NovoCure’s patented method involves using machine learning to improve the accuracy of tumor treating fields (TTFields) therapy by evaluating the quality of MRI image segmentations of a patient’s head. The system measures Dice coefficients, registration quality, and tissue type indicators to determine the best segmentation for treatment planning. GlobalData’s report on NovoCure 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 NovoCure, Neuromodulation implants was a key innovation area identified from patents. NovoCure's grant share as of February 2024 was 34%. Grant share is based on the ratio of number of grants to total number of patents.
Quality assessment of mri image segmentation for ttfields therapy
A recently granted patent (Publication Number: US11915424B2) discloses a method for determining the quality of a segmentation of an image of a head containing multiple tissue types. The method involves measuring the Dice coefficient between a computed head segmentation and a validated head segmentation from a training set, estimating registration quality, using indicators like shortest axis length and signal-to-noise ratio for each tissue type, and comparing the measured Dice coefficient to predictions based on Dice coefficients.
Furthermore, the method includes various steps such as describing segmentation shape using volume and connected components, outputting quality scores for the computed head segmentation based on comparisons with predictions, generating predictions based on features describing segmentation shape, utilizing decision tree regressor, and measuring separate Dice coefficients for each tissue type. The method aims to provide a comprehensive assessment of the quality of the computed head segmentation for different regions within the input image and for each tissue type separately, enhancing the accuracy and reliability of image analysis processes in the field of medical imaging.
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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.
