View source for 20240020860. METHOD AND APPARATUS OF FUSION OF MULTIMODAL IMAGES TO FLUOROSCOPIC IMAGES simplified abstract (ACREW Imaging, Inc.)

=METHOD AND APPARATUS OF FUSION OF MULTIMODAL IMAGES TO FLUOROSCOPIC IMAGES=


==Organization Name==

[[:Category:ACREW Imaging, Inc.|ACREW Imaging, Inc.]]


[[Category:ACREW Imaging, Inc.]]

==Inventor(s)==

[[:Category:William Plishker of Ocean View DE (US)|William Plishker of Ocean View DE (US)]][[Category:William Plishker of Ocean View DE (US)]]

[[:Category:Craig Hughes of Ocean View DE (US)|Craig Hughes of Ocean View DE (US)]][[Category:Craig Hughes of Ocean View DE (US)]]

==METHOD AND APPARATUS OF FUSION OF MULTIMODAL IMAGES TO FLUOROSCOPIC IMAGES - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240020860 titled 'METHOD AND APPARATUS OF FUSION OF MULTIMODAL IMAGES TO FLUOROSCOPIC IMAGES

==Simplified Explanation==

The present invention is a device that transforms 3D image data to align with a 2D fluoroscopic image. This process is called image registration, which finds the transform that aligns the features of the 3D image with the 2D image. The fluoroscopic image registration process uses a multistage framework to progressively refine the registration result. The core registration engine creates a candidate transform, creates a digitally reconstructed radiograph using the transform, compares it to the fluoroscopic image, and either ends or constructs a new candidate transform. Similarity measurement of a candidate transform is based on intensities and relevant custom data.

* The invention is a device for transforming 3D image data to align with a 2D fluoroscopic image.
* The device uses a multistage framework to progressively refine the registration result.
* The core registration engine creates a candidate transform and compares it to the fluoroscopic image.
* The device iteratively searches the parameter space defined by each stage to find the best transform.
* Similarity measurement of a candidate transform is based on intensities and custom data relevant to the registration scenario.

Potential applications of this technology:

* Medical imaging: This technology can be used in medical imaging to align 3D image data with 2D fluoroscopic images, aiding in surgical planning and guidance.
* Industrial inspection: The device can be used in industrial settings to align 3D scans with 2D images for quality control and inspection purposes.
* Virtual reality: This technology can be applied in virtual reality applications to align virtual objects with real-world images or videos, enhancing the immersive experience.

Problems solved by this technology:

* Alignment accuracy: The device solves the problem of aligning 3D image data with 2D fluoroscopic images accurately, ensuring precise registration.
* Time efficiency: The multistage framework and iterative search process improve the efficiency of the registration process, reducing the time required for alignment.
* Customizability: The device allows for the incorporation of custom data relevant to the registration scenario, enabling tailored alignment for specific applications.

Benefits of this technology:

* Improved surgical planning and guidance: The accurate alignment of 3D image data with fluoroscopic images enhances surgical planning and guidance, leading to better outcomes and reduced risks.
* Enhanced quality control: In industrial settings, the alignment of 3D scans with 2D images improves quality control processes, ensuring product integrity and reducing defects.
* Immersive virtual reality experiences: By aligning virtual objects with real-world images or videos, this technology enhances the immersion and realism of virtual reality experiences.


==Original Abstract Submitted==

the present invention includes a device for transforming 3d image data such that the transformed image aligns with a 2d fluoroscopic image. the process of finding the transform that aligns the features of the 3d image with the 2d image is called image registration. the fluoroscopic image registration process has at its core a multistage framework that progressively refines a registration result. each stage leverages the fluoroscopic registration engine which iteratively searches the parameter space defined by the stage. the core registration engine creates a candidate transform, uses it to create a digitally reconstructed radiograph, then compares that to the supplied fluoroscopic image, and the iterative alignment engine either ends or uses it to construct a new candidate transform. similarity measurement of a candidate transform is based on intensities and any custom data relevant to the registration scenario.



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