Quantitative endoscopy

• US 9,138,597 B2
• Filed: 05/13/2010
• Issued: 09/22/2015
• Est. Priority Date: 05/14/2009
• Status: Active Grant

• Current Assignee: University Health Network
• Original Assignee: University Health Network
• Inventors: Weersink, Robert, Hope, Andrew, Siewerdsen, Jeff, Jaffray, David, Kashigar, Aidin, Daly, Michael, Cho, John, Eubank, Jonathon
• Primary Examiner(s): Akhavannik, Hadi
• Application Number:
  US13/320,375
• Publication Number:
  US 20120155731A1
• Time in Patent Office: 1,958 Days
• Field of Search: 382/100, 382128-132, 600/101, 600/109, 600/112, 600/114, 600/117, 600/118, 600/139, 600/145, 600/173, 600/420, 600/424, 600/427, 600/437, 600/415, 600/416, 600/562, 600/587, 606/1, 606/45, 606/130, 700/57, 700/245, 703/2, 703/6, 703/11, 345/420, 345/427, 345/424, 345/629, 345/630
• US Class Current: 1/1
• CPC Class Codes: A61N 5/103 Treatment planning systems
• CPC Class Codes: A61N 5/1039 using functional images, e.g. PET or MRI
• CPC Class Codes: G06T 2207/10068 Endoscopic image
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/344 involving models
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing

Abstract

A method, computer program product and processor for quantitatively registering a 2D endoscopic ROI in a 3D volumetric imaging dataset. An endoscopic dataset and a volumetric imaging are registered to a common coordinate system. A 2D endoscopic ROI is generated within the endoscopic imaging dataset. A 3D surface ROI is generated within the volumetric imaging dataset corresponding to the 2D endoscopic ROI, based on a projection of the 2D endoscopic ROI to the registered common coordinate system.

Claims

1. A method for quantitatively registering a 2D endoscopic region of interest (ROI) in a 3D volumetric imaging dataset, the method comprising:

receiving signals representing the volumetric imaging dataset;

receiving signals representing an endoscopic dataset from an endoscope, the endoscopic dataset including an endoscopic imaging dataset and a tracking dataset, the tracking dataset including information about the position and orientation of the endoscope;

wherein coordinates of the endoscopic dataset and coordinates of the volumetric imaging dataset are registered to a common coordinate system;

receiving a definition of the 2D endoscopic ROI within the endoscopic imaging dataset, the 2D endoscopic ROI being outlined on a 2D endoscopic image by a 2D contour generated based on clinical examination;

generating a 3D surface ROI within the volumetric imaging dataset corresponding to the 2D endoscopic ROI, based on a projection of the 2D endoscopic ROI to the registered common coordinate system; and

transmitting signals representing the generated 3D surface ROI for treatment planning.

2. The method of claim 1 further comprising:

generating the 2D contour of the 2D endoscopic ROI by defining points within the contour.

3. The method of claim 1 further comprising:

registering the volumetric imaging dataset to the common coordinate system using reference markers.

4. The method of claim 3 wherein the reference markers are fiducial markers or anatomical features.

5. The method of claim 1 further comprising:

registering the volumetric imaging dataset to the common coordinate system using a 3D model based on the endoscopic imaging dataset.

6. The method of claim 1 further comprising:

displaying the 3D surface ROI superimposed on a 3D image generated from the volumetric imaging dataset.

7. The method of claim 1 wherein the common coordinate system is one of:

a real world coordinate system, an endoscopic coordinate system of the endoscopic dataset, and a volumetric coordinate system of the volumetric imaging dataset.

8. The method of claim 1 wherein the volumetric imaging dataset is one of:

a computer tomography (CT) imaging dataset, a magnetic resonance (MR) imaging dataset, and a positron emission tomography (PET) imaging dataset.

9. The method of claim 1 wherein the endoscopic dataset is one of:

a fluorescence endoscopic dataset, an endoscopic ultrasound dataset, a surgical endoscopic dataset, a white light endoscopic dataset, and a narrow-band endoscopic dataset.

10. A non-transitory computer readable medium comprising computer executable instructions embodied therein that when executed by at least one processor, cause the at least one processor to carry out the method of claim 1.

11. A computer system comprising at least one processor coupled to a non-transitory computer readable medium, the non-transitory computer readable medium comprising computer executable instructions embodied therein that when executed by the at least one processor cause the at least one processor to carry out the method of claim 1.