A Novel Method of Visualizing Three-Dimensional Image Datasets

University of Pittsburgh researchers have developed a novel method for visualizing C mode images on three-dimensional (3D) image datasets. This technique optimizes the visualization of target tissues by adopting the natural curvature of the tissue or region of interest, thereby eliminating artifacts and distortions caused by body motion during scanning. This method enhances the accuracy and reliability of 3D imaging modalities such as MRI, CAT scan, ultrasound, and optical coherence tomography (OCT).

Description

The invention is a novel method of visualizing C mode images on any 3D image dataset (OCT, SOCT, MRI, CT, Ultrasound etc.) by adopting the natural curvature of tissue or region of interest. To achieve this goal, the inventors use both automated segmentation and manually configured contour models (but mathematically interpolated using Spline interpolation) methods. Users can set 3D model lines for a plane where C mode image sampling occurs. As a result, the C mode image shows only the targettissue of interest eliminating artifacts and distortions from the image.

Applications

• MRI
• CAT scan
• Ultrasound
• Optical coherence tomography (OCT)
• Any type of three-dimensional image dataset

Advantages

This method eliminates unwanted artifacts and distortions from C mode images, making interpretation much easier for clinicians. It also allows for the visualization of previously undocumented anatomical features with a highly tissue-adapted sampling method. The technique improves the accuracy and reliability of 3D imaging, enhancing clinical decision-making.

Invention Readiness

The invention prototype has been fully developed and is currently working in a clinical setting. Clinical in vivo sample data is being gathered, and a clinical trial to determine its usefulness has already been approved by the Institutional Review Board (IRB).

IP Status

https://patents.google.com/patent/WO2009015295A1