Three Material Decomposition using a Triple-Layer Flat-Panel Detector

Case ID:
C17541

Value Proposition:

  • Method for direct, real-time visualization of bone, water, and iodine contrast agents.
  • Allows for better visualization of moving structures; reduces imaging artifacts induced by motion (i.e. beating heart)

 Technology Description

  • Researchers at Johns Hopkins have developed a method for fast processing of data acquired using a triple-layer flat-panel detector (TL-FPD) for enhanced visualization and interpretation of radiographic or fluoroscopy images.
  • This technology includes a machine learning model for decomposition of imaging data into bone, water, or iodine.

Unmet Need

  • Current methods for standard radiography and fluoroscopy presents overlapping anatomy, which obsures visualization of critical features. Additionally, contrast agent is not sufficient 
  •  Spectral radiography acquisition via dual-energy imaging are unable to fully separate iodine contrast agents from calcium.
  • Additionally, current contrast visualization methods, such as digital subtraction angiography (DSA), are sensitive to motion and can lead to artifacts that confound image processing.
  • Triple layer detector is a promising acquistion strategy to address these issues but requires an accurate, real-time (for angiography applications) processing algorithm for material decomposition 

Stage of Development

  • Machine-learning model for image processing was developed for fast, accurate material decomposition of data acquired with a triple layer flat panel detector
  • Looking for partners to commercialize the technology for integration into radiographic or fluoroscopy-based diagnostic and interventional imaging.

 Data Availability

  • Data available upon request.

Publication

N/A

Patent Information:
Title App Type Country Serial No. Patent No. File Date Issued Date Expire Date Patent Status
MACHINE LEARNING SYSTEMS AND RELATED ASPECTS FOR THREE MATERIAL DECOMPOSITION USING A TRIPLE-LAYER FLAT-PANEL DETECTOR PCT: Patent Cooperation Treaty PCT PCT/US2023/035371   10/18/2023     Pending
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For Information, Contact:
Lisa Schwier
lschwie2@jhu.edu
410-614-0300
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