Computed tomography method and apparatus for optimized detector utilization and dose utilization

Claim 3

A method as claimed in claim 1 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis.

Claim 4

A method as claimed in claim 1 wherein step (b) comprises dividing said output data into sub-segments wherein neighboring sub-segments overlap in overlapping regions, and comprising the additional step of weighting the output data in said overlap regions so that the respective portions of the output data in said overlap regions belonging to the neighboring sub-segments in that overlap region have respective weightings which, in combination, add to one.

Claim 5

A method as claimed in claim 1 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality of segment images inclined relative to said system axis which have different positions along a z-axis of a Cartesian coordinate system.

Claim 6

A method as claimed in claim 4 wherein step (c) further comprises, for each of sub-segments, reconstructing a plurality of images respectively in inclined image planes that intersect in a straight line proceeding tangentially relative to that sub-segment, as said plurality of segment images having a plane inclined relative to said system axis.

Claim 7

A method as claimed in claim 4 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, in step (c), for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0  - R f cos   γ 0 - ( ± RFOV )   sin   α 1 cos   γ 0 )   wherein γ 0 = arc   tan  ( - Sp   α ⋒ 2  π   R f  sin   α ⋒ ) .

Claim 8

A method as claimed in claim 1 wherein step (a) comprises rotating said focus around a rotational axis that coincides with said system axis.

Claim 9

A method as claimed in claim 1 wherein step (a) comprises rotating said focus around a rotational axis that intersects said system axis at a gantry angle ρ and wherein, in step (c), for each of said sub-segments, the plurality of segment images have respective inclination angles γ′ according to γ ′ = arc   tan  Sp ·  cos   ρ 4  π 2 · R f + S 2  p 2 + 4  π · R f  cos   α   sin   ρ · Sp .

Claim 10

A method as claimed in claim 8 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, in step (c), for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0  - R f cos   γ 0 - ( ± RFOV )   sin   α 1 cos   γ 0 )   wherein γ 0 = arc   tan  ( - Sp   α ⋒ 2  π   R f  sin   α ⋒ ) , and further comprising determining an optimum value γ min• of said inclination angle γ′ for a magnitude of said maximum value of said tilt angle |δ max | by satisfying an error criterion.

Claim 11

A method as claimed in claim 1 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality n ima of segment images inclined relative to said system axis which have different positions along a z-axis of a Cartesian coordinate system, and wherein: n ima = floor  [ sM p ] wherein s is a length of the sub-segment.

Claim 12

A method as claimed in claim 10 wherein step (c) comprises, for each of said sub-segments, reconstructing a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, in step (c), for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0  - R f cos   γ 0 - ( ± RFOV )   sin   α 1 cos   γ 0 )   wherein γ 0 = arc   tan  ( - Sp   α ⋒ 2  π   R f  sin   α ⋒ ) and further comprising determining the respective tilt angles δ of the inclined image planes according to δ  ( i ) = δ max  2  i - ( n ima - 1 ) n ima - 1 .

Claim 13

A method as claimed in claim 1 wherein step (d) comprises, for each of said sub-segments, combining said plurality of segment images by interpolation to form said partial image.

Claim 14

A method as claimed in claim 1 wherein step (d) comprises, for each of said sub-segments, combining said plurality of segment images by averaging to form said partial image.

Claim 15

A method as claimed in claim 1 wherein step (d) comprises, for each of said sub-segments, combining said plurality of segment images by weighted averaging to form said partial image.

Claim 16

A method as claimed in claim 14 wherein step (d) further comprises, for each of said sub-segments, weighting the plurality of segment images for that sub-segment dependent on a predetermined reconstruction slice thickness of said partial image.

Claim 17

A method as claimed in claim 1 wherein step (d) comprises, for each sub-segment, selecting said plurality of segment images for combining to form said partial image dependent on a predetermined reconstruction slice thickness of said partial image.

Claim 18

A method as claimed in claim 16 wherein step (c) comprises, for each of said sub-segments, reconstructing the segment images with a smallest possible value of said slice thickness of said partial image.

Claim 19

A method as claimed in claim 16 wherein step (c) comprises, for each of said sub-segments, selecting said plurality of images to be combined for generating said partial image, according to: N M =2·max( z*, sup φ ΔZ R ) W·N S .

Claim 20

A method as claimed in claim 1 comprising the additional step of selecting said target image plane as a plane that intersects said system axis at a right angle.

Claim 21

A method as claimed in claim 1 wherein step (e) comprises combining said partial images by addition to form said resulting CT image.

Claim 22

A method as claimed in claim 20 wherein each of said segment images has segment image data associated therewith, and comprising the additional step of compressing said segment image data to form compressed data.

Claim 23

A method as claimed in claim 21 wherein the step of compressing said segment image data comprises compressing said segment image data to form compressed data exhibiting a non-uniform pixel matrix having resolution in a first direction, proceeding substantially in a direction of a reference projection for the respective sub-segment is higher than in a second direction proceeding substantially orthogonally relative to said reference projection direction.

