with reference to fig1 a and 1b , a medical diagnostic imaging apparatus 10 includes an x - ray detector 12 which receives radiation arriving from a subject on a subject support 14 . in the preferred ct scanner embodiment , radiation emanates from an x - ray tube 16 having radiation . the cone - beam , as defined herein , can have a circular cross - section , a square or rectangular cross - section , a hexagonal cross - section , or the like . the radiation detector 12 of the preferred embodiment includes an array of detector elements mounted in a configuration which mimics the cross - section of the x - ray beam 20 . for example , a dozen square detector elements 22 may be mounted in a pattern which approximates a circle . when the beam is rectangular or square , the detector elements would be positioned in a corresponding square or rectangular pattern . as yet another alternate embodiment , a plurality of stationary rings of the detector elements can be mounted around the subject . providing a plurality of stationary rings of the detector elements adds cost in the detectors , but removes the cost associated with rotating the detector assembly . each of the detector assemblies 22 includes a scintillation crystal 24 disposed toward the radiation source , an array of photodetectors 26 disposed to view the scintillation crystal , and an array of integrated circuits 28 connected with the array of photodetectors 26 . preferably , the scintillation crystal , photodetector , and integrated circuit assembly is mounted on a common substrate . the scintillation crystal and photodetectors are etched or cut to define a larger number of light - sensitive elements , e . g ., a 16 × 16 array . optionally , a detector collimator 30 is mounted to the scintillation crystals to limit received radiation to radiation travelling along rays from an origin of the cone - beam collimator . in the ct scanner embodiment , the origin of the collimator is selected to match the focal point of the x - ray tube . alternately , the medical diagnostic apparatus may be a nuclear camera . in the nuclear camera , the radiation source includes an emission radiation source in the form of a radiopharmaceutical that is injected into the subject . because the cone - beam collimator limits received radiation to radiation travelling along a conical array of rays , the resultant data is again cone - beam data . further , a transmission line source may be disposed opposite the patient from the radiation detector . in a nuclear camera , the transmission line source is commonly a radioisotope . as is known in the art , an appropriate means or mechanical mechanism is provided for rotating the radiation source and the detector around the subject and subject support . in a ct camera , the radiation source commonly rotates continuously at a relatively high rate of speed . in a nuclear camera , the detector and transmission radiation source , if any , commonly rotate in incremental steps . with continuing reference to fig1 a - 1b and further reference to fig2 and 3 , the radiation detectors are all sampled concurrently to generate a current view which is stored in a current view memory or latch 40 . the memory or latch 40 also stores an indication of the origin of the cone , i . e ., the location of the x - ray tube and / or the location of the detector assembly . in a ct scanner in which the cone is rotating rapidly , the detectors are sampled at very short time intervals . in a nuclear camera , the output of the detectors is commonly integrated over a dwell duration at each angular position . the data from the current view memory 40 is conveyed to a partial cone - beam data memory 42 which stores a source cone or fan of data h t ( u , v ). more specifically , the partial cone beam data h t represents the line integrals or projections onto the plane p 0 along the rays φ from the origin or x - ray source . a weighting processor 44 weights each partial cone data value h t ( u , v ) to generate a weighted or data view h t ( u , v ). in a preferred embodiment , the weighting is cosine weighting of the form : ## equ1 ## where the weighting term is the cosine of the ray angle and r is the radius of the circle that defines the scan helix . the object to be reconstructed is represented by a function f from r 3 to r , where e is the radius of a circle that defines the scan helix , i . e ., the distance from the z - axis at the origin ω to the origin of the cone . the trajectory of the x - ray source is described by a curve φ which is defined mathematically by a function φ from an interval λ of r to r 3 . in the case of helical scanning , such a function φ is defined by three coordinate equations φ ( t )=( λcos ωt , λsin ωt , σt ) for t a subset of λ . for any direction represented by a unit vector α in r 3 , the positive half - line