forked from InsightSoftwareConsortium/ITK
-
Notifications
You must be signed in to change notification settings - Fork 0
/
itkMRIBiasFieldCorrectionFilter.h
617 lines (490 loc) · 24 KB
/
itkMRIBiasFieldCorrectionFilter.h
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
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkMRIBiasFieldCorrectionFilter.h
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkMRIBiasFieldCorrectionFilter_h
#define __itkMRIBiasFieldCorrectionFilter_h
#include <time.h>
#include "itkImageToImageFilter.h"
#include "itkImage.h"
#include "itkArray2D.h"
#include "itkMRASlabIdentifier.h"
#include "itkCompositeValleyFunction.h"
#include "itkMultivariateLegendrePolynomial.h"
#include "Statistics/itkNormalVariateGenerator.h"
#include "itkOnePlusOneEvolutionaryOptimizer.h"
#include "itkArray.h"
#include "itkImageRegionConstIterator.h"
#include "itkImageRegionIterator.h"
namespace itk
{
/** \class MRIBiasEnergyFunction
* \brief a cost function for optimization
*
* This is a wrapping class which provides interfaces between images,
* the bias field, the internal energy function (CompositeValleyFunction),
* and the Optimizer.
*
* This class is templated over the type of the input image (TImage),
* the image mask (which tells which pixels in the input image should be
* included for energy value calculation), and the bias field (TBiasField).
*/
template<class TImage, class TImageMask, class TBiasField>
class MRIBiasEnergyFunction : public SingleValuedCostFunction
{
public:
/** Standard class typedefs. */
typedef MRIBiasEnergyFunction Self;
typedef SingleValuedCostFunction Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Run-time type information (and related methods). */
itkTypeMacro( MRIBiasEnergyFunction, SingleValuedCostFunction );
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Image related type definitions. */
typedef TImage ImageType ;
typedef TImageMask MaskType ;
typedef typename ImageType::Pointer ImagePointer ;
typedef typename MaskType::Pointer MaskPointer ;
typedef typename ImageType::PixelType ImageElementType ;
typedef typename MaskType::PixelType MaskElementType ;
typedef typename ImageType::IndexType ImageIndexType ;
typedef typename ImageType::RegionType ImageRegionType ;
/** Bias field type definition. */
typedef TBiasField BiasFieldType;
/** Parameters type for optimizier (coefficients type for bias
* field estimate). */
typedef typename Superclass::ParametersType ParametersType ;
/** Not used, but expected by SingleValuedNonLinearOptimizer class. */
typedef Superclass::DerivativeType DerivativeType;
/** The cost value type. */
typedef Superclass::MeasureType MeasureType;
itkStaticConstMacro(SpaceDimension, unsigned int, 3);
/** The type of the internal energy function. */
typedef CompositeValleyFunction InternalEnergyFunction ;
/** The type of the sampling factors */
typedef unsigned int SamplingFactorType[SpaceDimension];
/** Specify the input image. */
itkSetObjectMacro( Image, ImageType );
/** Specify the input mask image. */
itkSetObjectMacro( Mask, MaskType );
/** Set the image region which will be included for energy calculation. */
itkSetMacro( Region, ImageRegionType );
/** Sets the BiasField object. */
void SetBiasField(BiasFieldType* bias)
{ m_BiasField = bias ; }
/** Sets the sampling factors of the energy function in each direction.
* Default is 1 in each dimension */
void SetSamplingFactors(SamplingFactorType factor)
{
for (unsigned int i = 0; i < SpaceDimension; i++)
{
m_SamplingFactor[i] = factor[i];
}
}
/** Get an energy value for the intensity difference between a pixel
* and its corresponding bias. */
double GetEnergy0(double diff)
{
return (*m_InternalEnergyFunction)(diff);
}
/** Gets the total energy value of an image or a slice using the
* given parameters. */
MeasureType GetValue(const ParametersType & parameters ) const ;
/** Dummy implementation to confirm to the SingleValuedCostFunction
* interfaces. It is pure virtual in the superclass */
void GetDerivative( const ParametersType & itkNotUsed(parameters),
DerivativeType & itkNotUsed(derivative) ) const
{ }
/** Set Mean and Sigma for the normal distributions
* \warning This method MUST be called before any attemp to
* evaluate the Function because it instantiate the internal
* energy function */
void InitializeDistributions( Array<double> classMeans,
Array<double> classSigmas );
unsigned int GetNumberOfParameters(void) const;
private:
/** Bias field object pointer. */
BiasFieldType * m_BiasField ;
/** Input image smart pointer. */
ImagePointer m_Image ;
/** Input mask image smart pointer. */
MaskPointer m_Mask ;
/** Region of interest. */
ImageRegionType m_Region ;
/** Internal energy function object pointer. */
InternalEnergyFunction* m_InternalEnergyFunction ;
/** Sampling factors */
SamplingFactorType m_SamplingFactor;
protected:
/** Constructor: */
MRIBiasEnergyFunction();
/** Destructor: */
virtual ~MRIBiasEnergyFunction();
private:
MRIBiasEnergyFunction(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
} ; // end of class
/** \class MRIBiasFieldCorrectionFilter
* \brief corrects 3D MRI bias field
*
* This class is templated over the type of the input image (TInputImage)
* and the type of the output image (TOutputImage).
