Systems and methods for processing real-time video from medical image device and detecting objects in video

A real-time video and medical imaging technology, applied in the field of neural network and network, can solve the problem of difficult real-time application of the system, and achieve the effect of good specialization, high accuracy and efficiency

Pending Publication Date: 2021-03-26
科斯默人工智能 AI有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, these systems are often difficult to implement in the required real-time manner

Method used

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  • Systems and methods for processing real-time video from medical image device and detecting objects in video
  • Systems and methods for processing real-time video from medical image device and detecting objects in video
  • Systems and methods for processing real-time video from medical image device and detecting objects in video

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Embodiment Construction

[0032] The disclosed embodiments relate to computer-implemented systems and methods for training and using generative adversarial networks. Advantageously, the exemplary embodiments may provide improved training networks and fast and efficient object detection. Embodiments of the present disclosure may also provide improved object detection with reduced false positives for medical image analysis.

[0033]Embodiments of the present disclosure can be implemented and used in a variety of applications and vision systems. For example, embodiments of the present disclosure may be implemented for medical image analysis systems and other types of systems that benefit from object detection where objects may be true positives or false positives. Although embodiments of the present disclosure are generally described herein with reference to medical image analysis and endoscopy, it should be understood that the embodiments are also applicable to other medical imaging procedures such as g...

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PUM

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Abstract

The present disclosure relates to systems and methods for processing real-time video and detecting objects in the video. In one implementation, a system is provided that includes an input port for receiving real-time video obtained from a medical image device, a first bus for transferring the received real-time video, and at least one processor configured to receive the real-time video from the first bus, perform object detection by applying a trained neural network on frames of the received real-time video, and overlay a border indicating a location of at least one detected object in the frames. The system also includes a second bus for receiving the video with the overlaid border, an output port for outputting the video with the overlaid border from the second bus to an external display,and a third bus for directly transmitting the received real-time video to the output port.

Description

technical field [0001] The present disclosure relates generally to the field of neural networks and to the use of such networks for image analysis and object detection. More specifically, but not limitation, the present disclosure relates to computer-implemented systems and methods for training generative adversarial networks and processing real-time video. The systems, methods, and trained neural networks disclosed herein can be used in various applications and vision systems, such as medical image analysis and systems that benefit from accurate object detection capabilities. Background technique [0002] In many object detection systems, objects are detected in images. Objects of interest can be people, places, or things. Localization of objects is also important in applications such as medical image analysis and diagnosis. However, computer-implemented systems utilizing image classifiers typically cannot recognize or provide the location of detected objects. Therefore...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04A61B1/00A61B1/31
CPCG06T2207/30004A61B1/31A61B1/041A61B1/00045A61B1/2736G06V20/40G06V2201/03G06V10/82A61B1/000094A61B1/000095A61B1/000096G06N3/045G06T7/0012G06N3/08G06T11/60G06T2207/20084G06T7/70G06T11/001G06T2207/30032G16H30/20G06T2207/30096G06T2207/10016A61B1/00009G16H50/20A61B5/7264A61B1/00055G06F18/214G06T11/203G06T2207/10068G06V20/49G06V2201/032A61B5/7267G06T2207/30064G06V10/25G06V10/255
Inventor N·吴丁朱利奥·伊万吉利斯提弗拉维奥·纳瓦里
Owner 科斯默人工智能 AI有限公司
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