Claim 24

A method as claimed in claim 22 comprising forming said compressed data of pixels having an oblong shape, with each pixel having a longest extent proceeding substantially in said direction of said reference projection direction for that sub-segment.

Claim 25

A method as claimed in claim 23 comprising forming said compressed data of rectangular pixels.

Claim 26

A method as claimed in claim 23 comprising converting said segment images into said non-uniform pixel matrix.

Claim 27

A method as claimed in claim 23 comprising reconstructing said segment images in said non-uniform pixel matrix.

Claim 28

A method as claimed in claim 26 wherein said reconstruction of said segment images ensues by back projection in a back-projection direction, and selecting said back-projection direction to substantially coincide with said reference projection direction for that sub-segment.

Claim 29

A method as claimed in claim 21 comprising reversing said compression in step (e) to produce said resulting CT image with a uniform pixel matrix.

Claim 30

A method as claimed in claim 28 comprising obtaining said pixels of said uniform matrix by interpolation from the pixels of said non-uniform pixel matrix.

Claim 31

A method as claimed in claim 28 comprising obtaining said pixels of said uniform matrix by averaging from the pixels of said non-uniform pixel matrix.

Claim 32

A computed tomography (CT) apparatus comprising: a CT scanner having an x-ray source with a focus and a matrix-like detector array for scanning a subject with a conical x-ray beam emanating from said focus and detecting said beam, after attenuation by said subject, with said matrix-like detector array while moving said focus along a spiral path around said subject relative to a system axis, said detector array generating output data dependent on radiation from said x-ray beam that is incident thereon; a computer supplied with said output data, said computer dividing said output data, for a segment of said spiral path having a length adequate for reconstructing a CT image, into a plurality of datasets respectively for a plurality of sub-segments of said segment, each of said sub-segments having a length shorter than said length adequate for reconstructing a CT image; said computer, for each of said sub-segments, reconstructing a plurality of segment images having a plane inclined relative to said system axis from the dataset for that sub-segment; said computer, for each of said sub-segments, combining the plurality of segment images reconstructed from the dataset for that sub-segment to form a partial image with respect to a target image plane; and said computer, combining the respective partial images for the respective sub-segments to form a resulting CT image with respect to said target plane.

Claim 33

A computed tomography (CT) apparatus comprising: a CT scanner having an x-ray source with a focus and a matrix-like detector array for scanning a subject with a conical x-ray beam emanating from said focus and detecting said beam, after attenuation by said subject, with said matrix-like detector array while moving said focus along a spiral path around said subject relative to a system axis, said detector array generating output data dependent on radiation from said x-ray beam that is incident thereon; a computer supplied with said output data, said computer dividing said output data, for a segment of said spiral path having a length adequate for reconstructing a CT image, into a plurality of datasets respectively for a plurality of sub-segments of said segment, each of said sub-segments having a length shorter than said length adequate for reconstructing a CT image; said computer, for each of said sub-segments, reconstructing a plurality of segment images having a plane inclined relative to said system axis from the dataset for that sub-segment; said computer, for each of said sub-segments, combining the plurality of segment images reconstructed from the dataset for that sub-segment to form a partial image with respect to a target image plane; and said computer, combining the respective partial images for the respective sub-segments to form a resulting CT image with respect to said target plane.

Claim 34

A computed tomography apparatus as claimed in claim 31 wherein sai computer, for each of said sub-segments, reconstructs a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis.

Claim 35

A computed tomography apparatus as claimed in claim 31 wherein said computer divides said output data into sub-segments wherein neighboring sub-segments overlap in overlapping regions, and weighs the output data in said overlap regions so that the respective portions of the output data in said overlap regions belonging to the neighboring sub-segments in that overlap region have respective weightings which, in combination, add to one.

Claim 36

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each of said sub-segments, reconstructs a plurality of segment images inclined relative to said system axis which have different positions along a z-axis of a Cartesian coordinate system.

Claim 37

A computed tomography apparatus as claimed in claim 34 wherein said computer, for each of sub-segments, reconstructs a plurality of images respectively in inclined image planes that intersect in a straight line proceeding tangentially relative to that sub-segment, as said plurality of segment images having a plane inclined relative to said system axis.

Claim 38

A computed tomography apparatus as claimed in claim 34 wherein said computer, for each of said sub-segments, reconstructs a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0  - R f cos   γ 0 - ( ± RFOV )   sin   α 1 cos   γ 0 )   wherein γ 0 = arc   tan  ( - Sp   α ⋒ 2  π   R f  sin   α ⋒ ) .

Claim 39

A computed tomography apparatus as claimed in claim 31 wherein said focus rotates around a rotational axis that coincides with said system axis.

Claim 40

A computed tomography apparatus as claimed in claim 31 wherein said focus rotates around a rotational axis that intersects said system axis at a gantry angle ρ and wherein, for each of said sub-segments, the plurality of segment images have respective inclination angles γ′ according to γ ′ = arctan   S   p · cos   ρ 4  π 2 · R f + S 2  p 2 + 4  π · R f  cos   α   sin   ρ · S   p .

