case class MeanSquaresMetric[D, A](fixedImage: Field[D, A], movingImage: DifferentiableField[D, A], transformationSpace: TransformationSpace[D], sampler: Sampler[D])(implicit evidence$1: NDSpace[D], evidence$2: Scalar[A]) extends MeanPointwiseLossMetric[D, A] with Product with Serializable
The mean squares image to image metric. It is implemented as the squared loss function in terms of the pointwise pixel differences.
Linear Supertypes
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- MeanSquaresMetric
- Serializable
- Product
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- MeanPointwiseLossMetric
- ImageMetric
- RegistrationMetric
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Visibility
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Instance Constructors
- new MeanSquaresMetric(fixedImage: Field[D, A], movingImage: DifferentiableField[D, A], transformationSpace: TransformationSpace[D], sampler: Sampler[D])(implicit arg0: NDSpace[D], arg1: Scalar[A])
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##(): Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
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- protected[lang]
- Definition Classes
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- def derivative(parameters: DenseVector[Double]): DenseVector[Double]
Computes the derivative of the metric at the point given by the parameters.
Computes the derivative of the metric at the point given by the parameters.
- Definition Classes
- MeanPointwiseLossMetric → RegistrationMetric
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
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- Annotations
- @throws(classOf[java.lang.Throwable])
- val fixedImage: Field[D, A]
- Definition Classes
- MeanSquaresMetric → ImageMetric
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def lossFunction(v: A): Double
- Attributes
- protected
- Definition Classes
- MeanSquaresMetric → MeanPointwiseLossMetric
- def lossFunctionDerivative(v: A): Double
- Attributes
- protected
- Definition Classes
- MeanSquaresMetric → MeanPointwiseLossMetric
- val movingImage: DifferentiableField[D, A]
- Definition Classes
- MeanSquaresMetric → ImageMetric
- val ndSpace: NDSpace[D]
- Definition Classes
- MeanSquaresMetric → MeanPointwiseLossMetric → RegistrationMetric
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
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- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
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- Annotations
- @native()
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val sampler: Sampler[D]
- val scalar: Scalar[A]
- Definition Classes
- MeanSquaresMetric → ImageMetric
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- val transformationSpace: TransformationSpace[D]
- Definition Classes
- MeanSquaresMetric → RegistrationMetric
- def value(parameters: DenseVector[Double]): Double
Computes the metric value for the given parameter vector
Computes the metric value for the given parameter vector
- Definition Classes
- MeanPointwiseLossMetric → RegistrationMetric
- def valueAndDerivative(parameters: DenseVector[Double]): ValueAndDerivative
Computes value and derivative in one go.
Computes value and derivative in one go. It should be the same as calling value and takeDerivative separately, but allows for more efficient implementations.
- Definition Classes
- MeanPointwiseLossMetric → RegistrationMetric
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()