*
* In MRI images, intensity inhomogenieties which are caused by
* magnetic settings, patients' postion, and other factors are not
* unusual. The main purpose of this filter is to reduce such bias field.
* To estimate the bias field, we use Legendre
* polynomials. The 1+1 evolutionary optimizer searches for the best
* paramters of a Legendre polynomial (bias field estimate) which
* minimizes the total energy value of each image after bias field
* is eleminated. The default Legendre polynomial degree is 3.
*
* The correction performes by default a multiplicative bias field correction
* by first log-transforming the input image. This log transform only
* works on images with grayscale values bigger than 0. The log-transform
* can be disabled and the filter computes an additive bias field.
*
* There are three major processes in the whole bias correction scheme:
* slab identification, inter-slice intensity correction, and
* actual bias correction process.
* Users can turn on and off each process within the whole bias
* correction scheme using SetUsingSlabIdentification(bool, false by default),
* SetUsingInterSliceIntensityCorrection(bool, true by default), and
* SetUsingBiasFieldCorrection(bool, true by default) member function.
*
* Only the last process (the actual bias field correction) is implemented in a
* multiresolution framework (without smoothing). Default is a standard level 2
* multiresolution schedule (2 2 2 1 1 1)
*
* The bias field correction method was initially developed
* and implemented by Martin Styner, Univ. of North Carolina at Chapel Hill,
* and his colleagues.
*
* The multiresolution pyramid implementation is based on
* itkMultiTesolutionPyramidImageFilter (without Gaussian smoothing)
*
* For more details. refer to the following articles.
* "Parametric estimate of intensity inhomogeneities applied to MRI"
* Martin Styner, Guido Gerig, Christian Brechbuehler, Gabor Szekely,
* IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000,
* (http://www.cs.unc.edu/~styner/docs/tmi00.pdf)
*
* "Evaluation of 2D/3D bias correction with 1+1ES-optimization"
* Martin Styner, Prof. Dr. G. Gerig (IKT, BIWI, ETH Zuerich), TR-197
* (http://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)
*/
template <class TInputImage, class TOutputImage, class TMaskImage>
class ITK_EXPORT MRIBiasFieldCorrectionFilter :
public ImageToImageFilter< TInputImage, TOutputImage >
{
public:
/** Standard class typedefs. */
typedef MRIBiasFieldCorrectionFilter Self;
typedef ImageToImageFilter< TInputImage, TOutputImage > Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods) */
itkTypeMacro(MRIBiasFieldCorrectionFilter, ImageToImageFilter);
/** The dimension of the image. */
itkStaticConstMacro(ImageDimension, unsigned int,
TOutputImage::ImageDimension);
/** Input and output image related type definitions. */
typedef TOutputImage OutputImageType ;
typedef TInputImage InputImageType ;
typedef typename TOutputImage::Pointer OutputImagePointer ;
typedef typename TOutputImage::IndexType OutputImageIndexType ;
typedef typename TOutputImage::PixelType OutputImagePixelType ;
typedef typename TOutputImage::SizeType OutputImageSizeType;
typedef typename TOutputImage::RegionType OutputImageRegionType;
typedef typename TInputImage::Pointer InputImagePointer ;
typedef typename TInputImage::IndexType InputImageIndexType;
typedef typename TInputImage::PixelType InputImagePixelType;
typedef typename TInputImage::SizeType InputImageSizeType;
typedef typename TInputImage::RegionType InputImageRegionType;
/** Mask image related type definitions. */
typedef TMaskImage ImageMaskType ;
typedef typename ImageMaskType::Pointer ImageMaskPointer ;
typedef typename ImageMaskType::RegionType ImageMaskRegionType ;
/** Internal (temporary) image related type definitions. */
