Company Filing History:
Years Active: 2021-2025
Title: Marcin Sieniek: Innovator in Medical Imaging Technology
Introduction
Marcin Sieniek is a prominent inventor based in Mountain View, CA (US), known for his contributions to the field of medical imaging technology. With a total of 3 patents, Sieniek has made significant strides in utilizing deep learning to enhance the interpretation of medical images.
Latest Patents
One of Sieniek's latest patents is titled "System and method for interpretation of multiple medical images using deep learning." This method involves processing a set of images, where each image has an associated counterpart. Regions of interest (ROIs) are identified, and reference regions in the counterpart images are cropped out to form pairs that are fed into a deep learning model. This model predicts the probability of a disease state based on the ROIs, generating an overall prediction from the individual predictions. Additionally, he holds a patent for a "System, user interface and method for interactive negative explanation of machine learning localization models in health care applications." This system assesses a machine learning model's predictions regarding a patient's disease state from 2D or 3D images. It presents the image along with a risk score, highlighting regions that influenced the prediction, allowing users to interactively assess the model's output.
Career Highlights
Marcin Sieniek is currently employed at Google Inc., where he continues to innovate in the realm of medical technology. His work focuses on integrating machine learning with healthcare applications, aiming to improve diagnostic accuracy and patient outcomes.
Collaborations
Sieniek collaborates with talented individuals such as Scott McKinney and Varun Godbole, contributing to a dynamic team that pushes the boundaries of medical imaging technology.
Conclusion
Marcin Sieniek's innovative work in medical imaging and deep learning exemplifies the potential of technology to transform healthcare. His patents reflect a commitment to improving diagnostic processes and enhancing patient care through advanced methodologies.