1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
|
/*
//
// Copyright 1997-2009 Torsten Rohlfing
//
// Copyright 2004-2010 SRI International
//
// This file is part of the Computational Morphometry Toolkit.
//
// http://www.nitrc.org/projects/cmtk/
//
// The Computational Morphometry Toolkit is free software: you can
// redistribute it and/or modify it under the terms of the GNU General Public
// License as published by the Free Software Foundation, either version 3 of
// the License, or (at your option) any later version.
//
// The Computational Morphometry Toolkit is distributed in the hope that it
// will be useful, but WITHOUT ANY WARRANTY; without even the implied
// warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License along
// with the Computational Morphometry Toolkit. If not, see
// <http://www.gnu.org/licenses/>.
//
// $Revision: 2453 $
//
// $LastChangedDate: 2010-10-18 10:33:06 -0700 (Mon, 18 Oct 2010) $
//
// $LastChangedBy: torstenrohlfing $
//
*/
namespace
cmtk
{
/** \addtogroup Registration */
//@{
template<class TMetricFunctional>
void
SplineWarpMultiChannelRegistrationFunctional<TMetricFunctional>
::EvaluateThreadFunction( void* args, const size_t taskIdx, const size_t taskCnt, const size_t, const size_t )
{
ThreadParameters<Self>* params = static_cast<ThreadParameters<Self>*>( args );
Self* This = params->thisObject;
const Self* constThis = This;
typename Self::MetricData metricData;
metricData.Init( This );
const DataGrid::IndexType& dims = constThis->m_ReferenceDims;
const int dimsX = dims[0], dimsY = dims[1], dimsZ = dims[2];
std::vector<Vector3D> pFloating( dimsX );
for ( int pZ = taskIdx; pZ < dimsZ; pZ += taskCnt )
{
for ( int pY = 0; pY < dimsY; ++pY )
{
constThis->m_Transformation.GetTransformedGridRow( dimsX, &pFloating[0], 0, pY, pZ );
size_t r = dimsX * (pY + dimsY * pZ );
for ( int pX = 0; pX < dimsX; ++pX, ++r )
{
// Continue metric computation.
This->ContinueMetricStoreReformatted( metricData, r, pFloating[pX] );
}
}
}
This->m_MetricDataMutex.Lock();
This->m_MetricData += metricData;
This->m_MetricDataMutex.Unlock();
}
template<class TMetricFunctional>
void
SplineWarpMultiChannelRegistrationFunctional<TMetricFunctional>
::EvaluateWithGradientThreadFunction( void* args, const size_t taskIdx, const size_t taskCnt, const size_t threadIdx, const size_t )
{
EvaluateGradientThreadParameters* params = static_cast<EvaluateGradientThreadParameters*>( args );
Self* This = params->thisObject;
const Self* constThis = This;
const size_t numberOfParameters = This->VariableParamVectorDim();
const size_t numberOfControlPoints = numberOfParameters / 3;
SplineWarpXform::SmartPtr transformation = constThis->m_ThreadTransformations[threadIdx];
transformation->SetParamVector( *(params->m_ParameterVector) );
for ( size_t cp = taskIdx; cp < numberOfControlPoints; cp += taskCnt )
{
typename Superclass::MetricData localMetricDataCP = constThis->m_MetricData;
This->BacktraceMetric( localMetricDataCP, constThis->m_VolumeOfInfluenceVector[cp] );
size_t idx = 3 * cp;
for ( int dim = 0; dim < 3; ++dim, ++idx )
{
if ( constThis->m_StepScaleVector[idx] <= 0 )
{
params->m_Gradient[idx] = 0;
}
else
{
const Types::Coordinate vOld = transformation->GetParameter( idx );
Types::Coordinate thisStep = params->m_Step * constThis->m_StepScaleVector[idx];
typename Superclass::MetricData localMetricData = localMetricDataCP;
transformation->SetParameter( idx, vOld + thisStep );
double upper = This->EvaluateIncremental( transformation, localMetricData, constThis->m_VolumeOfInfluenceVector[cp] );
localMetricData = localMetricDataCP;
transformation->SetParameter( idx, vOld - thisStep );
double lower = This->EvaluateIncremental( transformation, localMetricData, constThis->m_VolumeOfInfluenceVector[cp] );
transformation->SetParameter( idx, vOld );
if ( constThis->m_JacobianConstraintWeight > 0 )
{
double lowerConstraint = 0, upperConstraint = 0;
transformation->GetJacobianConstraintDerivative( lowerConstraint, upperConstraint, idx, constThis->m_VolumeOfInfluenceVector[cp], thisStep );
lower -= constThis->m_JacobianConstraintWeight * lowerConstraint;
upper -= constThis->m_JacobianConstraintWeight * upperConstraint;
}
if ( finite( upper ) && finite(lower) && ((upper > params->m_MetricBaseValue ) || (lower > params->m_MetricBaseValue)) )
{
params->m_Gradient[idx] = upper-lower;
}
else
{
params->m_Gradient[idx] = 0;
}
}
}
}
}
} // namespace cmtk
|
