Automated densitometry of cell populations in a continuous-motion imaging cell scanner

Tucker, James H. R.; Husain, O. A. N.; Watts, K. C.; Farrow, Scott; Bayley, R; Stark, Margaret

doi:10.1364/ao.26.003315

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…Dr Husain's interest in automation provoked attempts to standardise the samples that could be subjected to microscopic and automated analysis. Examples include the development of vaginal irrigation/cytopipette as sampling methods, various cell preparation techniques as well as recognising the issues arising from the implementation of new technology such as the cross‐contamination of specimens . He continued an involvement with automation throughout his career .…”

Section: Cytology Automation and Cell Preparationmentioning

confidence: 99%

Nasseem Husain: homage to a pioneer of cytology automation

Kocjan

Herbert

2015

Cytopathology

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This tribute to Dr Husain highlights his valuable contribution to the evolving discipline of cytology and the introduction of automation into cytology processes. Additionally, it gives a fascinating insight into cytology developments from the early 1970 ' s not just in automation but with respect to education , training, quality control methods and organised cervical screening in the UK. This study used mathematical modelling to determine the impact on sample adequacy of limiting the number of FNA passes. Analytical formulae were developed for the expected per-case success and expected number of samples for sampling with a limit using ROSE. Under typical sampling conditions for FNAC, sampling limits have relatively little impact on the per-case probability of success and reduce the expected number of needle passes.

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Section: Cytology Automation and Cell Preparationmentioning

confidence: 99%

Nasseem Husain: homage to a pioneer of cytology automation

Kocjan

Herbert

2015

Cytopathology

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“…The IOD for each isolated nucleus is calculated as the sum of the individual pixel ODs within the segmented object area, corrected by a skirt value [12] to compensate for the background. The skirt value for a segmented object is calculated from the difference between two dilated objects, the larger obtained by Euclidean dilation of the corresponding nucleus by a radius 4 disc, and the smaller one by a disc of radius 2.…”

Section: Three-dimensional Segmentation and Densitometric Measurementmentioning

confidence: 99%

“…The intensity values of each pixel were transformed to optical density (OD) values prior to analysis. This OD transformation was carried out by table look up, using a calibration table obtained by measurements on a photographic test slide which had previously been measured on a microdensitometer [7,12]. Figure 2 shows an example of sections of a typical pair of nuclei which are completely overlapped (only 24 middle sections are shown).…”

Section: Experimental Measurement Proceduresmentioning

confidence: 99%

DNA Measurement of Overlapping Cell Nuclei in Thick Tissue Sections

Liang

Tucker

1997

Analytical Cellular Pathology

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The paper describes an improved image analysis procedure for measuring the DNA content of cell nuclei in thick sections of liver tissue by absorption densitometry. Whereas previous methods only permitted the analysis of isolated nuclei, the new technique enables both isolated and overlapping nuclei to be measured. A 3D segmentation procedure determines whether each object is an isolated nucleus or a pair of overlapping nuclei; in the latter case the combined optical density is redistributed to the individual nuclei. A selection procedure ensures that only complete nuclei are measured.The method has been tested on specially‐prepared Feulgen‐stained 20μ sections of normal liver tissue. The overall distribution of the nuclear DNA measurements shows well‐defined diploid and tetraploid peaks, with coefficient of variations of less than 10%. Similar distributions were obtained from both the isolated nuclei and overlapped nuclei sub‐populations.

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“…The system by Castleman 17 apparently paused to perform static autofocus at regular intervals, and those by Shippey et al 18 and Tucker et al 19,20 autofocused dynamically during scanning. Both Shippey et al 18 and Netten et al 16 reported that the focus error was greater than the depth of field, and Tucker et al 19 reported that a 1-m focus error produced a 12% error in the integrated optical density of the cell nucleus. Autofocus accuracy was reported to be very dependent on the density of cells by Castleman, 17 and the need for many cells in each field of view was common to all of the systems that included autofocus.…”

Section: Introductionmentioning

confidence: 99%

Dynamic autofocus for continuous-scanning time-delay-and-integration image acquisition in automated microscopy

et al. 2007

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Efficient image cytometry of a conventional microscope slide means rapid acquisition and analysis of 20 gigapixels of image data (at 0.3-microm sampling). The voluminous data motivate increased acquisition speed to enable many biomedical applications. Continuous-motion time-delay-and-integrate (TDI) scanning has the potential to speed image acquisition while retaining sensitivity, but the challenge of implementing high-resolution autofocus operating simultaneously with acquisition has limited its adoption. We develop a dynamic autofocus system for this need using: 1. a "volume camera," consisting of nine fiber optic imaging conduits to charge-coupled device (CCD) sensors, that acquires images in parallel from different focal planes, 2. an array of mixed analog-digital processing circuits that measure the high spatial frequencies of the multiple image streams to create focus indices, and 3. a software system that reads and analyzes the focus data streams and calculates best focus for closed feedback loop control. Our system updates autofocus at 56 Hz (or once every 21 microm of stage travel) to collect sharply focused images sampled at 0.3x0.3 microm(2)/pixel at a stage speed of 2.3 mms. The system, tested by focusing in phase contrast and imaging long fluorescence strips, achieves high-performance closed-loop image-content-based autofocus in continuous scanning for the first time.

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Automated densitometry of cell populations in a continuous-motion imaging cell scanner

Cited by 5 publications

References 8 publications

Nasseem Husain: homage to a pioneer of cytology automation

Nasseem Husain: homage to a pioneer of cytology automation

DNA Measurement of Overlapping Cell Nuclei in Thick Tissue Sections

Dynamic autofocus for continuous-scanning time-delay-and-integration image acquisition in automated microscopy

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