Helical rowwise view weighting of computed tomographic images

• US 6,418,184 B1
• Filed: 12/29/2000
• Issued: 07/09/2002
• Est. Priority Date: 12/29/2000
• Status: Expired due to Fees

• Current Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Original Assignee: GE Medical Systems Global Technology Company LLC (GE Healthcare Technologies, Inc.)
• Inventors: Metz, Stephen W., Wang, Sharon X., Fusco, John A.
• Primary Examiner(s): BRUCE, DAVID VERNON
• Application Number:
  US09/752,275
• Time in Patent Office: 557 Days
• Field of Search: 378/4, 378/15, 378/901
• US Class Current: 378/15
• CPC Class Codes: A61B 6/027 characterised by the use of a particular data acquisition trajectory, e.g. helical or spiral
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/4085 Cone-beams
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

One aspect of the present invention is a method for reconstructing an image of an object utilizing a computed tomographic (CT) imaging system. The method includes steps of: helically scanning an object; interpolating an axial fan beam set of projection data as a vector function {right arrow over (R)}_a from a fan beam set of projection data from the helical scan {right arrow over (R)}_hi, where i=1, . . . , n is a row index and n represents a of number of rows of the detector array, using a relationship written as: ${\overrightarrow{R}}_a\left(\beta ,\gamma \right)=\sum _{i=1}^nw_i\left(\beta \right){\overrightarrow{R}}_{h_i}\left(\beta ,\gamma \right),$

where w_i(β) is a weighting function written as: $w_i=\sum _{j=1}^mf\left(\beta -{\beta }_j\right),$

where m is a number of images used for z smoothing, β_j is a gantry rotation angle for a plane of reconstrution of a jth image, and $f\left(x\right)=\{\begin{array}{cc}g\left(x\right),& x\le {\beta }_b\\ 0,& x>{\beta }_b\end{array}$

where constants ${\beta }_b=\frac{2\pi }{p},$

and g(x) is either a linear or non-linear function.

Claims

1. A method for reconstructing an image of an object utilizing a computed tomographic (CT) imaging system having a radiation source and a multislice detector array on a rotating gantry, the radiation source configured to project a beam of radiation through an object and towards the multislice detector array, the multislice detector array configured to sense attenuation of the radiation passing through the object;

said method comprising the steps of;

helically scanning an object with a computed tomographic imaging system to acquire a plurality of slices of projection data;

interpolating an axial fan beam set of projection data as a vector function {right arrow over (R)}_a from a fan beam set of projection data from the helical scan {right arrow over (R)}_hi, where i=1, . . . , n is a row index and n represents a of number of rows of the detector array, using a relationship written as;

${\stackrel{\to <br><br>}{R}}_a<br><br>\left(\mathrm{\beta <br><br>},\mathrm{\gamma <br><br>}\right)=\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>w_i<br><br>\left(\mathrm{\beta <br><br>}\right)<br><br>{\stackrel{\to <br><br>}{R}}_{h_i}<br><br>\left(\mathrm{\beta <br><br>},\mathrm{\gamma <br><br>}\right),$

where w_i(β

) is a weighting function written as;

$w_i=\underset{j=1}{\overset{m}{\sum <br><br>}}<br><br>f<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{\beta <br><br>}-{\mathrm{\beta <br><br>}}_j\right),$

where m is a number of images used for z smoothing,

β

_j is a gantry rotation angle for a plane of reconstrution of a jth image, and $f<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x\right)=\{\begin{array}{cc}g<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x\right),& <br><br>x<br><br>\le <br><br>{\mathrm{\beta <br><br>}}_b\\ 0,& <br><br>x<br><br>><br><br>{\mathrm{\beta <br><br>}}_b\end{array}$

where constants ${\mathrm{\beta <br><br>}}_b=\frac{2<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{\pi <br><br>}}{p},$

 

and g(x) is either a linear or non-linear function.

2. A method in accordance with claim 1 wherein g(x) is a linear function.

3. A method in accordance with claim 1 wherein g(x) is a nonlinear function.

4. A method in accordance with claim 1 wherein all views passing an image space defined by r_a=d_i/d_r are used for helical row weighting, where d_i is a width of an image space and d_r is a row thickness.

5. A method in accordance with claim 4 wherein a number of super views exceeds 2π

.

6. A method in accordance with claim 4 wherein said step of helically scanning comprises helically scanning at a helical pitch of p, and wherein a number of views v used for reconstruction is written:

$v=\frac{T}{p}<br><br>\left(r+r_a-1\right),$

where T is a detector sampling rate per rotation, and r is the number of detector rows.

7. A method for reconstructing an image of an object utilizing a computed tomographic (CT) imaging system having a radiation source and a multislice detector array on a rotating gantry, the radiation source configured to project a beam of radiation through an object and towards the multislice detector array, the multislice detector array configured to sense attenuation of the radiation passing through the object;

said method comprising the steps of;

helically scanning an object with a computed tomographic imaging system to acquire a plurality of slices of projection data;

rebinning the projection data to align and store helical scan data for view weighting;

generating a view weighting function;

looping, for each view and for each row of the multislice detector array, to retrieve and to view weight the helical scan data, and to write the weighted data to a buffer; and

reconstructing an image of the object using the weighted data.

