Alibaba Group had six patents in metaverse during Q4 2023. The patent filed by Alibaba Group Holding Ltd in Q4 2023 describes a method for detecting ribs in medical images using feature coding and a neural network model. The method allows for controllable rib detection at the instance level by focusing on different rib regions and providing semantic information in anatomy. The rib detection results include rib prediction classification and pose parameter prediction in a three-dimensional space. GlobalData’s report on Alibaba Group gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
Alibaba Group grant share with metaverse as a theme is 33% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Method for detecting a rib with a medical image, device, and medium (Patent ID: US20230401706A1)
The patent filed by Alibaba Group Holding Ltd. describes a method for detecting ribs in a medical image using a neural network model. The method involves feature coding on different rib regions to obtain feature vectors, determining feature vectors for rib query items, and performing parallel decoding to obtain rib detection results. These results include rib prediction classification and pose parameter prediction in a three-dimensional space. The method allows for controllable rib detection at the instance level, with semantic information in anatomy. The patent also covers the superimposition and display of rib detection results on real images, enhancing augmented reality applications.
Furthermore, the patent details the segmentation of rib instances from medical images based on the detection results, including operations like random displacement and rotation for data enhancement. It also involves determining classification and bounding box prediction losses, penalty terms, and matching losses to learn the corresponding relationship between rib query items and rib regions in the medical image. The method aims to improve the accuracy and efficiency of rib detection in medical imaging, providing a comprehensive approach to rib segmentation and detection using advanced neural network models and self-attention mechanisms.
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