typedef Image< float, itkGetStaticConstMacro(ImageDimension) >
InternalImageType ;
typedef typename InternalImageType::PixelType InternalImagePixelType ;
typedef typename InternalImageType::Pointer InternalImagePointer ;
typedef typename InternalImageType::RegionType InternalImageRegionType ;
/** Regions of the MRI slab identifier return. */
typedef MRASlabIdentifier<InputImageType> MRASlabIdentifierType ;
typedef typename MRASlabIdentifierType::SlabRegionVectorType
SlabRegionVectorType ;
typedef typename SlabRegionVectorType::iterator SlabRegionVectorIteratorType ;
/** Bias field object type defintion. */
typedef MultivariateLegendrePolynomial BiasFieldType;
/** Energy function type defintion. */
typedef MRIBiasEnergyFunction<InternalImageType,
ImageMaskType,
BiasFieldType> EnergyFunctionType;
typedef typename EnergyFunctionType::Pointer EnergyFunctionPointer;
/** Normal variate Generator Type */
typedef Statistics::NormalVariateGenerator NormalVariateGeneratorType ;
/** Optimizer type definition. */
typedef OnePlusOneEvolutionaryOptimizer OptimizerType ;
/** ScheduleType typedef support. */
typedef Array2D<unsigned int> ScheduleType;
/** Set/Get the input mask image pointer
* Without this mask, this filter calculates the energy value using
* all pixels in the input image. */
void SetInputMask(ImageMaskType* inputMask);
itkGetObjectMacro( InputMask, ImageMaskType );
/** Sets the out mask image pointer.
* Without this mask, this filter corrects every pixel in the input image. */
void SetOutputMask(ImageMaskType* outputMask) ;
/** Gets the output mask image pointer. */
itkGetObjectMacro( OutputMask, ImageMaskType );
/** If you set this true, this filter assumes the bias field is
* multiplicative and internally uses log intensity values for
* every calculation. */
void IsBiasFieldMultiplicative(bool flag)
{ m_BiasMultiplicative = flag ; }
/** If the bias field is multiplicative, it returns true. */
bool IsBiasFieldMultiplicative()
{ return m_BiasMultiplicative ; }
/** Set/Gets the intensity correction flag. if the flag is true, inter-slice
* intensity correction will be applied before bias field
* correction. default - true (3D input image), false (2D input image). */
itkSetMacro( UsingInterSliceIntensityCorrection, bool );
itkGetConstReferenceMacro( UsingInterSliceIntensityCorrection, bool );
/** Set/Gets the slab correction flag. If the flag is true, inter-slice
* intensity correction and bias field correction will be performed slab by
* slab which is identified by the slab identifier. default - false
* NOTE: if users want to slab identification, all the input image data
* should be buffered. */
itkSetMacro( UsingSlabIdentification, bool );
itkGetConstReferenceMacro( UsingSlabIdentification, bool );
itkSetMacro( SlabBackgroundMinimumThreshold, InputImagePixelType );
itkGetConstReferenceMacro( SlabBackgroundMinimumThreshold,
InputImagePixelType );
itkSetMacro( SlabNumberOfSamples, unsigned int );
itkGetConstReferenceMacro( SlabNumberOfSamples, unsigned int );
itkSetMacro( SlabTolerance, double );
itkGetConstReferenceMacro( SlabTolerance, double );
/** Set/Gets the bias correction flag. If the flag is true, bias field
* correction runs. This flag sounds odd. But if users want to use only
* the inter-slice intensity correction without actual bias correction,
* disabling bias field correction would be an useful option. default -
* true. */
itkSetMacro( UsingBiasFieldCorrection, bool );
itkGetConstReferenceMacro( UsingBiasFieldCorrection, bool );
/** Set/Gets the flag, If the flag is true, the output image (corrected image)
* will be created when this filter is updated. default - true */
itkSetMacro( GeneratingOutput, bool );
itkGetConstReferenceMacro( GeneratingOutput, bool );
/** Sets the direction of slicing.
