Abstract: The contrast of an image produced by epifluorescence microscopy may be increased by placing a dichroic reflector behind the sample. The dichroic reflector reflects the emission light emitted by the fluorescent tags in the sample back through the objective lens while allowing the shorter wavelength excitation light to pass through the sample holder.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: The contrast of an image produced by epifluorescence microscopy may be increased by placing a high-pass dichroic reflecting film behind the sample. The reflecting film reflects the emission light emitted by the fluorescent tags in the sample back through the objective lens while allowing the shorter wavelength excitation light to pass through the sample holder.

Abstract: Among embodiments is disclosed a process for immunostaining a sample such that the stain is stable under FISH conditions

Abstract: A system for reading microscope slides in an automated fashion.

Abstract: An imager system is disclosed comprising a image intensifier and a CMOS image sensor. The system provides fast capture speed and high sensitivity.

Abstract: A non-invasive method for determining the developmental age of a fetus or detecting cancer cells in a sample is provided. The method utilizes, for example, a sample of blood from a pregnant female and telomeric nucleic acid probes.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map may be segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map may be compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method for segmenting an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The image is segmented by thresholding the fractal map of the image.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: The present invention provides devices and methods for detection of particles, such as biological cells, in samples using a photosensitive waveguide. The photosensitive waveguide changes its transmissivity in a detectable manner in response to controlling radiation emitted from the particles. In preferred embodiments, the waveguide is two-dimensional and the position of the particles as well as their presence is obtained by scanning the waveguide in two non-parallel directions. The provided devices are preferably used to locate labeled cells. The present invention also includes control systems and methods for detecting and locating cells using the devices provided.

Abstract: A method for segmenting an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The image is segmented by thresholding the fractal map of the image.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is a fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is a fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is a fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is a fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: A computer controlled method for detecting and diagnosing a rare cell type in a tissue sample is provided, said method comprising treating the tissue sample such that it generates a first signal indicative of the presence at a location of a rare cell, detecting the first signal, treating the location at which the first signal is detected to generate a second signal indicative of a diagnostically useful cellular characteristic and detecting the second signal. The first signal can be morphological or a color present in a sought cell either before or after staining. The second signal can be generated by in situ PCR or PCR in situ hybridization. In one preferred embodiment, the rare cell type is a fetal cell in a maternal blood tissue sample, said sample consisting of a smear of unenriched maternal blood. In another embodiment, the method is used to diagnose or genotype cancer cells in a blood or tissue biopsy sample.

Abstract: The contrast of an image produced by epifluorescence microscopy may be increased by placing a high-pass dichroic reflecting film behind the sample. The reflecting film reflects the emission light emitted by the fluorescent tags in the sample back through the objective lens while allowing the shorter wavelength excitation light to pass through the sample holder.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.