Learn about EndoSoft® Patents Below

Patent Date – 03-23-2021

An artificial intelligence (AI) platform, method and program product for detecting and sizing a lesion in real time during a clinical procedure. An AI platform is disclosed that includes: a trained classifier that includes a deep learning model trained to detect lesions and reference objects in image data; a real time video analysis system that receives a video feed during a clinical procedure, uses the trained classifier to determine if a video frame from the video feed has both a lesion and a reference object, calculates an actual size of the lesion based on a pixel size of both the lesion and the reference object, and outputs an indication that the lesion was detected and the actual size of the lesion.

Patent Date – 03-05-2024

An AI based platform for processing information collected during a medical procedure. A method includes capturing images and speech during a medical procedure; processing the images using a trained classifier to identify image-based quality-of-care indicators (QIs); converting the speech into text; parsing the text into sentences; performing a search and replace on predefined text patterns in the sentences; identifying text-based QIs in the sentences; classifying sentences into sentence types using a trained model; updating sentences by integrating the image-based QIs with text-based QIs; and outputting structured data that includes sentences organized by sentence type.

Patent Date – 02-11-2025

An AI based system and method for processing and querying files. A method of processing files for an artificial intelligence (AI) querying service includes: hierarchically parsing the files into a set of hierarchically connected data chunks; generating metadata for each of the hierarchically connected data chunks, wherein the metadata includes hierarchical information; processing the hierarchically connected data chunks and metadata with an embedding model to generate vector embeddings that include the hierarchical information; generating textual summaries from the hierarchically connected data chunks; and storing the vector embeddings, textual summaries, and hierarchically connected data chunks for the AI querying service.

Patent Date – 02-25-2025

A system and method for processing a video stream captured during a clinical procedure. A method includes: receiving and forwarding a current frame to a display using a first processing thread; forwarding the current frame to a memory buffer; using a second processing thread to check for a new frame in the memory buffer; using the second processing thread to forward the new frame to a cloud service that detects lesions in image data; receiving a result from the cloud service; in response to the result being indicative of a new detected lesion in the new frame, performing object sizing using the second processing thread and forwarding new lesion information to the first processing thread; and graphically overlaying the new lesion information onto the current frame at the display manager.

Patent Date – 05-14-2025

The patented system consists of three main parts, training the model, real-time analysis and a sizing algorithm. Training the model learns using labeled reference images so that the software can easily understand the different kinds of lesions. With a model created, the software is then able to provide real-time analysis of endoscopy footage, highlighting any lesions that are detected from the model by placing a box around the lesion. With additional reference to common endoscopy tools, forceps and snare that are used to extract lesion, polyps can be sized accurately using the tools as a size reference. Sizes of lesions are calculated using pixels from the video feed and displayed on screen in real-time.  

Patent Date – 09-09-2025

An AI based platform for processing information collected during a medical procedure. A method includes capturing images and speech during a medical procedure; processing the images using a trained classifier to identify image-based quality-of-care indicators (QIs); converting the speech into text; parsing the text into sentences; performing a search and replace on predefined text patterns in the sentences; identifying text-based QIs in the sentences; classifying sentences into sentence types using a trained model; updating sentences by integrating the image-based QIs with text-based QIs; and outputting structured data that includes sentences organized by sentence type.