8. A method in accordance with claim 7 wherein said step of generating a view weighting function comprises the steps of:

initializing a buffer for storing the weighting function;

generating a base weighting function f(z), where z is a distance from a scan data location to a plane of reconstruction;

calculating an offset for z-smoothing images; and

summing all weights with an offset h.

9. A method in accordance with claim 8 wherein view weighting the helical scan data comprises the steps of:

obtaining parameters for a view weighting function;

calculating a projection view number to determine a location to store the weighted data in the buffer; and

multiplying the helical scan data by the view weighting function.

10. A computed tomographic (CT) imaging system for reconstructing an image of an object, said computed tomographic (CT) imaging system comprising a radiation source and a multislice detector array on a rotating gantry, said radiation source configured to project a beam of radiation through an object and towards said multislice detector array, said multislice detector array configured to sense attenuation of said radiation beam passing through the object;

said imaging system configured to;

helically scan an object to acquire a plurality of slices of projection data;

interpolate an axial fan beam set of projection data as a vector flnction {right arrow over (R)}_a from a fan beam set of projection data from the helical scan {right arrow over (R)}_hi, where i=1, . . . , n is a row index and n represents a of number of rows of the detector array, using a relationship written as;

${\stackrel{\to <br><br>}{R}}_a<br><br>\left(\mathrm{\beta <br><br>},\mathrm{\gamma <br><br>}\right)=\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>w_i<br><br>\left(\mathrm{\beta <br><br>}\right)<br><br>{\stackrel{\to <br><br>}{R}}_{h_i}<br><br>\left(\mathrm{\beta <br><br>},\mathrm{\gamma <br><br>}\right),$

where w_i(β

) is a weighting function written as;

$w_i=\underset{j=1}{\overset{m}{\sum <br><br>}}<br><br>f<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(\mathrm{\beta <br><br>}-{\mathrm{\beta <br><br>}}_j\right),$

where m is a number of images used for z smoothing,

β

_j is a gantry rotation angle for a plane of reconstrution of a jth image, and $f<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x\right)=\{\begin{array}{cc}g<br><br>\text{\hspace{1em}<br><br>}<br><br>\left(x\right),& <br><br>x<br><br>\le <br><br>{\mathrm{\beta <br><br>}}_b\\ 0,& <br><br>x<br><br>><br><br>{\mathrm{\beta <br><br>}}_b\end{array}$

where constants ${\mathrm{\beta <br><br>}}_b=\frac{2<br><br>\text{\hspace{1em}<br><br>}<br><br>\mathrm{\pi <br><br>}}{p},$

 

and g(x) is either a linear or non-linear function.

11. An imaging system in accordance with claim 10 wherein g(x) is a linear function.

12. An imaging system in accordance with claim 10 wherein g(x) is a nonlinear function.

13. An imaging system in accordance with claim 10 configured to use all views passing an image space defined by r_a=d_i/d_r for helical row weighting, where d_i is a width of an image space and d_r is a row thickness.

14. An imaging system in accordance with claim 13 configured to utilize a number of super views exceeding 2π

.

15. An imaging system in accordance with claim 13 wherein to helical scan the object, said imaging system is configured to helically scan at a helical pitch of p, and said imaging system is configured to utilize a number of views v for reconstruction, where v is written:

$v=\frac{T}{p}<br><br>\left(r+r_a-1\right),$

where T is a detector sampling rate per rotation, and r is the number of detector rows.

16. A computed tomographic (CT) imaging system for reconstructing an image of an object, said computed tomographic (CT) imaging system comprises a radiation source and a multislice detector array on a rotating gantry, said radiation source configured to project a beam of radiation through an object and towards said multislice detector array, said multislice detector array configured to sense attenuation of said radiation passing through the object;

said imaging system configured to;

helically scan an object with a computed tomographic imaging system to acquire a plurality of slices of projection data;

rebin the projection data to align and store helical scan data for view weighting;

generate a view weighting function;

loop, for each view and for each row of the multislice detector array, to retrieve and to view weight the helical scan data, and to write the weighted data to a buffer; and

reconstruct an image of the object using the weighted data.

17. An imaging system in accordance with claim 16 wherein to generate a view weighting function, said imaging system is configured to:

initialize a buffer for storing the weighting function;

generate a base weighting function f(z), where z is a distance from a scan data location to a plane of reconstruction;

calculate an offset for z-smoothing images; and

sum all weights with an offset h.

18. An imaging system in accordance with claim 17 wherein to view weight the helical scan data, said imaging system is configured to:

obtain parameters for a view weighting function;

calculate a projection view number to determine a location to store the weighted data in the buffer; and

multiply the helical scan data by the view weighting function.