originated at φ ( t ) can be represented parametrically by { φ ( t )+ rα | r ε [ 0 ,∞]} so that h ( α , t ) is defined by : ## equ2 ## is the integral of the function f along the semi - line starting at φ ( t ) in the direction α . a partial cone - beam data at any instant t 0 may be represented by h ( α , t ), with α in the subset of r 3 . φ ( t ) is the vertex of the partial cone at the particular instant t 0 . the definition of the function h can be extended for all α in r 3 with ∥ α ∥≠ 0 . such an extended version of h is denoted hereinafter by g . the inner product of two vectors x , y in r 3 is denoted by & lt ; x , y & gt ;. the fourier transform of the function f is given by : ## equ3 ## or in spherical coordinates : ## equ4 ## where s denotes the unit sphere r 3 . the following equations give a relationship between the fourier transform of a function f and that of a function g : where , ## equ5 ## is the three - dimensional fourier transform of g with respect to the first variable α . from the definition itself of the function f , it can be concluded that : ## equ6 ## if θ is a unit vector in r 3 , the slice projection theorem which produces the relationship between the fourier transform of f and the one - dimensional fourier transform of its planar integrals r 0 f , it can be concluded that : ## equ7 ## consequently , the expression f ( θ , u )- f (- θ ,- u ) is 0 if | u |& gt ; a for a , because the integrals along planes perpendicular to θ are 0 if the plane does not intersect the support of the function f . from this , it can be concluded that : ## equ8 ## in condition 1 , it is assumed that for any point x in the support of the function f , where f ( x ) is to be reconstructed from the cone - beam data , there exists a sub - interval λ x of λ such that any plane going through the support of f intersects the subcurve φ x of φ associated with the sub - interval λ x . from this condition and by making the change of variables defined by u =& lt ; φ ( t ), θ & gt ;, equation ( 10 ) can be expressed as : ## equ9 ## where the redundancy weight function m ( θ , t ) satisfies the following multiplicity condition which pertains to the number of times that the plane going through φ ( t ) and perpendicular to θ cuts the curve φ x : ## equ10 ## if the plane perpendicular to a direction θ and going through φ ( t ) intersects the sub - curve φ x at φ ( s 0 ), . . . , φ ( s t θ ), then the condition of equation ( 12 ) can simply be expressed as : the term f ( x ) can be computed from its fourier transform using the spherical coordinate system as follows : ## equ11 ## substituting equation ( 11 ) into equation ( 14 ), one obtains : ## equ12 ## after interchanging the order of integration , one obtains : ## equ13 ## observing that m (- θ , t )= m ( θ , t ), after the integration with respect to ρ , one has : ## equ14 ## that is , the set of t is such that φ ( t ) is the intersection of the plane going through f and perpendicular to the direction θ . the expression f ( x ) can also be written : ## equ15 ## observe that g and g are both homogeneous functions with respect to their first variable , and that g ( ρφ , t )= g ( φ , t )/ ρ 2 , equation ( 19 ) can be written as : ## equ16 ## the inner double integrals of the right hand side of equation ( 20 ) is only the three - dimensional inverse fourier transform of the product of two functions , namely : consequently , the integrals are the three - dimensional convolution of their inverse fourier transform . more precisely : ## equ17 ## the above convolution backprojection is complex due to the redundancy of the weighting function m and is not appropriate for partial cone - beam data . for the weighting function m constant , and with such constant set equal to 1 for simplicity , the kernel of the convolution is given by : ## equ18 ## the expression α and ξ in the coordinate system ( t , u , v ) with the t axis going through φ ( t ), and the u axis parallel to the vector φ &# 39 ;( t ): ## equ19 ## i . e ., q is the product of the classical ramp filter for the two - dimensional reconstruction with the delta function with respect to the variable ( t , v ) weighted with ∥ φ &# 39 ;( t )∥. consequently , the expression q ( x , t )=( g ( α , t )* q ( α , t )) ( x - φ ( t )) becomes : ## equ20 ## note that the function g is homogeneous with respect to its first variable . the convolution expression is a one - dimensional convolution of weighted line integrals or projection data along the direction of the tangent φ &# 39 ;( t ) of the trajectory φ . the kernel of the convolution is the classical ramp kernel which is used in two - dimensional slice reconstruction . furthermore , the convolution of g (- α , t ) is null since the object is of compact support . thus , if m is constant , i . e ., every plane goes through the point x at