* 0 - x axis, 1 - y axis, 2 - z axis */
itkSetMacro( SlicingDirection , int );
/** Set/Get the degree of the bias field estimate. */
itkSetMacro( BiasFieldDegree, int );
itkGetMacro( BiasFieldDegree, int );
/** Sets the initial 3D bias field estimate coefficients that will be
* used for correcting each slab. */
void SetInitialBiasFieldCoefficients(const
BiasFieldType::CoefficientArrayType
&coefficients)
{ this->Modified() ; m_BiasFieldCoefficients = coefficients ; }
/** Get the result bias field coefficients after the bias field
* estimation (does not apply to the inter-slice intensity
* correction) */
BiasFieldType::CoefficientArrayType GetEstimatedBiasFieldCoefficients()
{ return m_EstimatedBiasFieldCoefficients ; }
/** Set the tissue class statistics for energy function initialization
* If the numbers of elements in the means and the sigmas are not equal
* it will throw exception */
void SetTissueClassStatistics(const Array<double> & means,
const Array<double> & sigmas)
throw (ExceptionObject) ;
/** Set/Get the maximum iteration termination condition parameter. */
itkSetMacro( VolumeCorrectionMaximumIteration, int );
itkGetMacro( VolumeCorrectionMaximumIteration, int );
itkSetMacro( InterSliceCorrectionMaximumIteration, int );
itkGetMacro( InterSliceCorrectionMaximumIteration, int );
/** Set/Get the initial search radius. */
void SetOptimizerInitialRadius(double initRadius)
{ m_OptimizerInitialRadius = initRadius ; }
double GetOptimizerInitialRadius()
{ return m_OptimizerInitialRadius ; }
/** Set/Get the search radius grow factor. */
itkSetMacro( OptimizerGrowthFactor, double );
itkGetMacro( OptimizerGrowthFactor, double );
/** Set/Get the search radius shrink factor. */
itkSetMacro( OptimizerShrinkFactor, double );
itkGetMacro( OptimizerShrinkFactor, double );
/** Set the number of multi-resolution levels. The matrix containing the
* schedule will be resized accordingly. The schedule is populated with
* default values. At the coarset (0) level, the shrink factors are set
* 2^(nlevel - 1) for all dimension. These shrink factors are halved for
* subsequent levels. The number of levels is clamped to a minimum value
* of 1. All shrink factors are also clamped to a minimum value of 1. */
void SetNumberOfLevels(unsigned int num);
/** Get the number of multi-resolution levels. */
itkGetMacro(NumberOfLevels, unsigned int);
/** Set a multi-resolution schedule. The input schedule must have only
* ImageDimension number of columns and NumberOfLevels number of rows. For
* each dimension, the shrink factor must be non-increasing with respect to
* subsequent levels. This function will clamp shrink factors to satisify
* this condition. All shrink factors less than one will also be clamped
* to the value of 1. */
void SetSchedule( const ScheduleType& schedule );
/** Get the multi-resolution schedule. */
itkGetConstReferenceMacro(Schedule, ScheduleType);
/** Set the starting shrink factor for the coarset (0) resolution
* level. The schedule is then populated with defaults values obtained by
* halving the factors at the previous level. All shrink factors are
* clamped to a minimum value of 1. */
void SetStartingShrinkFactors( unsigned int factor );
void SetStartingShrinkFactors( unsigned int* factors );
/** Get the starting shrink factors */
const unsigned int * GetStartingShrinkFactors() const;
/** Test if the schedule is downward divisible. This method returns true if
* at every level, the shrink factors are divisble by the shrink factors at
* the next level. */
static bool IsScheduleDownwardDivisible( const ScheduleType& schedule );
/** Initializes the energy function object and optimizer objects and
* creates the internal image object copying the input image data to it.
