Company Filing History:
Years Active: 2008
Title: Ruth Heimann: Innovator in Computerized Image Analysis for Prognosis
Introduction
Ruth Heimann is a notable inventor based in Burlington, VT (US). She has made significant contributions to the field of medical imaging, particularly in the area of prognosis determination through computerized image analysis. Her innovative work aims to enhance decision-making in treatment options for patients with cancer.
Latest Patents
Ruth Heimann holds a patent for an "Automated method and system for computerized image analysis for prognosis." This automated method determines prognosis based on an analysis of abnormality features and parenchymal features obtained from medical image data of a patient. The techniques involved include segmentation of lesions from radiographic images, extraction of lesion features, and merging these features with clinical information to estimate prognosis for specific cases. An example of her work is the prognosis of breast cancer lesions using mammographic data. The computerized image analysis system she developed combines the analysis of medical images of cancerous lesions with training-based methods to assess patient prognosis, utilizing indicators such as lymph node involvement and presence of metastatic disease. This system is expected to aid in improved decision-making regarding treatment options.
Career Highlights
Ruth Heimann is affiliated with the University of Chicago, where she continues her research and development in medical imaging technologies. Her work has the potential to significantly impact the field of oncology by providing more accurate prognostic assessments.
Collaborations
Ruth has collaborated with esteemed colleagues such as Maryellen L. Giger and Ioana Bonta, contributing to advancements in the field of medical imaging and prognosis determination.
Conclusion
Ruth Heimann's innovative contributions to computerized image analysis for prognosis exemplify the intersection of technology and healthcare. Her work not only enhances the understanding of cancer prognosis but also supports better treatment decisions for patients.
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