SimpleITK Fundamental Concepts

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Presentation transcript:

SimpleITK Fundamental Concepts Ziv Yaniv1,2 , Bradley C. Lowekamp1,2 1National Institutes of Health 2Medical Science and Computing LLC

Transforms All global transformation are of the form*: *Except translation.

Transforms Free-Form Deformation: You set: sparse grid of control points with uniform spacing, B0..3 cubic B-spline basis functions. You set: Spline order (default is cubic) Number of grid points per axis (mesh size) Spatial domain manually: origin; physical dimension; direction cosine matrix image based: BSplineTransformInitializerFilter Transformation is identity outside the user defined domain.

Transforms Displacement Field: Dense set of vectors representing the displacement in a given spatial domain. You set: Spatial domain and deformation: manually: origin; physical dimension; direction cosine matrix; vector values. image based: vector image which is emptied of its contents. Transformation is identity outside the user defined domain.

Transforms Composite transformation: Represents multiple transformations applied one after the other. T0(T1(T2(…Tn(p)...))) Stack based semantics – first in last applied. composite_transform = sitk.Transform(T0) composite_transform.AddTransform(T1) When used as the optimized transformation in registration (SetInitialTransform), only the parameters of the last transformation, Tn, are optimized.

Images An image is defined by: Pixel type + spatial dimensionality. Physical region in space occupied by the image as specified by: origin, spacing, size, and direction cosine matrix.

Images SimpleITK2Numpy: Numpy2SimpleITK: sitk.GetArrayFromImage – Data copied into numpy array (mutable). sitk.GetArrayViewFromImage – numpy array view of image data (immutable). Numpy2SimpleITK: Copy bulk pixel data into SimpleITK image: new_image = sitk.GetImageFromArray Set all of the parameters defining the physical region in space: new_image.CopyInformation or new_image.SetOrigin, new_image.SetSpacing, new_image.SetDirection Caution: If SimpleITK image is released the array view memory is no longer valid.

Resample: Image + Transform Resampling, three elements (assuming arbitrary interpolation method): Image – the image we resample in coordinate system m. transformation – T(fp) = mp maps points from coordinate system f to m. resampling grid – uniform set of points which will be mapped by the transformation.

Resample: Image + Transform Specifying the resampling grid Use an existing image. Use origin, size, spacing, and direction cosine. Unexpected results: errors in resampling grid specification or transformation.

Registration – Coordinate Systems Three coordinate systems: Fixed, Virtual, Moving. Three transformations: Tf(vp) = fp Tm(vp) = mp Topt(mp) = mp’ Most often Tf=I, the fixed and virtual coordinate systems coincide.

Registration - Framework Optimizers: Exhaustive Nelder-Mead Simplex/Amoeba Powell 1+1 evolutionary GradientDescent GradientDescentLineSearch RegularStepGradientDescent ConjugateGradientLineSearch L-BFGS-B L-BFGS-2 Similarity metrics: MeanSquares Demons Correlation ANTSNeighborhoodCorrelation JointHistogramMutualInformation MattesMutualInformation Multi-resolution framework. Masks. Sampling strategies.