Location History:
- Madison, CT (US) (2017)
- Cambridbe, MA (US) (2020)
- New Haven, CT (US) (2022)
Company Filing History:
4 out of 1,327 
2 out of 21,384 
1 out of 2,077 
Years Active: 2017-2025
Title: Innovations of James S. Duncan
Introduction
James S. Duncan is a notable inventor based in Madison, CT (US). He has made significant contributions to the field of clinical radiology through his innovative patents. With a total of 4 patents, Duncan's work focuses on enhancing medical imaging techniques and artificial intelligence applications in healthcare.
Latest Patents
One of his latest patents is titled "Interpretable deep machine learning for clinical radiology." This invention provides a computer-implemented method for identifying clinical factors associated with artificial intelligence predictions. The method involves applying a previously trained deep neural network to images of a subject, comparing node outputs to identified patterns, and determining which clinical factors correlate most with these outputs.
Another significant patent is "CBCT to MR registration via occluded shape reconstruction and robust point matching." This invention describes an image guidance method that acquires a stream of cone-beam computed tomography (CBCT) images of an anatomical organ. It includes segmenting the organ's surface, reconstructing occluded portions, and spatially registering pre-operative medical images with CBCT images to create a fused image for better visualization.
Career Highlights
James S. Duncan has worked with prestigious organizations, including Yale University and Koninklijke Philips Corporation. His experience in these institutions has allowed him to collaborate on groundbreaking research and development projects in medical imaging and artificial intelligence.
Collaborations
Duncan has collaborated with notable colleagues such as John Treilhard and Susanne Smolka. Their combined expertise has contributed to the advancement of innovative solutions in the medical field.
Conclusion
James S. Duncan's contributions to the field of clinical radiology through his patents demonstrate his commitment to improving healthcare technology. His innovative approaches in deep learning and medical imaging continue to influence the industry positively.