KITS COMPRISED CLINICAL MEDICAL

Brand Owner Address Description
HONEYCOMB PATTERN BIOSCIENCE, INC. 9600 Great Hills Trail, Suite 160E Austin TX 78759 Kits comprised of clinical medical reagents and antibiotics in test containers for clinical laboratory use in detecting, quantifying, and analyzing disease-causing micro-organisms;Chemical compositions for use in detecting and quantifying biological and chemical molecules; kits comprised primarily of reagents for research purposes in test containers for clinical laboratory use in detecting, quantifying, and analyzing disease-causing microorganisms and also including antibiotics in test containers for clinical laboratory use in detecting, quantifying, and analyzing disease-causing micro-organisms;
 

Where the owner name is not linked, that owner no longer owns the brand

    
Technical Examples
  1. A method and apparatus are provided for adjusting a dynamic range of a digital medical image for a medical imaging system. The digital medical image contains a clinical region and a non-clinical region. The method and apparatus identify the non-clinical region of the digital medical image and mask the non-clinical region therefrom to form a clinical image. The clinical image is then used to calculate a desired dynamic range for the medical imaging system. The dynamic range of the medical imaging system is adjusted accordingly. According to one embodiment, the non-clinical region is identified by dividing the digital medical image into bands of a predetermined width, generating profiles for each band and differentiating the profiles to obtain a differentiated profile of each band of a digital medical image. The differentiated profile is than analyzed to identify peaks that exceed predetermined thresholds, wherein the regions of the differentiated profile proximate the peaks exceeding the threshold correspond to non-clinical regions. Once the non-clinical regions are identified, they are masked or removed. Next, a desired image characteristic, such as maximum and minimum gray scale values, are determined for the clinical region and a desired dynamic range for the image is obtained based on the image characteristics of the clinical region. In an alternative embodiment, a histogram is used to identify the non-clinical regions which are subsequently masked from the digital medical image.