Abstract: A process for determining whether tissue is precancer, in which tests discriminating between precancer and benign tissue and between precancer and normal tissue are combined, and tissue that is classified as precancer in both tests is determined to be precancer, in which neither of the tests to be combined is the most selective. Further, a process and device in which certain optimal wavelengths of glycogen, phosphate and lipid, but not protein, discriminate between normal and precancer tissues.

Abstract: A process for maintaining 3 dimensional orientation between a tissue specimen and images of the area of investigation, to register histopathologic diagnoses of multiple locations within the specimen with corresponding locations on the surface of said area of investigation.

Abstract: The present invention is an automated image analysis framework for cervical cancerous lesion detection. The present invention uses domain-specific diagnostic features in a probabilistic manner using conditional random fields. In addition, the present invention discloses a novel window-based performance assessment scheme for two-dimensional image analysis, which addresses the intrinsic problem of image misalignment. As a domain-specific anatomical feature, image regions corresponding to different tissue types are extracted from cervical images taken before and after the application of acetic acid during a clinical exam. The unique optical properties of each tissue type and the diagnostic relationships between neighboring regions are incorporated in the conditional random field model. The output provides information about both the tissue severity and the location of cancerous tissue in an image.

Abstract: A rule-based unsupervised process for classifying cervical tissue by serially applying classifiers selected from the group that consists of determining size of texture region, opacity parameter, size of acetowhite regions, number of coarse and fine punctations, size of coarse and fine mosaics, size of atypical blood vessels and demographic data, so that the cervical tissue can be classified into no evidence of disease, low-grade dysplasia, high-grade dysplasia or cancer.

Abstract: Automated image quality assessment algorithms, which perform the functions of locating a region of interest, maximizing the image contrast, and ensuring the region of interest is properly centered in the image. Wherein the region of interest is located by spectral matching filter using a target spectrum obtained from samples of the image itself.

Abstract: A method of contrast enhancement for improved visualization of diagnostically important tissue structures, such as blood vessels. A texture analysis algorithm is applied to identify regions with a high likelihood of disease. Mathematical morphology operations are applied to identify areas of high and low brightness (intensity). The low intensity areas are then subtracted, and controllably variable amounts of the high intensity areas are added, controlled by a selectable tuning parameter, to produce an image with controllably variable visualization enhancement.

Abstract: Automated image quality assessment methods, which include locating a region of interest, region assessment, contrast assessment, blur assessment, and contaminant detection, on video data and high-resolution imagery. Where the blur assessment is performed without a reference image by dividing the region into non-overlapping block, measuring the wavenumber frequency of the blocks and calculating the ratio of the low frequency to high frequency areas.

Abstract: This invention uses LEDs and cross-polarization to produce bright, high-resolution digital images, both with and without glint (which adversely affects the clarity of standard colposcopic images), as well as streaming video at lower resolution. The invention allows for deeper layers of the tissue to be more efficiently visualized at multiple magnifications, thereby enhancing the invention's diagnostic capabilities, and it includes a focusing subsystem and a computerized data management system to archive and annotate still image data.

Abstract: A method for differentiating cancerous lesions from surrounding tissue, which includes extracting an opacity parameter from acetowhite regions of pre acetic acid and post acetic acid images of a cervix.

Abstract: An apparatus for determine a glucose level having a calibration module; an image acquisition module; an image compensation module; and, a dynamic pattern matching module. A method using the apparatus is also described.

Abstract: The present invention discloses a method for the detection of atypical vessels in digital cervical imagery. A pre-processing stage is applied to enhance the contrast of blood vessel features compared to the surrounding tissue. Next, a segmentation stage is applied to identify regions of interest for atypical vessels using texture and gradient information. Finally, a post-processing stage (1) identifies other clinically relevant features in the cervical imager, and removes these features from the region of interest; and (2) uses color, size, and shape information to further refine the region of interest to eliminate false positives and determine a final region of interest. This automated method of atypical vessel detection is especially useful for diagnostic purposes such as cervical cancer detection.

Abstract: A method of automated image calibration that corrects for non-uniform illumination and calibrates color that is simple, fast, automated, accurate and reliable. A gray balance algorithm is applied to correct for non-uniform illumination and a color calibration algorithm is then applied to calibrate the human subject data. The system has been applied in multiple clinical sites with different instruments.

Abstract: The noninvasive measurement system provides a technique for manipulating wave data. In particular, wave data reflected from a biological entity is received, and the reflected wave data is correlated to a substance in the biological entity. The wave data may comprise light waves, and the biological entity may comprise a human being or blood. Additionally, a substance may comprise, for example, a molecule or ionic substance. The molecule may be, for example, a glucose molecule. Furthermore, the wave data is used to form a matrix of pixels with the received wave data. The matrix of pixels may be modified by techniques of masking, stretching, or removing hot spots. Then, the pixels may be integrated to obtain an integration value that is correlated to a glucose level. The correlation process may use a lookup table, which may be calibrated to a particular biological entity.

Abstract: Uterine cervical cancer Computer-Aided-Diagnosis (CAD) according to this invention consists of a core processing system that automatically analyses data acquired from the uterine cervix and provides tissue and patient diagnosis, as well as adequacy of the examination. The data can include, but is not limited to, color still images or video, reflectance and fluorescence multi-spectral or hyper-spectral imagery, coherent optical tomography imagery, and impedance measurements, taken with and without the use of contrast agents like 3-5% acetic acid, Lugol's iodine, or 5-aminolevulinic acid. The core processing system is based on an open, modular, and feature-based architecture, designed for multi-data, multi-sensor, and multi-feature fusion. The core processing system can be embedded in different CAD system realizations.