Unknown Organization (20240265645). LIVE SURGICAL AID FOR BRAIN TUMOR RESECTION USING AUGMENTED REALITY AND DEEP LEARNING simplified abstract
Contents
LIVE SURGICAL AID FOR BRAIN TUMOR RESECTION USING AUGMENTED REALITY AND DEEP LEARNING
Organization Name
Inventor(s)
Rayhan Papar of The Woodlands TX (US)
LIVE SURGICAL AID FOR BRAIN TUMOR RESECTION USING AUGMENTED REALITY AND DEEP LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240265645 titled 'LIVE SURGICAL AID FOR BRAIN TUMOR RESECTION USING AUGMENTED REALITY AND DEEP LEARNING
The abstract describes an augmented reality system and method that utilizes neural networks to automatically segment tumors and vasculature in medical scans, and generate an augmented reality display of physiological objects, tumors, and vasculature based on captured images.
- Memory stores 3D medical scans with tumor images and angiograms.
- Output port presents signals for augmented reality display.
- Camera captures images of physiological objects.
- Processor implements neural networks to segment tumors and vasculature, and recognize physiological objects.
- Generates augmented reality display of segmented objects compensated for changes in perspective.
Potential Applications: - Medical education and training for visualizing tumors and vasculature. - Surgical planning and navigation for precise tumor removal. - Telemedicine for remote consultations and collaboration on medical scans.
Problems Solved: - Automates tumor and vasculature segmentation for faster and more accurate analysis. - Enhances visualization of complex medical scans for improved understanding and decision-making.
Benefits: - Improved accuracy in tumor segmentation for better treatment planning. - Enhanced visualization of vasculature for safer surgical procedures. - Streamlined medical imaging analysis process for increased efficiency.
Commercial Applications: "Augmented Reality System for Medical Imaging Analysis: Revolutionizing Tumor Segmentation and Visualization"
Frequently Updated Research: Stay updated on advancements in neural networks for medical image analysis and augmented reality applications in healthcare.
Questions about Augmented Reality System for Medical Imaging Analysis: 1. How does the system compensate for changes in perspective when generating the augmented reality display? 2. What are the potential limitations of using neural networks for tumor segmentation in medical scans?
Original Abstract Submitted
an augmented reality system and method, comprising: a memory configured to store 3d medical scans comprising an image of a tumor and an angiogram; an output port configured to present a signal for presentation of an augmented reality display to a user; at least one camera, configured to capture images of a physiological object from a perspective; at least one processor, configured to: implement a first neural network trained to automatically segment the tumor; implement a second neural network to segment vasculature in proximity to the tumor; implement a third neural network to recognize a physiological object in the captured images; and generate an augmented reality display of the physiological object, tumor and vasculature based on the captured images, the segmented tumor and the segmented vasculature, compensated for changes in the perspective.
