Image Reconstruction System for ROI-Based Processing

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Imaging devices with longer axial field of view (AFOV) generate excessive image data, including irrelevant regions, leading to increased radiation dose, storage redundancy, and decreased speed and accuracy in image processing for medical diagnosis.

Innovation Solution

A system that determines regions of interest (ROIs) within the image data, reconstructs target portions corresponding to these ROIs, and performs attenuation corrections to generate accurate and efficient images, reducing unnecessary data processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If image data from the entire axial field of view is processed, then complete coverage of the object is achieved, but processing time and computational resources increase significantly

Engineering Contradiction:
Improveimage reconstruction accuracyVSAvoidimage processing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent divides the full axial field of view into multiple regions of interest (ROIs) based on anatomical structures or clinical requirements. Only the selected ROI data is reconstructed and processed, while other regions are excluded. This segmentation approach maintains diagnostic accuracy for the region of interest while dramatically reducing the volume of data that requires processing, thereby resolving the contradiction between complete coverage and processing efficiency.

Inventive Principle:
Principle #1Segmentation

2Reliability

If image data from the entire axial field of view is stored, then all imaging information is preserved, but storage redundancy increases

Engineering Contradiction:
Improvedata completenessVSAvoiddata storage volume
Core Design Contradiction:
ReliabilityVSQuantity of substance

Solution Approach 1:

The patent extracts and selects only the relevant region of interest from the complete axial field of view data. By taking out the unnecessary data portions that do not contribute to the diagnostic goal, the system preserves the essential diagnostic information while eliminating storage redundancy. This extraction principle allows the system to maintain data reliability for the required region while significantly reducing the total data volume that needs to be stored.

Inventive Principle:
Principle #2Taking out (Extraction)

3Area of stationary object

If the entire axial field of view is scanned, then comprehensive imaging coverage is obtained, but radiation dose to the patient increases

Engineering Contradiction:
Improveimaging coverage areaVSAvoidradiation dose
Core Design Contradiction:
Area of stationary objectVSObject-affected harmful factors

Solution Approach 1:

The patent applies local quality by concentrating the imaging resources and radiation exposure only on the specific region of interest that requires diagnostic evaluation. Instead of uniformly scanning the entire axial field of view, the system tailors the scan coverage to match the clinical question or anatomical region of concern. This localized approach maintains adequate imaging coverage for diagnostic purposes while minimizing unnecessary radiation exposure to other body parts.

Inventive Principle:
Principle #3Local quality

Data Source

PatentUS12165328B2Systems and methods for image reconstruction and processing
Publication Date: 2024.12.10 SHANGHAI UNITED IMAGING HEALTHCARE
  • US12165328B2 patent drawing
  • US12165328B2 patent drawing
  • US12165328B2 patent drawing

AI summary

The present disclosure provides a system and method for image reconstruction and processing. The method may include obtaining image data of an object acquired by an imaging device. The method may include determining one or more regions of interest (ROIs) of the object. The method may also include determining, based on each ROI of the one or more ROIs, a target portion of the image data corresponding to the ROI among the image data. The method may further include reconstructing, based on the target portion of the image data, one or more images of the ROI.