3D Volume Model for Ultrasound Simulation
Solution Overview
Problem
Current ultrasound imaging simulators for training are limited by the availability and cost of 3D datasets from real patients, particularly those with rare pathologies or dynamic conditions, and struggle to produce high-quality images due to finite data and restricted scanning windows and angles.
Innovation Solution
The method involves generating a 3D volume model of an organ using volume modeling techniques, allowing for the simulation of internal and external features, which can be animated and sliced to reproduce realistic ultrasound images across various imaging techniques, including non-invasive, semi-invasive, and invasive methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D datasets are obtained from real patient scanning, then training realism is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent creates virtual 3D models of organs that replicate the appearance and characteristics of real patient data without requiring actual patient scanning. These synthetic datasets serve as copies that maintain training value while eliminating time-consuming data acquisition processes.
Solution Approach 2:
The system generates its own training datasets through automated 3D modeling and rendering processes, eliminating the need to externally acquire data from patient scans. The virtual models self-generate the necessary training data with specific pathologies and anatomical variations.
2Manufacturing precision
If complete scans of rare pathology patients are performed, then dataset quality is improved, but patient availability and data accessibility worsen
Solution Approach 1:
The system creates virtual replicas of rare pathology cases that can be reproduced indefinitely. These synthetic datasets capture the essence of rare conditions without requiring actual patient participation, making rare pathologies accessible for training purposes.
Solution Approach 2:
The patent pre-generates comprehensive 3D models with various pathologies and scanning conditions before training needs arise. This allows instructors to access pre-prepared datasets of rare conditions without waiting for patient availability or performing time-consuming scans.
3Measurement precision
If multiple scanning windows and angles are used, then image quality is improved, but data requirements and system complexity increase
Solution Approach 1:
The virtual 3D model serves multiple functions: it can be scanned from any angle, any window, and any orientation without requiring additional physical equipment. A single virtual model replaces the need for multiple physical scanning setups, providing universal access to all viewing angles.
Solution Approach 2:
The patent transitions from 2D scan slices to a full 3D virtual model, enabling viewing from any angle and orientation. This dimensional enhancement allows unlimited scanning perspectives without requiring additional physical scanning devices or complex multi-angle acquisition systems.
4Adaptability or versatility
If more patient data is collected, then training variety is improved, but cost and time for data acquisition worsen
Solution Approach 1:
The system generates numerous variations of organ models with different pathologies, sizes, and anatomical features through virtual modeling. These synthetic copies provide diverse training scenarios without requiring proportional increases in actual patient data collection.
Solution Approach 2:
The patent varies parameters such as pathology type, organ size, density distribution, and anatomical variations within the virtual modeling process. By changing these parameters computationally, the system generates diverse training datasets without the time and cost of acquiring data from numerous different patients.
Data Source
AI summary
There is described a method for simulating an imaging process for an organ, the method comprising: retrieving from a memory a 3D volume model of the organ, the 3D volume model describing a 3D structure of the organ and a distribution of density within the 3D structure, the 3D structure representing a surface and internal features of the organ; generating a slice of the 3D model according to a position and an orientation of an imaging device, the slice including a cross-section of the surface and the internal features; rendering an image in accordance with the slice; and displaying the image.