Efficient cardiac MR workflows based on automated planning from mDIXON surveys

• US 9,324,150 B2
• Filed: 07/17/2013
• Issued: 04/26/2016
• Est. Priority Date: 07/18/2012
• Status: Active Grant

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips N.V.
• Inventors: Hautvast, Guillaume Leopold Theodorus Frederik, De Kok-Strijbos, Wendy
• Primary Examiner(s): AZARIAN, SEYED H
• Application Number:
  US14/414,635
• Publication Number:
  US 20150193921A1
• Time in Patent Office: 1,014 Days
• Field of Search: 382/100, 382/103, 382106-107, 382128-134, 382/162, 382/168, 382/173, 382/181, 382/199, 382/203, 382/209, 382/219, 382/232, 382/254, 382/274, 382/276, 382286-291, 382/305, 382/312, 378/4, 378/21, 324/309
• US Class Current: 1/1
• CPC Class Codes: G01R 33/4828 Resolving the MR signals of different chemical species, e.g. water-fat imaging
• CPC Class Codes: G01R 33/543 Control of the operation of the MR system, e.g. setting of acquisition parameters prior to or during MR data acquisition, dynamic shimming, use of one or more scout images for scan plane prescription G01R33/546 takes precedence
• CPC Class Codes: G01R 33/5608 Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels image data processing or generation, in general G06T
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30048 Heart; Cardiac
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80

Abstract

A system (10) for planning cardiac MRI views, said system (10) includes a planning device (16) which includes at least one processor (42) programmed to: receive one or more images (18) from an imaging device (12) acquired utilizing an mDIX-ON protocol, determine a position and orientation of an object of interest from the one or more images, transform a model of the object of interest such that is matches the object of interest with a generalized Hough transform, and generate one or more object of interest views from the matching of the object of interest, A display (48) displays the one or more object of interest views.

Claims

1. A system for planning cardiac MRI views, said system comprising:

at least one processor programmed to;

utilize an mDixon protocol scan sequence;

receive one or more images including an object of interest acquired from the mDIXON protocol scan sequence wherein the one or more received images include a water image and a fat image of the object of interest;

determine a position and orientation of the object of interest from the one or more images including identify edges of the object of interest by detecting transitions in gradient magnitude in the received one or more images, wherein the transitions provide a segmentation of the object of interest which is refined with non-maximum suppression;

match a model of the object of interest to the position and orientation of the object of interest;

generate one or more views of the object of interest from the matching of the object of interest; and

display the one or more views of the object of interest on a display device.

2. The system according to claim 1, wherein the object of interest is a heart and the views include at least one of a short axis (SA) view, long axis (LA) two chamber (2CH) view, LA three chamber (3CH) view and a LA four chamber (4CH) view.

3. The system according to claim 1, wherein the model of the object of interest is matched to the position and orientation of the object of interest by operations including transforming the model of the object of interest such that the transformed model matches the edges of the object of interest with a generalized Hough transform.

4. The system according to claim 1, wherein the fat image provides a global location of the object of interest and the water image provides a location and orientation of the object of interest.

5. A method for planning cardiac MRI views, said method comprising:

utilizing an mDixon protocol scan sequence;

receiving one or more images including an object of interest acquired from the mDIXON protocol scan sequence wherein the one or more received images include a water image and a fat image of the object of interest;

determining a position and orientation of the object of interest from the one or more images including;

identifying edges of the object of interest by detecting transitions in gradient magnitude in the received one or more images, wherein the transitions provide a segmentation of the object of interest which is refined with non-maximum suppression;

matching a model of the object of interest to the position and orientation of the object of interest;

generating one or more object of interest views from the matching of the object of interest; and

displaying the one or more object of interest views on a display device.

6. The method according to claim 5, wherein the object of interest is the heart and the views include at least one of a short axis (SA) view, long axis (LA) two chamber (2CH) view, LA three chamber (3CH) view and a LA four chamber (4CH) view.

7. The method according to 5, further including:

transforming the model of the object of interest such that is matches the edges of the object of interest with a generalized Hough transform.

8. The method according to claim 5, further including:

providing a global location of the object of interest from a fat image; and

providing a location and orientation of the object of interest from the water image.

9. The method according to claim 5, further including:

administering at least one of a contrast bolus for viability imaging and a long half-life stress agent for stress imaging.

10. The method according to claim 9, wherein the step of administering is performed prior to acquiring the one or more received images and outside a magnetic resonance examination room.

11. A non-transitory computer readable medium carrying software which controls one or more processors to perform the method according to claim 5.

12. A system for planning cardiac MRI views, said system comprising:

a planning device which includes at least one processor programmed to;

receive one or more images from an imaging device acquired in a single breath hold utilizing a cardiac gated mDIXON protocol wherein the one or more received images include a water image and a fat image of the object of interest;

determine a position and orientation of an object of interest from the one or more images including identifying edges of the object of interest by detecting transitions in gradient magnitude in the received one or more images, wherein the transitions provide a segmentation of the object of interest which is refined with non-maximum suppression;

transform a model of the object of interest such that is matches the object of interest using a generalized Hough transform;

generate one or more cardiac views from the matching of the object of interest; and

a display which displays the one or more cardiac views.

13. The system according to claim 12, wherein the cardiac views include at least one of a short axis (SA) view, long axis (LA) two chamber (2CH) view, LA three chamber (3CH) view and a LA four chamber (4CH) view.

14. The system according to claim 12, wherein the fat image provides a global location of the object of interest and the water image provides a location and orientation of the object of interest.