Systems and Methods for Image Segmentation in N-Dimensional Space
Description
This technology is a method of determining optimal surfaces in 3-D, 4-D of higher dimensional graphs. Simultaneously detects multiple interacting surfaces in optimal fashion, surfaces that change topology, and incorporates a priori shape knowledge in optimal surface detection process.
Problem
There is an inability for a human image reader to reproducibly and accurately segment volumetric 3D images of: lungs, liver, heart tumors, and other organs.
Solution
This invention overcomes the inability of reproducing and accurately segment volumetric 3D images of organs. Additionally, our invention can segment organs through dynamic 4D image data. The use of volumetric 3D and higher-D contextual information that is generated with our technology, ultimately guarantees optimality in analyzing quantitative parameters of individual objects and their interactions. The intended filed of application is quantitative image analysis from volumetric pulmonary images (CT, MR, etc.).
Value Proposition
This invention presents an improved, low cost, time saving, commercially scalable process for synthesizing a pharmacologically active synthetic triterpenoid CDDO and its derivatives and analogs, from oleanolic acid.
Competitive Advantages
- Overcome limitations of segmentation and characterization of volumetric data
- Provides extensive data that allows accurate segment volumetric 3D & higher-D context
Status of Development
Seeking implementation and research advancement partners
IP Status
- US Patent # US7995810B2
- Licensing Available