Claim 41

A computed tomography apparatus as claimed in claim 38 wherein said computer, for each of said sub-segments, reconstructs a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0  - R f cos   γ 0 - ( ± RFOV )   sin   α 1 cos   γ 0 )   wherein γ 0 = arc   tan  ( - Sp   α ⋒ 2  π   R f  sin   α ⋒ ) , and further comprising determining an optimum value ε min• Of said inclination angle γ′ for a magnitude of said maximum value of said tilt angle |δ max | by satisfying an error criterion.

Claim 42

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each of said sub-segments, reconstructs a plurality n ima of segment images inclined relative to said system axis which have different positions along a z-axis of a Cartesian coordinate system, and wherein: n ima = floor  [ sM p ] wherein s is a length of the sub-segment.

Claim 43

A computed tomography apparatus as claimed in claim 40 wherein said computer, for each of said sub-segments, reconstructing a plurality of said segment images in image planes that are inclined relative to both a first axis, that intersects said system axis at a right angle by an inclination angle γ, and a second axis intersecting each of said first axis and said system axis at respective right angles by a tilt angle δ measured with respect to said system axis, and wherein, for each of said sub-segments, the plurality of segment images associated therewith respectively have image planes inclined relative to said system axis limited by extreme values +δ max• and −δ max of said tilt angle δ, according to ± δ max = arctan  ( - WM 2 + Sp  α 1 2  π ± RFOV   cos   α 1  tan   γ 0 - R f cos   γ 0 - ( ±  RFOV )   sin   α 1 cos   γ 0 ) wherein γ 0 = arctan   ( - Sp   α ̑ 2  π   R f  sin   α ̑ ) and further comprising determining the respective tilt angles δ of the inclined image planes according to δ  ( i ) = δ max  2  i - ( n ima - 1 ) n ima - 1 .

Claim 44

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each of said sub-segments, combines said plurality of segment images by interpolation to form said partial image.

Claim 45

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each of said sub-segments, combines said plurality of segment images by averaging to form said partial image.

Claim 46

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each of said sub-segments, combines said plurality of segment images by weighted averaging to form said partial image.

Claim 47

A computed tomography apparatus as claimed in claim 44 wherein said computer, for each of said sub-segments, weighs the plurality of segment images for that sub-segment dependent on a predetermined reconstruction slice thickness of said partial image.

Claim 48

A computed tomography apparatus as claimed in claim 31 wherein said computer, for each sub-segment, selects said plurality of segment images for combining to form said partial image dependent on a predetermined reconstruction slice thickness of said partial image.

Claim 49

A computed tomography apparatus as claimed in claim 46 wherein said computer, for each of said sub-segments, reconstructs the segment images with a smallest possible value of said slice thickness of said partial image.

Claim 50

A computed tomography apparatus as claimed in claim 46 wherein said computer, for each of said sub-segments, selects said plurality of images to be combined for generating said partial image according to: N M =2·max( z*, supφΔz R ) W·N S .

Claim 51

A computed tomography apparatus as claimed in claim 31 wherein said computer selects said target image plane as a plane that intersects said system axis at a right angle.

Claim 52

A computed tomography apparatus as claimed in claim 31 wherein said computer combines said partial images by addition to form said resulting CT image.

Claim 53

A computed tomography apparatus as claimed in claim 50 wherein each of said segment images has segment image data associated therewith, and wherein said computer has a compression stage compressing said segment image data to form compressed data.

Claim 54

A computed tomography apparatus as claimed in claim 51 wherein said compression stage compresses said segment image data to form compressed data exhibiting a non-uniform pixel matrix having resolution in a first direction, proceeding substantially in a direction of a reference projection for the respective sub-segment is higher than in a second direction proceeding substantially orthogonally relative to said reference projection direction.

Claim 55

A computed tomography apparatus as claimed in claim 52 wherein said compression stage forms said compressed data of pixels having an oblong shape, with each pixel having a longest extent proceeding substantially in said direction of said reference projection direction for that sub-segment.

Claim 56

A computed tomography apparatus as claimed in claim 53 wherein said compression stage forms said compressed data of rectangular pixels.

Claim 57

A computed tomography apparatus as claimed in claim 53 wherein said computer converts said segment images into said non-uniform pixel matrix.

Claim 58

A computed tomography apparatus as claimed in claim 53 wherein said computer reconstructs said segment images in said non-uniform pixel matrix.

Claim 59

A computed tomography apparatus as claimed in claim 56 wherein said computer reconstructs said segment images ensues by back projection in a back-projection direction, and selects said back-projection direction to substantially coincide with said reference projection direction for that sub-segment.

Claim 60

A computed tomography apparatus as claimed in claim 51 wherein said computer reverses said compression to produce said resulting CT image with a uniform pixel matrix.

Claim 61

A computed tomography apparatus as claimed in claim 58 wherein said computer obtains said pixels of said uniform matrix by interpolation from the pixels of said non-uniform pixel matrix.

Claim 62

A computed tomography apparatus as claimed in claim 58 wherein said computer obtains said pixels of said uniform matrix by averaging from the pixels of said non-uniform pixel matrix.