RadNet. has been granted a patent for a method that automates the determination of growth rates for abnormalities in 3D medical data. The process utilizes trained deep neural networks to identify and map volumes of interest across different time instances, enabling precise volume calculations and growth rate assessments. GlobalData’s report on RadNet gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on RadNet, was a key innovation area identified from patents. RadNet's grant share as of June 2024 was 49%. Grant share is based on the ratio of number of grants to total number of patents.
Automated method for determining growth rate of abnormalities
The patent US11996198B2 outlines a method and system for the automated determination of the growth rate of abnormalities in a patient's body part using advanced 3D deep neural networks (DNNs). The process begins with a current 3D data set, which is analyzed by a first DNN trained to identify abnormalities and output volumes of interest (VOIs) associated with these abnormalities. A prior 3D data set is then registered with the current data set using a registration algorithm, allowing for the mapping of VOIs from both time instances. This enables the system to generate probability maps that indicate the likelihood of voxels being part of the identified abnormalities, facilitating the calculation of their respective volumes.
Additionally, the method incorporates the use of metadata to retrieve prior data sets and employs various DNN architectures, including convolutional and Siamese networks, to enhance the accuracy of abnormality detection and volume estimation. The registration algorithm may utilize non-rigid transformations and similarity scoring to ensure precise alignment of VOIs across time points. Ultimately, the system aims to produce a digital report that includes graphical representations of the abnormalities and their growth rates, thereby providing valuable insights for medical professionals in monitoring and diagnosing conditions.
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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.
