individual chromosomes and the Raman spectral patterns were collected for the trapped chromosomes. Then, the captured chromosome was manipulated with the optical tweezers and moved to another chamber through a micro - channel, in which the chromosomes were G- banded for positive identification as chromosome number 1, 2, or 3. Generalized discriminate analysis (GDA) was used to compare the Raman signatures. This analysis revealed that chromosomes 1, 2, and 3 could be distinguished and identified based on their Raman spectra. Development of this approach will lead to more rapid automatic methods for chromosome analysis and identification without the use of prior staining. Moreover, the Raman spectral patterns may lend themselves to more detailed analysis of chromosomal structure than is currently available with standard staining protocols. Such analysis may some day be useful for rapid, automated screening and diagnosis for certain cancers.