RadNet has patented a method for automated determination of growth rate of abnormalities in 3D data sets. The process involves trained deep neural networks to detect abnormalities, register them, segment voxels, and calculate growth rate based on volume changes. GlobalData’s report on RadNet gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
According to GlobalData’s company profile on RadNet, was a key innovation area identified from patents. RadNet's grant share as of May 2024 was 43%. Grant share is based on the ratio of number of grants to total number of patents.
Automated determination of growth rate of abnormalities in 3d data
A recently granted patent (Publication Number: US11996198B2) outlines a method for the automated determination of the growth rate of abnormalities in a patient's body part. The method involves utilizing deep neural networks (DNNs) to analyze 3D data sets from different time instances to identify abnormalities and track their growth. The processor registers abnormalities from different time instances, generates 3D maps to identify abnormal voxels, and calculates abnormality volumes to determine growth rates accurately. Additionally, the method includes steps for requesting prior data sets from a database, training multiple 3D DNNs, and generating digital reports with graphical representations of abnormalities and growth rates.
Furthermore, the patent details the training process for multiple 3D DNNs, including the use of training sets with 3D data sets containing abnormalities and volume of interests (VOIs). The method involves training different DNNs to analyze voxel representations, location information, probabilistic 3D maps, and non-linear image transformations to assess abnormalities and similarities between different time instances. The computer system described in the patent includes a storage medium with program code for executing the method, trained 3D DNNs, and processors to perform the operations. Overall, the patent highlights a sophisticated approach to automated abnormality detection and growth rate determination using advanced deep learning techniques and registration algorithms for improved medical imaging analysis.
To know more about GlobalData’s detailed insights on RadNet, buy the report here.
Data Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
