1. MEGN 536 – Computational Biomechanics
Prof. Anthony J. Petrella
Basics of Medical Imaging
Introduction to Simpleware Software

2. Medical Imaging
Used for measuring anatomical structures… size, shape, relative position in body
Can reconstruct geometry for modeling purposes
X-ray techniques
planar x-rays, mammography, chest x-ray, bone fracture
CT scans – computed tomography
Nuclear imaging, radioactive isotope
planar imaging, bone scan
positron emission tomography (PET)
MRI – magnetic resonance imaging
Ultrasound

3. Medical Imaging Ionizing Non-ionizing Broken molecular
Ultrasound (~1mm)
Ionizing
Non-ionizing
Broken molecular
bonds, DNA damage
May produce heating,
induce currents
Non-thermal, low
induction

4. X-ray Imaging (Roentgenogram)
Wilhelm Röntgen ( )
Nov 1895, announces X-ray discovery
Jan 1896, images needle in patient’s hand
1901, receives first Nobel Prize in Physics
Röntgen’s wife, 1895

5. X-ray Imaging
X-ray film shows intensity as a negative ( dark areas, high x-ray detection)

6. X-ray Imaging
X-ray film shows intensity as a negative ( dark areas, high x-ray detection) = radiolucency

7. CT Imaging Computed tomography
Tomography – imaging by sections or sectioning, creation of a 2D image by taking a slice through a 3D object
2D images are captured with X-ray techniques
X-ray source is rotated through 360° and images are taken at regular intervals
CT image is computed from X-ray data

8. CT Imaging
Developed by Sir Godfrey Hounsfield, engineer for EMI PLC 1972
Nobel Prize 1979 (with Alan Cormack)
“Pretty pictures, but they will never replace radiographs” –Neuroradiologist 1972
early
today

9. Inhalation
Exhalation

10. How a CT Image is Formed
X-ray source is rotated around body for each slice
Patient is moved relative to the beam
Figure below does not show it well, but the X-ray beam has a thickness  each slice has a thickness
Note: slice thickness

11. How a CT Image is Formed Figures below show only two views 90° apart
A process of “back projection” is used to indicate regions where X-ray attenuation is greater – i.e., tissue is more dense

12. How a CT Image is Formed
Example at left w/ only 2 views shows poor image
Clinical CT uses several hundred views for each slice
Data collected in matrix

13. CT Image Data
Recall that each CT slice has a thickness  each element in the data matrix for a single CT slice represents a measurement of X-ray attenuation for a small volume or “voxel” of tissue
X-ray attenuation is expressed in terms of the X-ray attenuation coefficient, which is dependent primarily on tissue density

14. CT Numbers
CT numbers are expressed in Hounsfield units (HU) and normalized to the attenuation coefficient of water
(atomic number)

15. CT Numbers & Viewing a CT Image
CT numbers usually recorded as 12-bit binary number, so they have 212 = 4096 possible values
Values arranged on a scale from HU to HU
Scale is callibrated so air gives a value of HU and water has a CT number of 0 HU
Dense cortical bone falls in the to HU range HU HU

16. MR Imaging Magnetic resonance imaging
1946: Felix Block and Edward Purcell discover magnetic resonance
: Richard Ernst and Peter Mansfifield develop MR imaging
An object is exposed to a spatially varying magnetic field, causing certain atomic nuclei to spin at their resonant frequencies
An electromagnetic signal is generated and varies with spatial position and tissue type
Hydrogen is commonly measured – hence, good contrast for soft tissues that contain more water than hard tissues like bone

17. MR Imaging – 30 Years Later
“Interesting images, but will never be as useful as CT” –Neuroradiologist (different), 1982
First brain MR image
Contemporary Image

18. Notes on CT v. MR Images
CT image based on X-ray beam attenuation, depends on tissue density
CT images generally regarded as better for visualization & contrast in bone imaging
Bone density and modulus can be estimated
MR image based on resonance of certain atomic nuclei, e.g. hydrogen
MR images generally regarded as better for visualization & contrast in imaging soft tissues, which contain more water than bone

19. 3D Reconstruction
CT & MR images represent 2D slices through 3D anatomic structures
2D slices can be “stacked” and reconstructed to form an estimate of the original 3D structure

20. Simpleware Software
Simpleware ( is a leading commercial software program for reconstruction of CT & MR image data

21. What Data Format Does Simpleware Read?
Most medical images are saved in the DICOM image format
What is DICOM?
The standard for Digital Imaging and Communications in Medicine
Developed by the National Electrical Manufacturers Association (NEMA) in conjunction with the American College of Radiology (ACR)
Covers most image formats for all of medicine
Specification for messaging and communication between imaging machines
You don’t need to know the details of the format, but software is happiest when reading DICOM images

22. What If You Don’t Have DICOM Data?
DePuy Orthopaedics, Inc.
Feb 2005
What If You Don’t Have DICOM Data?
You will need to use manual input methods with to read the data
You need to know something about the images
A CT or MR scan consists of many slices
We will be focused on bone modeling, so CT data will be our main interest
It is also important to remember how a CT image slice is formed and what data it contains
CONFIDENTIAL

23. Data in an Image File
The format of CT numbers in the data file depends on the precision of the binary data
For CT numbers, we only need to cover the 12-bit range, to 3071
short has 2 bytes = 2 × 8 bits/byte = 216 binary values = 65,536
When using unsigned shorts the data is shifted so all CT numbers are positive  0 to 4095

24. Data in an Image File Recall a single CT slice is a matrix of data
512 x 512 is a common size  262,144 pixels
Each element in the matrix represents a pixel value with a binary format of “short”, therefore each pixel contains 2 bytes of data
262,144 x 2 = 524,288 bytes, any additional data is part of the “header”

25. Data in an Image File Visible Human link on class website
Data are available for download
Download sample of Visible Human data from today’s Class Notes page
These images are 512 x 512 and the data format is unsigned short
How large is the header (bytes)?

26. Data in an Image File 512 x 512 = 262,144 pixels
Each element in the matrix represents a pixel value with a binary format of “short”, therefore each pixel contains 2 bytes of data
262,144 x 2 = 524,288 bytes, any additional data is part of the “header”
Total file size is 527,704  header is 3416 bytes

27. Starting Simpleware DO NOT use the search box on the Start menu
You should find a ScanIP icon in the EG Apps folder
Run Simpleware with the ScanIP icon
Since we do not have a DICOM dataset, choose to Import Raw Stack

28. Importing Vizible Human CT Data
Download ZIP file from class notes page and uncompress in a separate folder
Use following settings to import raw stack…

29. Working with Vizible Human Data
Now you are ready to work on reconstructing geometry of the knee (next time)

30. Simpleware Tutorials
Find tutorial and reference guide under Welcome tab

31. Simpleware Tutorials
Complete Tutorial Chapter 7 to learn basics of segmentation and meshing