MEDICAL CLINICAL SERVICES ASSESSMENT

Brand Owner (click to sort) Address Description
PREDICTIVFBLAST Univfy Inc. 685 Jay Street Los Altos CA 94022 Medical clinical services for assessment of a subject for an in vitro fertilization treatment cycle, including determining probability of a live birth event;
PREDICTIVFBLAST Univfy Inc. 685 Jay Street Los Altos CA 94022 Medical clinical services for assessment of a subject for an in vitro fertilization treatment cycle, including determining probability of a live birth event;
PREDICTIVFPGS Univfy Inc. 685 Jay Street Los Altos CA 94022 Medical clinical services for assessment of a subject for an in vitro fertilization treatment cycle, including determining probability of a live birth event;
UNIVFY Univfy Inc. 685 Jay Street Los Altos CA 94022 Medical clinical services for assessment of a subject for an in vitro fertilization treatment cycle, including determining probability of a live birth event;
 

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.