[Insight-users] Problem with BSpline Registration with Mattes-MI
Serena Fabbri
fabbri at u.washington.edu
Thu Jul 9 15:12:59 EDT 2009
Hi Luis, hi All,
I used DeformableRegistration15 and I got a good result.
In order to understand the problem in my code I did some trials:
1)
fixed=MRI, moving=BSpline (grid 6x6x6) registered image
Bspline grid=13x13x13
I have got the same result already described.
2)
I have changed the optimizer in my code. I have put itkRegularStepGradientDescentOptimizer with the
same parameters set in DeformableRegistration15.
fixed=MRI, moving=BSpline (grid 6x6x6) registered image
Bspline grid=13x13x13
I have got good result.
(I have checked several slices and i have seen pretty good overlap between fixed and registered image,
indeed nose structures appear in the correct place).
so I have a question: could LBFGSB be the reason about the bad result that i got ?
is LBFGSB able to manage only 'few' parameters?
now I have another question not correlated with the previous things.
I'd like to use Normalized Mutual Information and Bspline Transformation, but i get this error
message:
terminate called after throwing an instance of 'itk::ExceptionObject'
what(): /Users/physics/InsightToolkit-3.10.0/Code/Algorithms/itkImageToImageMetric.txx:91:
itk::ERROR: NormalizedMutualInformationHistogramImageToImageMetric(0x6690c0): Transform is not
present
Abort trap
of course in the code there are:
TransformType::Pointer transform = TransformType::New();
registration->SetTransform( transform );
where is the error? any suggestion?
Tx a lot!
Serena.
On Tue, 7 Jul 2009, Luis Ibanez wrote:
>
>
> Hi Serena,
>
> Please try running the example:
>
>
> Insight/Examples/Registration/
> DeformableRegistration15.cxx
>
>
> with your input images,
>
>
> and let us know if the results are similar or
> better than what you get with your current
> code.
>
>
> Thanks
>
>
> Luis
>
>
> -----------------------
> Serena Fabbri wrote:
>> Hi All,
>>
>> I am registering brain MRI and CT image with BSpline (Non Rigid
>> Registration), Mattes MI and LBFGSB optimization.
>>
>> fixed=MRI (176,256,160); (1,1,1)mm; (0,0,0)mm
>> moving=CT (176,256,160); (1,1,1)mm; (0,0,0)mm
>>
>> CT image is been previously Rigid registered to MRI
>>
>> I have started with 6x6x6 grid (3x3x3 nodes on the fixed image), MI sample
>> =20% statistics and the registered image is pretty good.
>> In order to improve the result I have used a fine grid: 13x13x13 (10x10x10
>> nodes on the fixed image), MI sample =20% statistics, and the result is:
>> in general the registration is good because some details are better
>> overlapped, but the slices containing the nose structures are distorted. In
>> particular nasal septum is deviated in the left side and the other bone
>> appears too much smoothed.
>> I have read some previous e-mails
>> (http://www.itk.org/pipermail/insight-users/2008-
>> December/028417.html) in archives and an Ibanez advice was to check if there
>> are enough samples for population every cell of the BSpline grid. I think
>> that it is enough samples because i get the same result with 50% samples.
>>
>> I have tried to set different number of nodes in x and y direction. I have
>> used 6x13x13 grid and 20% sample too, and i get exactly the same registered
>> image previous described (Below I put the Iteration-
>> MattesMI value ).
>>
>>
>> can anyone give me some advice?
>> maybe it is necessary to set different number of nodes in x and y direction.
>> Could it be a reasonable explanation?
>>
>> any suggestion will be appreciate.
>>
>> Thanks.
>>
>> Serena.
>>
>>
>> Iter MattesMI
>> 0 -0.350671 0 -0.351995 0 -0.357607 0 -0.377623 0
>> -0.402784 0 -0.402784 1 -0.435035 1 -0.435035 2 -0.430811
>> 2 -0.466589 2 -0.466589 3 -0.491583 3 -0.491583 4
>> -0.499865 4 -0.499865 5 -0.53353 5 -0.53353 6 -0.533558 6
>> -0.543796 6 -0.543796 7 -0.559133 7 -0.559133 8 -0.567699
>> 8 -0.567699 9 -0.577058 9 -0.577058 10 -0.586574 10
>> -0.586574 11 -0.59515 11 -0.59515 12 -0.600187 12 -0.600187
>> 13 -0.608752 13 -0.608752 14 -0.614033 14 -0.614033 15
>> -0.619695 15 -0.619695 16 -0.623183 16 -0.623183 17
>> -0.627047 17 -0.627047 18 -0.630555 18 -0.630555 19
>> -0.634089 19 -0.634089 20 -0.638822 20 -0.638822 21