which f ( x ) is to be reconstructed cuts a sub - curve φ x at the same number of points , then the convolution is a one - dimensional convolution in the direction of φ &# 39 ;( t ). consequently , data can be collected in a partial cone - beam , as long as the data are not truncated in the direction of φ &# 39 ;( t ), for any instance t in λ x . although the exact reconstruction formula requires a non - constant weighting function m ( θ , t ) which satisfies the redundancy condition stated above , based on the simplicity of the convolution expression , the weighting function m can be written as the sum of a constant c and a non - constant function n , i . e . : with this decomposition , the convolved data is the sum of two terms . the first term corresponds to c ; and the second term corresponds to the weighting function n . because the first term requires a one - dimensional convolution in the direction φ &# 39 ;( t ), it can be assumed that the partial cone - beam data is collected within a rectangle with one side parallel to φ &# 39 ;( t ). in condition 2 , it is assumed that at any instant t , the data of the partial cone beam is not truncated in the direction φ &# 39 ;( t ) and there exists a positive integer k . the integer k has the property that if at time t , the data is truncated along a direction δ , then the plane defined by the line δ and the vertex φ ( t ) either ( i ) intersects φ x exactly k times or ( ii ) intersects φ x at another vertex φ ( t &# 39 ;) for which the data along the line δ &# 39 ; orthogonal to the plane is not truncated . furthermore , it is assumed that along that side , the data is not truncated . the redundancy condition on the function m requires n to satisfy the following condition : ## equ21 ## observe that if w ( θ , t )≧ 0 and satisfies the condition : ## equ22 ## then the function n can be defined by : ## equ23 ## w is chosen such that the computation of the convolved data does not use the truncated data . using the truncated data would allow n ( θ , t )= 0 . thus , to simplify the reconstruction , the reconstruction formula is chosen to be : ## equ24 ## where q 1 is the convolved data corresponding to c which is the one - dimensional convolution of the weighted data with the classical ramp function in the direction φ &# 39 ;( t ) and the second term q 2 is given by : ## equ25 ## thus , it follows that : ## equ26 ## the right hand side of equation ( 33 ) is only the product of - i / 2π , with the integral of the directional derivative of propagation data along a line in the detector plane and orthogonal to the direction θ . consequently , the computation of q 2 does not require the data along that line with the truncated data . to insure that such choice is always possible , w is selected accordingly . for this reason , appropriate conditions are set on the curve φ traversed by the x - ray source or origin of the cone - beam relative to the axis z . a spiral or a partial spiral extending from a to b satisfies the conditions . the weighting processor 44 performs the constant weighting component weighting of the data while a second factor processor 46 calculates the non - constant weighting factor . the weighted data from the processor 44 is conveyed to a first or q 1 processor 48 which calculates the q 1 component and to a second or q 2 processor 50 which calculates the q 2 component with the non - constant weighting function from the weighting function processor 46 . a processor 52 computes the sum of q 1 and q 2 and the sum is backprojected by a three - dimensional backprojector 54 , generally as described by equations ( 19 )-( 21 ) and as described in greater detail below . with reference to fig4 , and 6 , we start first in the ( t , u , v ) coordinate system . in this coordinate system q 1 is evaluated as : ## equ27 ## to simplify the coordinate transformation , the center of the coordinate system ( t , u , v ) is chosen to be the orthogonal projection c ( t ) of φ ( t ) onto the z - axis . this coordinate system is simply the translation of the coordinate system of fig5 with the translation vector d 96 , where τ is the unit vector along the t - axis . in this new coordinate system , the coordinates ( t , u , v ) of the reconstruction point x can be obtained from its original coordinates ( x , y , z ) by multiplying the column matrix ( x , y , z - σt ) t with the 3 × 3 rotation matrix a ( t ) which consists of the coordinates of the unit vectors τ , μ , ν along the t , u , and v - axes respectively . for φ ( t )=( rcosωt , rsinωt , σt ): it remains then to evaluate the integral expression of q 1 using a sample from the set of line integrals h t which are estimated from the partial cone - beam projection data . conforming to the choice of the new local coordinate system , h t ( u , v ) is defined as the integral of the function