Method and system for multi-detector-row computed tomography utilizing projection data up-sampling with shift
View Patent ↗A computed tomography apparatus and method where data is upsampled with shifting to produce upsampled data. The data is shifted up and down in the same amount in the z-direction, and then upsampled through interpolation. An image is reconstructed using the upsampled data. The process is preferably performed column-by-column. An upsampling shift and interpolation kernel size can be adaptive to the data z-gradient.
1. A computed-tomography apparatus, comprising:
an x-ray source;
an x-ray detector disposed to receive x-rays from said x-ray source;
a data collection unit; and
a processing unit for performing upsampling with shifting on data collected by said data collection unit to produce upsampled data, and for reconstructing an image using said upsampled data, wherein said processing unit is configured to perform said upsampling using:
Out
[
seg
·
K
+
k
]
=
In
[
seg
-
1
]
·
a
(
-
1
,
k
)
+
In
[
seg
]
·
a
(
0
,
k
)
+
In
[
seg
+
1
]
·
a
(
1
,
k
)
=
∑
j
=
-
1
1
In
[
seg
+
j
]
·
a
(
j
,
k
)
where:
a(j, k) is the contribution of each of three input data samples,
“In” is an input data column,
“Out” is an output upsampled data column,
seg is a segment (detector row) index, 0≦seg≦Nseg, where Nseg is a number of detector rows in said detector,
K is an upsampling factor, K=2, 4, . . . ,
k is an local upsampled segment index, 0≦k≦K, and
j is a local interpolation segment index, j=−1, 0, 1.
2. The apparatus as recited in claim 1 , wherein a(j, k) is a weight coefficient and said weights are determined as
a ( j,k )= h ( j−s ),
where h(j−s) is a interpolation kernel defined by
h
(
j
,
L
)
=
{
L
-
j
,
-
L
<
j
<
L
0
,
otherwise
.
and parameter s is found by:
s
=
k
-
K
-
1
2
K
=
2
k
-
K
+
1
2
K
.
3. A computed tomography method, comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, wherein said upsampling with shift comprises:
Out
[
seg
·
K
+
k
]
=
In
[
seg
-
1
]
·
a
(
-
1
,
k
)
+
In
[
seg
]
·
a
(
0
,
k
)
+
In
[
seg
+
1
]
·
a
(
1
,
k
)
=
∑
j
=
-
1
1
In
[
seg
+
j
]
·
a
(
j
,
k
)
where:
a(j, k) is the contribution of each of three input data samples,
“In” is an input data column,
“Out” is an output upsampled data column,
seg is a segment (detector row) index, 0≦seg≦Nseg, where Nseg is a number of detector rows in said detector,
K is an upsampling factor, K=2, 4, . . . ,
k is an local upsampled segment index, 0≦k≦K, and
j is a local interpolation segment index, j=−1, 0, 1.
4. The method as recited in claim 3 , wherein a(j,k) is a weight coefficient and said weights are determined as
a ( j,k )= h ( j−s ),
where h(j−s) is a interpolation kernel defined by
h
(
j
,
L
)
=
{
L
-
j
,
-
L
<
j
<
L
0
,
otherwise
,
and parameter s is found by:
s
=
k
-
K
-
1
2
K
=
2
k
-
K
+
1
2
K
.
5. A computed tomography method, comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, wherein said upsampling increases a number of detector rows by 1.
6. A computed tomography method, comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, the method further comprising:
using an interpolation kernel in said upsampling; and
adaptively changing a size of said kernel.
7. A computed tomography method, comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, the method further comprising:
varying a shift amount used in said upsampling.
8. A non-transitory computer-readable medium that stores instructions that when executed by a computer, cause the computer to perform a method comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, wherein said upsampling with shift comprises:
Out
[
seg
·
K
+
k
]
=
In
[
seg
-
1
]
·
a
(
-
1
,
k
)
+
In
[
seg
]
·
a
(
0
,
k
)
+
In
[
seg
+
1
]
·
a
(
1
,
k
)
=
∑
j
=
-
1
1
In
[
seg
+
j
]
·
a
(
j
,
k
)
where:
a(j, k) is the contribution of each of three input data samples,
“In” is an input data column,
“Out” is an output upsampled data column,
seg is a segment (detector row) index, 0≦seg≦Nseg, where Nseg is a number of detector rows in said detector,
K is an upsampling factor, K=2, 4, . . . ,
k is an local upsampled segment index, 0≦k≦K, and
j is a local interpolation segment index, j=−1, 0, 1.
9. The medium as recited in claim 8 , wherein a(j, k) is a weight coefficient and said weights are determined as
a ( j,k )= h ( j−s ),
where h(j−s) is a interpolation kernel defined by
h
(
j
,
L
)
=
{
L
-
j
,
-
L
<
j
<
L
0
,
otherwise
,
and parameter s is found by:
s
=
k
-
K
-
1
2
K
=
2
k
-
K
+
1
2
K
.
10. A non-transitory computer-readable medium that stores instructions that when executed by a computer, cause the computer to perform a method comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, wherein said upsampling increases a number of detector rows by 1.
11. A non-transitory computer-readable medium that stores instructions that when executed by a computer, cause the computer to perform a method comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data and
reconstructing an image of said subject using said upsampled data, wherein said method further comprises:
using an interpolation kernel in said upsampling; and
adaptively changing a size of said kernel.
12. A non-transitory computer-readable medium that stores instructions that when executed by a computer, cause the computer to perform a method comprising:
exposing a subject to x-rays;
collecting data;
performing upsampling with shift on said data to produce upsampled data; and
reconstructing an image of said subject using said upsampled data, wherein said method further comprises:
varying a shift amount used in said upsampling.