This document provides an overview of medical image registration using SimpleITK. It first discusses relevant DICOM image metadata fields like pixel data, bits allocated, and image orientation. It then defines image registration as aligning a target image to a source image using a transform and optimization process. Finally, it outlines the SimpleITK registration framework which loads images, applies an initial transform, uses a metric and optimizer to improve alignment between fixed and moving images.

1. 1
Image Registration by using
SimpleITK
Macy Kung
2019/06/06

2. 2
Outline
- Foreword
- DICOM Image Information
- Pixel Data
- Bits Allocated
- Bits Stored
- High Bit
- pixel Representation
- Image position (patient)
- Image orientation (patient)
- Pixel Spacing
- Spacing Between Slices
- Slice Thickness
- Image Registration
- SimpleITK Image Registration Framework

3. 3
Foreword
- Doctors using medical image annotation tools need to mark the same
series of images at the same time.
- Tools support image registration to help
doctors mark symptoms.
- Interpret various medical images to
help doctors find lesions in the clinic.
CT MRI Fused image
CTPET Fused image
MRI SPECT Fused image

4. 4
DICOM - Pixel Data (7FE0,0010)
- Pixel data The pixel order of each image plane is encoded from
left to right, top to bottom

5. 5
DICOM - Bits Allocated (0028,0100)
- Number of bits allocated for each pixel sample. Each sample shall
have the same number of bits allocated.
- Bits Allocated (0028,0100) shall either be 1, or a multiple of 8.
- 8bit (2 bytes) 2^8
- 16bit 2^16

6. 6
DICOM - Bits Stored (0028,0101)
- Number of bits stored for each pixel sample. Each sample shall
have the same number of bits stored.
- Bits Stored (0028,0101) defines the total number of these
allocated bits that will be used to represent a Pixel Sample
Value.
- Bits Stored (0028,0101) shall never be larger than Bits Allocated
(0028,0100).

7. 7
DICOM - High Bit (0028,0102)
- High Bit (0028,0102) specifies where the high order bit of the
Bits Stored (0028,0101) is to be placed with respect to the Bits
Allocated (0028,0100) specification.
- High Bit (0028,0102) shall be one less than Bits Stored
(0028,0101).

8. 8
DICOM - Pixel Representation (0028,0103)
- Pixel sample 是 0001H(2’s complement) or 0000H(unsigned integer)
- 2’s complement
- if High Bit is 11, the range of High Bit for Bits Stored is -
2048(2^11)~2047(2^11-1)
- unsigned integer
- 0~(2^11 - 1)

9. 9
DICOM - Image Position (Patient) (0020,0032)
- Describe the coordinates of the first pixel of the image ("top
left")
- The first pixel of each slice ("upper left") (x, y, z) triple

10. 10
DICOM - Image Orientation (Patient) (0020,0037)
- Specifies the direction cosine of the first row and the first
column relative to the patient. The first three x, y, and z axis
values are rows, and the last three x, y, and z axis values are
columns, which exist in pairs.
- (1,0,0,0,1,0)
X+
X-
Z+
Z-
Y+
Y-

11. 11
- Transverse plane(1,0,0,0,1,0)
- Coronal plane(1,0,0,0,0,-1)
- Sagittal plane(0,1,0,0,0,-1)
Coronal Cut
Saggital Cut Transverse(Axial) Cut

12. 12
DICOM - Pixel Spacing (0028,0030)
- The distance between the center points of the pixels, in mm
- All attributes related to pixel spacing should have positive non-
zero values unless there are pixels with only a single row or
column or data, in which case the corresponding value can be zero
Pixel Spacing = Row Spacing Column Spacing = 0.300.25

13. 13
DICOM - Spacing Between Slices (0018,0088)
- Distance between slices
MRI sequence with 5.5 mm spacing between slices.

14. 14
DICOM - Slice Thickness (0018,0050)
- The thickness of the slice in mm
Slice thickness
eq. 6mm

15. 15
Image Registration
- The process of aligning a target image to a source image
- More generally, determining the transform that maps points in the
target image to points in the source image

16. 16
SimpleITK Registration Framework
- 2 input images, fixed and moving
- Transform - map the coordinate (x, y) of an image to a new
coordinate (x′,y′).
- Metric - determines the “fitness” of the current registration
iteration
- Optimizer - adjust the transform in an attempt to improve the
metric
- Interpolator - applies transform to image and computes sub-pixel
values

17. 17
Transform Type
- Rigid (rotate, translate)
- Affine (rigid + scale & shear)
- Deformable =
non-rigid (affine + vector field)
- Many others

18. 18
SimpleITK - How to process image registration
- load DICOM, 2 series
- specific fixed image and moving image
- stored to mha data
- special medicine image format used in ITK
- initial transform
- optimizer
Group the series
with the same Image
Orientation Patient
under study
Aligning one series
or more series
(moving) to another
series (fixed)

19. 19
Thanks to all the pictures of scholars from the google network like
papers, bloggers, DICOM NEMA
Sorry, no source is attached.
Don't learn from me :P