f along the line from φ ( t ) to the point ( u , v ) in the plane defined by c ( t ), the u and v - axes of the local coordinate system . for p as the point x -( 0 , u , 0 ) as shown in fig3 by the homogeneity property of g , one can express g from the corresponding line integrals as follows : ## equ28 ## for p as the intersection of the line from φ ( t ) to p with the ( c ( t ), u , v ) plane , the coordinates of the point p in the coordinate system are ( 0 , w ( u - u ), wv ) with w = r /( r - t ). because p = φ ( t )+ w ( p - φ ( t ))=( r , 0 , 0 )+ w ( t - r , u - u , v ), and because w is the constant which makes the first coordinate of p null , then : accordingly , the expression of q 1 becomes : ## equ31 ## when v is defined as equal to wv , and after a change of the variable of integration is made , q 1 becomes : ## equ32 ## where h t ( u , v ) is defined by equation ( 1 ), where r =∥ φ &# 39 ;( t )∥/ 2π 2 . in other words q 1 ( x , t ) is obtained by convolving h t ( u , v ) with the classical ramp kernel with respect to the first variable u and evaluating it at wu , where u is the second coordinate of x in the local coordinate system . h t ( u , v ) is the projection data h t ( u , v ) weighted with the constant divided by the distance from φ ( t ) to the point ( u , v ) on the plane ( c ( t ), u , v ). thus , the term q 1 is essentially a one - dimensional convolution of the weighted data with the classical ramp 2d reconstruction filter . by contrast , the computation of q 2 involves the computation of a weighting function n based on a knowledge of the number of intersection points of a plane with a portion of the helix φ , the trajectory of the vertex of the cones . accordingly , before calculating q 2 , one first establishes the number of intersection points . with reference again to fig1 and 2 , and further reference to fig6 the equation for the local coordinate planes ( cosωt 0 , sinωt 0 , 0 ) is : a plane ( q ) containing φ ( t 0 ) and a point x of the support of the object intersects φ at another point φ ( t ) if and only if the intersection i of the line joining the two vertices φ ( t ) and φ ( t 0 ) with the coordinate plane ( p 0 ) associated with φ ( t 0 ) belongs to the intersection line d of the plane ( q ) with the plane ( p 0 ). note that i belongs to both planes ( q ) and ( p 0 ). conversely , when the intersection line d of ( q ) with ( p 0 ) contains the point i which is the intersection of φ ( t 0 ), φ ( t ) with the plane ( p 0 ), then φ ( t ) belongs to ( q ), i . e ., ( q ) intersects φ at φ ( t ). to count the number of intersection points of the plane ( q ) besides φ ( t 0 ), the number of intersections points of the line d with the trace of the helix on ( p 0 ) is counted . the trace of φ on the local coordinate plane ( p 0 ) associated with φ ( t 0 ) is the set of intersection points i of the line φ ( t 0 ) φ ( t ) with the plane ( p 0 ) as t varies in an interval containing t 0 . similarly , the trace of a point x onto the local coordinate plane ( p 0 ) is defined by the point of the intersection m at the line φ ( t 0 ), x with the plane ( p 0 ). the trace of φ contains two branches of curves which intersect the u - axis at infinity , because the line φ ( t 0 ) φ ( t ) becomes tangent to φ as t tends to t 0 . the coordinates of the intersection point i can be written as a point of the line φ ( t 0 ) φ ( t ) as : where r is a real number . because the point i belongs to the local coordinate plane , the coordinates of i must satisfy the above equation of the local coordinate plane . accordingly , r =( 1 - cosω ( t - t 0 )) - 1 . the equation ( 42 ) coordinates of i are with respect to the original coordinate system oxyz . with reference to fig3 to obtain the coordinates ( u , v ) of i with respect to the local coordinate system , it suffices to compute the inner product of the vector ωi with the unit vectors : it follows that : ## equ33 ## as t → t 0 , u →±∞, and v → 0 , for t = t 0 ± π / ω , equations ( 45a ) and ( 45b ) become : ## equ34 ## the derivatives of u and v with respect to t are : ## equ35 ## for ω and σ & gt ; 0 , the derivative of u with respect to t is negative , and that the derivative of v is positive . note fig7 . this analysis of u and v shows that the trace of the helix on a local coordinate plane has a graph in the ( u , v ) space as illustrated in fig8 . this analysis suggests the following practical criteria to count the number of intersection points of a plane going through a point of reconstruction with part of a helix . with reference to fig9 [ t 1 , t 2 ] is an interval containing t 0 and i 1 , i 2 is the trace of φ ( t 1 ) and φ ( t 2 ) on the local coordinate planes ( p 0 ) associated to t 0 , respectively . ( q ) is a plane containing φ ( t 0 ) and a point x on the support of the object . m is the trace