Aselsan Elektronik Sanayi Ve has patented a method for reconstructing images from raw MRI data using joint and individual objective functions. The system acquires multiple images with different contrast mechanisms from the same anatomy and solves an optimization problem to recover the images simultaneously. GlobalData’s report on Aselsan Elektronik Sanayi Ve 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 Aselsan Elektronik Sanayi Ve, was a key innovation area identified from patents. Aselsan Elektronik Sanayi Ve's grant share as of February 2024 was 19%. Grant share is based on the ratio of number of grants to total number of patents.

Mri image reconstruction using joint and individual objective functions

Source: United States Patent and Trademark Office (USPTO). Credit: Aselsan Elektronik Sanayi Ve Ticaret AS

A recently granted patent (Publication Number: US11885863B2) discloses a method for reconstructing images in a magnetic resonance imaging (MRI) system. The method involves acquiring multiple images under different contrast mechanisms within the same anatomy and using an optimization algorithm to reconstruct these images from the acquired data. The optimization problem is solved with joint and individual objective functions simultaneously, with the use of analysis-based methods. The patent details the specific calculations and parameters involved in defining the Contrast Total Variation (CTV) and Generalized Sparse (GSp) functions, as well as the incorporation of sensitivity maps for parallel imaging.

Furthermore, the patent outlines the use of various optimization algorithms such as Alternating Direction Method of Multipliers (ADMM), Conjugate Gradient, or Augmented Lagrangian to solve the optimization problem efficiently. The method also considers the employment of total generalized variation (TGV) and 11-norm of a Wavelet transformation as joint and individual objective functions in reconstructing the MRI images. The patent emphasizes the importance of utilizing known sensitivity maps for parallel imaging and updating the transformation matrix accordingly. Overall, the patent provides a detailed and technical approach to image reconstruction in MRI systems, highlighting the significance of optimization algorithms and objective functions in enhancing image quality and accuracy.

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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.