CureMetrix是一家医学图像分析公司，旨在为医疗机构和患者提供可信赖的下一代医学图像分析技术。该公司在收集了超过50万张图片以训练和验证专有算法的基础上推出了图像分析平台CureMetrix?，希望能成为乳腺X射线检查的辅助精密工具，去帮助医生完成患者的乳腺癌筛查、治疗和诊断。目前，该平台已被尝试应用在乳腺癌的胸部透视图领域，并受到Analytics Ventures和evoNexus等多家投资公司的青睐。

  Confidence in Cancer Screening.That’s our vision at CureMetrix®.

  CureMetrix is committed to the advancement of technology that will improve cancer survival rates worldwide. Our research is focused on designing the next generation of medical image analysis technology that healthcare providers and patients can confidently rely on.

  Today, we are honing our powerful image analysis platform into an adjunct, precision tool for mammography. Our goal is to equip radiologists with the objective, data-driven answers they need to support patients and their healthcare team as they make decisions about breast cancer screening, treatment and diagnosis. At CureMetrix, we believe that providing radiologists with the most advanced technology to support their evaluation of mammograms will lead to improved clinical outcomes, reduced healthcare costs and increased assurance that patients are getting the highest standard of care available from screening through post-biopsy follow-up.

  We have surveyed radiologists globally and they have expressed the need to improve the performance of their existing Computer Aided Detection (CAD) software. At CureMetrix, we are building a ‘CAD that works.’

  To support our efforts, CureMetrix has partnered with esteemed institutions such as UC San Diego and MD Anderson to train and validate our algorithm’s ability to recognize different types of anomalies. We’ve collected more than 500,000 images to train and validate our proprietary algorithm. We are working on developing technology to:

  Accurately detect, quantify and classify anomalies in screening and diagnostic mammograms

  Differentiate between various types of anomalies to help radiologists focus first on suspicious lesions, while discarding verifiably benign ones

  Reduce the rates of false positives and false negatives to improve clinical efficacy, operational efficiency and financial outcomes - while, most importantly, easing the anxiety that such diagnoses can cause patients