CELLS MEDICAL CLINICAL

Brand Owner (click to sort) Address Description
ANKOR BIOLOGICS NANTKWEST, INC. 2533 SOUTH COAST HIGHWAY 101 STE. 210 THE PLASTINO BUILDING CARDIFF-BY-THE-SEA CA 920072133 cells for medical and clinical use; biological and pharmaceutical preparations for the treatment of infectious diseases; pharmaceutical products for the treatment of infectious diseases; therapeutic pharmaceutical for the treatment of infectious diseases;cells for scientific, laboratory or medical research;The wording ANKOR has no meaning in a foreign language or significance in applicant's industry.;BIOLOGICS;biological research in the area of infectious diseases;
NEUCYTE Neucyte, Inc. 3657 Ramona Circle Palo Alto CA 94306 Cells for medical and clinical research for the development of pharmaceutical products;
SYNFIRE Neucyte, Inc. 3657 Ramona Circle Palo Alto CA 94306 Cells for medical and clinical research for the development of pharmaceutical products;
T-CUBED DISCOVERY LABWARE, INC. 2 OAK PARK BEDFORD MA 01730 cells for medical and clinical use;TISSUE TRANSFORMATION TECHNOLOGIES;
T3 Tissue Transformation Technologies, Inc. Edison Corporate Center 175 May Street, Suite 600 Edison NJ 08837 cells for medical and clinical use;
TISSUE TRANSFORMATION TECHNOLOGIES Tissue Transformation Technologies, Inc. Edison Corporate Center 175 May Street, Suite 600 Edison NJ 08837 cells for medical and clinical use;
 

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.