of x on ( p 0 ) and d is the intersection of ( q ) with ( p 0 ). looking to the first criteria , ( q ) intersects φ at φ ( t ) with t in [ t 1 , t 2 ] if and only if d intersects the portion of the branch of the trace of the helix from -∞ to i 1 . practically , this is equivalent to the angle between the half lines mu &# 39 ; and md &# 39 ; being less than the angle between mu &# 39 ; and mi 1 . looking to the second criteria , ( q ) intersects φ at φ ( t ) with t in [ t 0 , t 2 ] if and only if d intersects the portion of the branch of the trace of the helix from i 2 to ∞. practically , this is equivalent to the angle between the half lines mu and md being less than the angle between mu and mi 2 . q 2 as defined in equations ( 32 ) and ( 33 ) can be further quantified by splitting the unit sphere into the union of two disjoint sphere halves , namely s / 2 and - s / 2 , the upper and lower half unit spheres . equation ( 32 ) then reduces to : ## equ36 ## where : substituting - θ for θ in the second integral of q 2 and because i (- θ , t )=- i ( θ , t ), equation ( 48 ) becomes : ## equ37 ## integrating with respect to the variable ρ and replacing g ( θ , t )- g (- θ , t ) by the above - expression , one obtains : ## equ39 ## equation ( 51 ) is similar to equation ( 11 ) of the defrise and clack reference of record , but with a different weighting function n ( θ , t ). the following notation is used in transposing their results : ( u , v ) is the local coordinates of the intersection of the local coordinate plane ( p 0 ) with the line going through φ ( t ) and parallel to the direction α ; ( u x , v x ) is the local coordinates of the trace of the reconstruction point x ; ( s , ψ ) is the polar parameters of the intersection of the local coordinate plane ( p 0 ) with the plane perpendicular to the direction θ and going through x , and φ ( t ); and , lh t ( s , ψ ) is the integral of the function h t along the line defined by the polar parameter ( s , ψ ), where s is the distance from ω to the line , and ψ is the angle between the u - axis and the line , see fig1 . with this notation , q 2 can be carried out as follows : ## equ40 ## may be computed using grangeat &# 39 ; s fundamental relationship by multiplying |& lt ; φ &# 39 ;( t ), θ & gt ;| n ( θ , t ) with the weighted partial derivatives of the line integrals of h t : ## equ41 ## with h t being a function defined on the local coordinate plane in a fashion similar to the one defined for computing q 1 , except for a constant factor : ## equ42 ## in other words , q 2 is obtained by two - dimensionally backprojecting at the trace of the reconstruction point , partial derivatives of weighted partial derivatives of line integrals of weighted partial cone - beam data . with reference to fig1 , a coordinate system ωqrs is defined with ωq along ωφ ( t ), ωr parallel to the intersection line d of the color coordinate plane with the plane perpendicular to the unit vector θ , and perpendicular to d . in this coordinate system , the coordinates of the vector α are ( ρ , σ , r )/( ρ 2 + σ 2 + r 2 ) 1 / 2 and those of the intersection point n of the line d with the axis ωs are ( 0 , s , 0 ). because the vector θ is perpendicular to both vectors ( 0 , s , 0 ) and the vector nφ ( t ) with coordinates ( 0 ,- s , r ), it follows that the coordinates of θ are proportional to the exterior product of the two vectors . consequently , the coordinates of θ are ( 0 , r ,- s )/( s 2 + r 2 ) 1 / 2 , and hence : ## equ43 ## if a and b are the polar and azimuthal angles of the unit vectors α , see fig1 , then : hence , equation ( 54 ) becomes : ## equ46 ## where h t ( ρ , σ )= rg ( α , t ). after integrating with respect to σ , this becomes : ## equ47 ## from this , a constructive form of q 2 can be developed . in the local coordinate system in which integration is carried out with respect to θ over s / 2 , the vector θ can be obtained by multiplying its coordinates with respect to ( r , s ) coordinate system with the rotation matrix introduced by the angle ( π / 2 - ψ ). consequently : ## equ48 ## moreover , if a and b are the polar and the azimuthal angles of the vector θ , then : ## equ51 ## and with particular reference to fig6 the q 2 calculation 50 is divided into four parts . first , a processor or means 60 computes line integrals of the weighted partial cone - beam data . this is followed by a processor or means 62 for estimating the partial derivative of the line integrals with respect to the variable s , which represents the distance from the origin ω of the local coordinate system to the lines in accordance with equation ( 54 ). the partial derivatives of the line integrals h t ( s , ψ ) are weighted by ( r 2 + s 2 )/( 4π 2 s 2 ). this weighting is inversely proportional to cos 2 ( a ), where a denotes the divergence angle between the