Sysmex had five patents in big data during Q4 2023. Sysmex Corp filed patents for an image analysis method using deep learning to identify cell nucleus regions in tissue or cell images, and a specimen analyzer utilizing artificial intelligence algorithms to analyze optical signals and process data related to analytes in specimens. GlobalData’s report on Sysmex gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Sysmex grant share with big data as a theme is 60% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Image analysis method, apparatus, program, and learned deep learning algorithm (Patent ID: US20230419696A1)
The patent filed by Sysmex Corp. describes an image analysis method using a deep learning algorithm to generate data indicating the region of a cell nucleus in an image of tissue or a cell. The method involves analyzing the image using a neural network structure and inputting analysis data from the image into the algorithm to identify the cell nucleus region. Training data for the algorithm are generated based on bright field and fluorescence images of the same tissue specimen or sample, with the fluorescence image indicating the cell nucleus region.
The image analysis system outlined in the patent includes an imaging device to capture images of tissue or cells, connected to an image analysis apparatus that utilizes a deep learning algorithm for analysis. The system generates analysis data from the target image, inputs it into the algorithm, and identifies the cell nucleus region. The training data for the algorithm are derived from bright field and fluorescence images of the same specimen, with the fluorescence image converted to binary data to indicate the cell nucleus region. Additionally, the system can output a cell nucleus region weighted image where the identified region is superimposed on the original image for visualization purposes.
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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.