>> -0.642822 21 -0.642822 22 -0.648013 22 -0.648013 23
>> -0.651278 23 -0.651278 24 -0.65333 24 -0.65333 25 -0.656569
>> 25 -0.656569 26 -0.659193 26 -0.659193 27 -0.661128 27
>> -0.661128 28 -0.663331 28 -0.663331 29 -0.66513 29 -0.66513
>> 30 -0.666392 30 -0.666392 31 -0.667716 31 -0.667716 32
>> -0.668881 32 -0.668881 33 -0.669772 33 -0.669772 34
>> -0.671548 34 -0.671548 35 -0.672711 35 -0.672711 36
>> -0.674103 36 -0.674103 37 -0.674998 37 -0.674998 38
>> -0.676283 38 -0.676283 39 -0.677051 39 -0.677051 40
>> -0.678061 40 -0.678061 41 -0.678757 41 -0.678757 42 -0.67975
>> 42 -0.67975 43 -0.680577 43 -0.680577 44 -0.681572 44
>> -0.681572 45 -0.682606 45 -0.682606 46 -0.683061 46
>> -0.683061 47 -0.683633 47 -0.683633 48 -0.684106 48
>> -0.684106 49 -0.684759 49 -0.684759 50 -0.685085 50
>> -0.685085 51 -0.685878 51 -0.685878 52 -0.686366 52
>> -0.686366 53 -0.686903 53 -0.686903 54 -0.687805 54
>> -0.687805 55 -0.688129 55 -0.688129 56 -0.688648 56
>> -0.688648 57 -0.689047 57 -0.689047 58 -0.689372 58
>> -0.689372 59 -0.690139 59 -0.690139 60 -0.690221 60
>> -0.690221 61 -0.690577 61 -0.690577 62 -0.69085 62 -0.69085
>> 63 -0.691391 63 -0.691391 64 -0.691557 64 -0.691557 65
>> -0.691489 65 -0.691692 65 -0.691692 66 -0.691924 66
>> -0.691924 67 -0.692416 67 -0.692416 68 -0.692831 68
>> -0.692831 69 -0.692933 69 -0.692933 70 -0.693209 70
>> -0.693209 71 -0.693661 71 -0.693661 72 -0.69374 72 -0.69374
>> 73 -0.694059 73 -0.694059 74 -0.694317 74 -0.694317 75
>> -0.694812 75 -0.694812 76 -0.694946 76 -0.694946 77
>> -0.695411 77 -0.695411 78 -0.695788 78 -0.695788 79
>> -0.695936 79 -0.695936 80 -0.69627 80 -0.69627 81 -0.696409
>> 81 -0.696409 82 -0.696002 82 -0.696418 82 -0.696418 83
>> -0.696533 83 -0.696533 84 -0.697105 84 -0.697105 85
>> -0.697287 85 -0.697287 86 -0.697609 86 -0.697609 87
>> -0.697957 87 -0.697957 88 -0.697482 88 -0.697993 88
>> -0.697993 89 -0.698045 89 -0.698045 90 -0.698389 90
>> -0.698389 91 -0.699091 91 -0.699091 92 -0.699072 92
>> -0.699127 92 -0.699127 93 -0.699169 93 -0.699169 94
>> -0.699422 94 -0.699422 95 -0.699545 95 -0.699545 96
>> -0.700181 96 -0.700181 97 -0.70052 97 -0.70052 98 -0.700755
>> 98 -0.700755 99 -0.700869 99 -0.700869 100 -0.699019 100
>> -0.700874 100 -0.700874 101 -0.697901 101 -0.700846 101
>> -0.700874 101 -0.700875 101 -0.700875 101 -0.700874 101
>> -0.700875 101 -0.700875 101 -0.700875 101 -0.700875 101
>> -0.700875 102 -0.682951 102 -0.700818 102 -0.700878 102
>> -0.700878 103 -0.700522 103 -0.700962 103 -0.700962 104
>> -0.700956 104 -0.701143 104 -0.701143 105 -0.700847 105
>> -0.701264 105 -0.701264 106 -0.699357 106 -0.701293 106
>> -0.701293 107 -0.700802 107 -0.701318 107 -0.701318 108
>> -0.701101 108 -0.701454 108 -0.701454 109 -0.701117 109
>> -0.701525 109 -0.701525 110 -0.700914 110 -0.701622 110
>> -0.701622 111 -0.701429 111 -0.701679 111 -0.701679 112
>> -0.702049 112 -0.702049 113 -0.702067 113 -0.702067 114
>> -0.702424 114 -0.702424 115 -0.702911 115 -0.702911 116
>> -0.702993 116 -0.702993 117 -0.703354 117 -0.703354 118
>> -0.70348 118 -0.70348 119 -0.703623 119 -0.703623 120
>> -0.703758 120 -0.703758 121 -0.703861 121 -0.703861 122
>> -0.703992 122 -0.703992 123 -0.704031 123 -0.704031 124
>> -0.704308 124 -0.704308 125 -0.704431 125 -0.704431 126
>> -0.704565 126 -0.704565 127 -0.704793 127 -0.704793 128
>> -0.704626 128 -0.704884 128 -0.704884 129 -0.7044 129
>> -0.704907 129 -0.704907 130 -0.705365 130 -0.705365 131
>> -0.705579 131 -0.705579 132 -0.705919 132 -0.705919 133
>> -0.706196 133 -0.706196 134 -0.706419 134 -0.706419 135
>> -0.706565 135 -0.706565 136 -0.706604 136 -0.706604 137
>> -0.706731 137 -0.706731 138 -0.706708 138 -0.706768 138
>> -0.706768 139 -0.706699 139 -0.70692 139 -0.70692 140
>> -0.706833 140 -0.706975 140 -0.706975 141 -0.706896 141
>> -0.707044 141 -0.707044 142 -0.706378 142 -0.70706 142
>> -0.70706 143 -0.705602 143 -0.707069 143 -0.706376 143
>> -0.707055 143 -0.707068 143 -0.707069 143 -0.707069 143
>> -0.707069 144 -0.0399776 144 -0.677537 144 -0.706919 144
>> -0.707062 144 -0.707068 144 -0.707069 144 -0.707069 144
>> -0.707069 144 -0.707069 144 -0.707069 144 -0.707069 144
>> -0.707069 144 -0.707069 145 -0.614007
>>
>>
>>
>>
>>
>>
>>
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