line φ ( t ) ω and the plane generated by the vertex φ ( t ) and the line parameterized by ( s , ψ ). for simplicity of computation , the parallel beam geometry described by the parameters ( s , ψ ) on the local coordinate plane is utilized throughout the computation of q 2 . a second part 46 computes the weight w associated with each line ( s , ψ ) in order to insure the normalization of the 3d backprojection when reconstructing the images . to insure this normalization , the number of intersections of a plane with the portion of the helix in which the data are three - dimensionally backprojected for reconstruction are computed for each plane defined by ( s , ψ ). a processor or means 70 identifies the affected volume v t . more specifically , a processor or means 72 computes the traces a z and b z of the end points of the backprojection range for each slice , indexed by c , in the affected volume v t . a processor or means 74 computes the weighting function w t for each view t of each slice z in accordance with : due to the fact that the truncated data is not used in backprojection , a count of the number of intersection vertices with non - truncated data along the plane is also counted . with reference to fig1 and continuing reference to fig6 without counting the current vertex φ ( t ), the number of intersections of a plane defined by the line ( s , ψ ) is equal to the number of intersections of the line ( s , ψ ) with the two branches of the trace of the portion of the helix in which the data are backprojected to create a slice of the reconstructed volume . this number is constant and equal to 1 when the line ( s , ψ ) cuts the line δ outside the line segment defined by the orthogonal projections of δ of the traces of the two extreme vertices of the portion of the helix . inside this line segment , the number is either 0 or 2 . that is , the line ( s , ψ ) either intersects the two branches of the trace or it does not have a common point with the trace at all . second , because the weight is null for lines along which the data are truncated , it is not necessary to do any computation of line integrals or other related factors of these truncated lines . more specifically , it is predetermined into how many slices the data is to be reconstructed , the number of pixels per slice , and the like . for each view t , a determination is made which slices are affected by view t , k is set 76 accordingly to either 1 or 2 for the reconstruction process . once k is set , c from equation ( 27 ) is known as is the weight of q 1 , which gives the range of each slice . at 78 a sufficient range [ t 1z , t 2z ] which satisfies the condition 2 , i . e ., that the angle between the half lines mu &# 39 ; and md &# 39 ; is less than the angle between mu &# 39 ; and mi 1 to reconstruct slice c in the reconstruction volume v . from the range , the weighting for q 2 is determined . for each view t , a step or means 80 computes the traces a z and b z of φ ( t 1z ) and φ ( t 2z ) for each slice z in the affected volume v t . a step or means 82 computes orthogonal projections a z and b z of the traces a z and b z onto the line δ which makes an angle ψ with the u - axis and goes through the origin ω . with reference to fig6 and 12 , a step or means 84 computes the number of intersections m tz ( s , ψ ) of the portion of the helix between ψ ( t 1z ) and ψ ( t 2z ) with the plane p ( s , ψ ) defined by ψ ( t ) and the line l ( s , ψ ), which is orthogonal to the line δ at a distance s from ω . again , the helix can only intersect the plane at 1 , 2 , or 3 points . m tz ( s , ψ )= 1 or 3 , if the line l of ( s , ψ ) cuts [ a z , b z ]. otherwise , m tz ( s , ψ )= 2 . the step or means 86 computes the number m &# 39 ; tz ( s , ψ ) of the vertices among the intersections with non - truncated data along the plane p ( s , ψ ). a step or means 88 computes the number n tz ( s , ψ ) which is supplied to the step or means 74 to compute the weighting function w tz ( s , ψ ). the number of intersections is calculated in accordance with : with reference again to fig6 a processor 90 determines a partial derivative with respect to s and weights it . more specifically , a step or means 92 computes i tz ( s , ψ )= w tz ( s , ψ ) p t ( s , ψ ). a step or means 94 determines the jacobian j tz ( s , ψ ) as follows : ## equ57 ## a processor 96 multiplies , at each pixel ( u , v ) in the local coordinate plane , the backprojection of ( u , v ) from the processor 90 with the square of the distance from the vertex φ ( t ) to the pixel . more specifically , a step or means 98 adds up 180 ° of parallel beam backprojections . it performs a parallel beam two - dimensional backprojection of j tz at each ( u , v ) to compute b tz ( u , v ). a step or means 100 computes q 2tz ( u , v )=( u 2 + v 2 + r 2 ) b tz ( u , v ). these