Method for prior image constrained progressive image reconstruction
A method for reconstructing a high quality image from undersampled image data is provided. The image reconstruction method is applicable to a number of different imaging modalities. Specifically, the present invention provides an image reconstruction method that incorporates an appropriate prior image into an iterative image reconstruction process as well as utilizing an image frame from a previous time frame to constrain the reconstruction of a current image frame.
1. A method for reconstructing a time series of image frames of a subject with an imaging system, the steps comprising:
a) acquiring, with the imaging system, image data from the subject;
b) producing a prior image using the acquired image data;
c) producing a plurality of image frame estimates using the acquired image data and the prior image;
d) reconstructing a plurality of image frames using the prior image and the plurality of image frame estimates; and
e) iteratively repeating step d) until a stopping criterion is satisfied, wherein the plurality of image frame estimates are updated after each iteration.
2. The method as recited in claim 1 in which step d) includes calculating the difference between the image frame estimate from a current time frame and the image frame estimate from a previous time frame.
3. The method as recited in claim 1 in which step b) includes reconstructing a plurality of initial image frames and producing the prior image by averaging the plurality of initial image frames.
4. The method as recited in claim 1 in which the imaging system is at least one of an x-ray fluoroscopy imaging system, a C-arm x-ray imaging system, a magnetic resonance imaging (MRI) system, and an interventional MRI system.
5. The method as recited in claim 1 in which step c) includes performing an algebraic reconstruction technique (ART).
6. The method as recited in claim 1 in which step d) includes minimizing an objective function of the form:
Ψ
1
(
I
_
-
I
P
)
1
+
α
Ψ
2
I
t
1
+
β
∑
t
=
2
N
Ψ
3
(
I
t
-
I
t
-
1
)
1
wherein:
Ψ 1 =a first sparsifying transform;
Ψ 2 =a second sparsifying transform;
Ψ 3 =a third sparsifying transform;
Ī=an average of the plurality of image frame estimates;
I p =the prior image;
α=a first regularization parameter;
I t =an image frame estimate for a current time frame;
β=a second regularization parameter; and
I t−1 =an image frame estimate for a previous time frame.
7. A method for reconstructing an image of a subject with an imaging system, the steps comprising:
a) acquiring, with the imaging system, image data from the subject;
b) producing a prior image of the subject using the acquired image data;
c) producing, using the acquired image data and the prior image, a current image frame estimate corresponding to a current time frame;
d) selecting a new time frame and storing the current image frame estimate as a previous image frame estimate;
e) repeating step c) to produce the current image frame estimate corresponding to the new time frame; and
f) reconstructing an image frame corresponding to the new time frame using the previous image frame estimate, the new current image frame estimate, and the prior image.
8. The method as recited in claim 7 in which steps d)-f) are repeated to produce a plurality of image frames corresponding to a plurality of time frames.
9. The method as recited in claim 7 in which step b) includes reconstructing a plurality of initial image frames and producing the prior image by averaging the plurality of initial image frames.
10. The method as recited in claim 7 in which step c) includes performing an algebraic reconstruction technique (ART).
11. The method as recited in claim 7 in which the imaging system is at least one of an x-ray fluoroscopy imaging system, a C-arm x-ray imaging system, a magnetic resonance imaging (MRI) system, and an interventional MRI system.