* Also, if the bias field is multiplicative, applies logarithm to pixel
* intensity values, tissue classes' statistics values and the optimizer's
* initial radius NOTE: If the tissue class statistics values (mean and
* sigma values) then it will throw exception. */
void Initialize() throw (ExceptionObject) ;
/** Optimizes the bias field only using the image data that are in
* the specified region. */
BiasFieldType EstimateBiasField(InputImageRegionType region,
unsigned int degree,
int maximumIteration) ;
/** Correct the internal image using the bias field estimate
* created by EstimateBiasField() member function and the internal image
* data that are in the specified region. */
void CorrectImage(BiasFieldType& bias,
InputImageRegionType region) ;
/** Internally calls EstimateBiasField() and CorrectImage() member functions
* for each slice to correct inter-slice intensity inhomogeneities. */
void CorrectInterSliceIntensityInhomogeneity(InputImageRegionType region) ;
protected:
MRIBiasFieldCorrectionFilter() ;
virtual ~MRIBiasFieldCorrectionFilter() ;
void PrintSelf(std::ostream& os, Indent indent) const;
/** Checks if the mask image's dimensionality and size matches with
* those of the input image */
bool CheckMaskImage(ImageMaskType* mask) ;
protected:
/** Converts image data from source to target applying vcl_log(pixel + 1)
* to all pixels. If the source pixel has negative value, it sets
* the value of the corresponding pixel in the targe image as zero. */
void Log1PImage(InternalImageType* source,
InternalImageType* target) ;
/** Converts image data from source to target applying vcl_exp(pixel) - 1
* to all pixels. */
void ExpImage(InternalImageType* source,
InternalImageType* target) ;
/** Converts pixel type, and
* copies image data from source to target. */
template<class TSource, class TTarget>
void CopyAndConvertImage(const TSource * source,
TTarget * target,
typename TTarget::RegionType requestedRegion)
{
typedef ImageRegionConstIterator<TSource> SourceIterator ;
typedef ImageRegionIterator<TTarget> TargetIterator ;
typedef typename TTarget::PixelType TargetPixelType ;
SourceIterator s_iter(source, requestedRegion) ;
TargetIterator t_iter(target, requestedRegion) ;
s_iter.GoToBegin() ;
t_iter.GoToBegin() ;
while (!s_iter.IsAtEnd())
{
t_iter.Set(static_cast<TargetPixelType>( s_iter.Get() ) ) ;
++s_iter ;
++t_iter ;
}
}
/** Converts ImageRegion type (region) to DomainSize type (std::vector)
* NOTE: if the size of the last dimension of the image region is one, then
* the dimension of the resulting domain size will be one less than that of
* he image region */
void GetBiasFieldSize(InputImageRegionType region,
BiasFieldType::DomainSizeType& domainSize) ;
/** Find overlapping regions between the slab regions and the output image's
* requested region. And then replace the original slab regions with
* the resulting overlapping regions. */
void AdjustSlabRegions(SlabRegionVectorType& slabs,
OutputImageRegionType requestedRegion) ;
void GenerateData() ;
private:
MRIBiasFieldCorrectionFilter(const Self&); //purposely not implemented
void operator=(const Self&); //purposely not implemented
/** Energy function object pointer. */
EnergyFunctionPointer m_EnergyFunction ;
/** Normal variate generator smart pointer */
NormalVariateGeneratorType::Pointer m_NormalVariateGenerator ;
/** Input mask image smart pointer. */
ImageMaskPointer m_InputMask ;
/** Output mask image smart pointer. */
ImageMaskPointer m_OutputMask ;
/** Internal image smart pointer. */
InternalImagePointer m_InternalInput ;
/** Storage for the MRI slab identifier return. */
SlabRegionVectorType m_Slabs ;
/** [0 - x, 1 - y, 2 - z]. */
int m_SlicingDirection ;
/** Bias Field character if true, multiplicative. if false, additive. */
bool m_BiasMultiplicative ;
/** operation selection flags. */
bool m_UsingInterSliceIntensityCorrection ;
bool m_UsingSlabIdentification ;
bool m_UsingBiasFieldCorrection ;
bool m_GeneratingOutput ;
unsigned int m_SlabNumberOfSamples ;
InputImagePixelType m_SlabBackgroundMinimumThreshold ;
double m_SlabTolerance ;
/** The degree of the bias field estimate. */
int m_BiasFieldDegree ;
/** The number of levels for the multires schedule */
unsigned int m_NumberOfLevels;
/** The multires schedule */
ScheduleType m_Schedule;
/** Storage for the initial 3D bias field estimate coefficients that will be
* used for correcting each slab. */
BiasFieldType::CoefficientArrayType m_BiasFieldCoefficients ;
/** Storage for the resulting 3D bias field estimate coefficients
* after optimization. */
BiasFieldType::CoefficientArrayType m_EstimatedBiasFieldCoefficients ;
/** Storage for the optimizer's maximum iteration number. */
int m_VolumeCorrectionMaximumIteration ;
/** Storage for the optimizer's maximum iteration number. */
int m_InterSliceCorrectionMaximumIteration ;
/** Storage for the optimizer's initial search radius. */
double m_OptimizerInitialRadius ;
/** Storage for the optimizer's search radius grow factor. */
double m_OptimizerGrowthFactor ;
/** Storage for the optimizer's search radius shrink factor. */
double m_OptimizerShrinkFactor ;
/** Storage for tissue classes' mean values. */
Array<double> m_TissueClassMeans ;
/** Storage for tissue classes' variance values. */
Array<double> m_TissueClassSigmas ;
};
// ==================================
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkMRIBiasFieldCorrectionFilter.txx"
#endif
#endif