values of q 2 are supplied to the summation means 52 to be combined with the corresponding values of q 1 . with reference to fig1 and 14 , the three - dimensional backprojector 54 is a processor which computes the final reconstruction from the processed data , such as the above - described convolved data . the backprojector is an estimator of : ## equ58 ## where q represents the processed data . because the data are collected at only a finite number of instances , the integral can be approximated by the finite sum : further , the continuous volume can be represented by a finite number of voxels of size δxδyδz , that is x =( 1δx , mδy , nδz )+( x 0 , y 0 , z 0 ) for some 1 = 0 , 1 , . . . , l - 1 , m = 0 , 1 , . . . , m - 1 , n = 0 , 1 , . . . , n - 1 . ( x 0 , y 0 , z 0 ) is a corner of the represented volume . when q is reduced to q 1 , then q is estimated by appropriately weighting the convolved data h t . due to the fact that at each instance t , data are collected only along a finite number of rays within a partial cone - beam , h t ( u , v ) must be approximated from a sample { h t ( iδu + u 0 , jδv + v 0 ) | i = 0 , 1 , . . . , i - 1 , and j = 0 , 1 , . . . , j - 1 }. it should further be noted that because there is data within a partial cone geometry , the backprojection of the processed data does not affect the whole represented volume , but only a portion of it . another important point is that the backprojection is conveniently carried out in a new coordinate system defined by ( c ( t ), u , v ). with particular reference to fig1 , a three - dimensional image memory 110 receives the backprojected views . as each view t is received , an affected volume determining means or step 112 determines the part of the volume of memory 110 which is affected by the processed view t . a voxel generator 114 sweeps through all of the voxels in the affected part of the volume . a coordinate transform processor 116 converts the absolute coordinate system ( x , y , z ) of the voxel address generator into the local coordinate system ( t , u , v ). with continuing reference to fig1 and further reference to fig1 , a weight generating system includes a first weight generator 118 which generates a first weighting value w which is equal to r /( r - t ). a two - dimensional input generator 120 which generates local coordinates of a voxel given by the voxel generator , the local address being ( u , v ) and generates weighting factors u and w , where u = wu and v = wv . the u and v addresses address a two - dimensional memory 122 in which the two - dimensional view h t * ram is stored . an input interpolator 124 uses the input data retrieved from the input memory 122 and fractional parts of the new coordinates calculated by the two - dimensional input generator 120 to estimate the input data corresponding to a ray going through the voxel given by the voxel generator . a multiplier 126 multiplies the weighting factor w by itself to form a weighting factor w 2 . a multiplier 128 multiplies the interpolated input data h t * ram ( u , v ) by the squared weighting function w 2 . an adder 130 retrieves the current values b ( l , m , n ) retrieved from the volumetric memory 110 with the product from the multiplier 128 . in this manner , the values stored in each voxel is updated with each two - dimensional set of processed data . initially , the three - dimensional output memory 110 has each pixel value assigned a nominal , non - zero starting value , e . g ., 1 . in this manner , the value at each voxel is iteratively updated until an accurate reconstruction is obtained . the invention has been described with reference to the preferred embodiment . obviously , modifications and alterations will occur to others upon reading and understanding the preceding detailed description . it is intended that the invention be construed as including all such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof .
a two - dimensional radiation detector receives divergent ray penetrating radiation along conical or pyramidal ray paths which converge at an apex . the radiation may emanate from one or both of an x - ray tube or radionuclei injected into a human subject . as the radiation detector rotates around the subject , it is repeatedly sampled to generate two - dimensional data sets h t at each of a plurality of samplings t . each two - dimensional data array is weighted and divided into two components . a first component processor convolves a first component of each two - dimensional array with respect to u for each v . a second component processor processes a second component of each two - dimensional array including weighting each component with a geometrically dependent weighting function w from a weighting function computer . the processed first and second components are combined and backprojected .