Location History:
- Bengaluru, IN (2016)
- Karnataka, IN (2019)
Company Filing History:
Years Active: 2016-2019
Title: Innovations by Soma Biswas in Ultrasound Imaging
Introduction
Soma Biswas is an accomplished inventor based in Karnataka, India. She has made significant contributions to the field of medical imaging, particularly in ultrasound technology. With a total of 2 patents to her name, her work focuses on improving lesion detection in ultrasound images.
Latest Patents
Soma's latest patents include a method and system for lesion detection in ultrasound images. This innovative method involves acquiring ultrasound information and determining discriminative descriptors that describe the texture of a candidate lesion region. The process classifies each descriptor as one of several categories, including top boundary pixel, lesion interior pixel, lower boundary pixel, or normal tissue pixel. Additionally, the method determines a pattern of transitions between these classified descriptors to classify the candidate lesion region as either a lesion or normal tissue. Another patent also addresses lesion detection by generating a Fisher-Tippett (FT) distribution-based edge feature map from the acquired ultrasound image. This method generates gradient concentration (GC) scores for the pixels and identifies a candidate lesion region based on these scores.
Career Highlights
Soma Biswas is currently employed at General Electric Company, where she continues to innovate in the field of medical imaging. Her work has the potential to significantly enhance the accuracy of ultrasound diagnostics, thereby improving patient outcomes.
Collaborations
Soma collaborates with talented professionals in her field, including Rakesh Mullick and Vivek Prabhakar Vaidya. These collaborations foster an environment of innovation and creativity, leading to advancements in ultrasound technology.
Conclusion
Soma Biswas is a pioneering inventor whose work in ultrasound imaging is making a substantial impact in the medical field. Her innovative methods for lesion detection are paving the way for more accurate and efficient diagnostics.