CMR Surgical has been granted a patent for a method of real-time image correction in a surgical robotic system. The method involves identifying different regions in a video stream from a surgical endoscope, applying a region-specific modification to each region using a mask, deriving data from the robotic system, determining the relationship between features in the image, modifying the mask based on the predicted relationship for the next image, and applying the modified mask to the subsequent image. GlobalData’s report on CMR Surgical 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 CMR Surgical, Surgical robots was a key innovation area identified from patents. CMR Surgical's grant share as of September 2023 was 38%. Grant share is based on the ratio of number of grants to total number of patents.
Real-time image correction of surgical endoscope video stream
A recently granted patent (Publication Number: US11771302B2) describes a method for real-time image correction of a video stream from a surgical endoscope in a surgical robotic system. The method involves identifying different regions within the video stream and applying region-specific modifications to each region using a mask. The modifications can include adjustments to image properties such as brightness, contrast, gamma, and color.
The method also involves deriving data from the surgical robotic system and determining a relationship between features in the image based on this data. The mask is then modified based on the predicted relationship between features in subsequent images of the video stream. The modified mask is applied to the subsequent image to correct any changes in the image properties.
The patent also mentions the option of storing a set of predetermined modifications and generating each region-specific modification as a weighted combination of these predetermined modifications. This allows for more flexibility in adjusting the image properties based on the specific needs of each region.
The derived data from the surgical robotic system can include information such as the position of the surgical endoscope relative to other features in the image, depth information of the features, and identification of features in the image. The depth information can be derived from the movement of the surgical endoscope or from a combination of two stereo video channels of the endoscope.
The method also includes tracking the surgeon's focus and applying different region-specific modifications to regions centered on the surgeon's focus and regions excluding the focus. Additionally, feature-specific modifications can be applied to selected regions based on identified features in the image.
The patent further describes the application of an iteratively updated mask to further images of the video stream. This involves deriving further data from the surgical robotic system, determining an updated relationship between features in a new image, modifying the mask based on the updated relationship, and applying the updated mask to the new image. The mask can be updated at a slower rate than the image frame rate and only upon gross changes or movement of the features in the image or the surgical endoscope.
Overall, this patented method provides a real-time image correction technique for surgical endoscope video streams, allowing for improved visualization and accuracy during surgical procedures.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
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.
