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

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Presentation on theme: "MEGN 536 – Computational Biomechanics Prof. Anthony J. Petrella Basics of Medical Imaging Introduction to Mimics Software."— Presentation transcript:

1 MEGN 536 – Computational Biomechanics Prof. Anthony J. Petrella Basics of Medical Imaging Introduction to Mimics 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 bonds, DNA damage May produce heating, induce currents Non-thermal, low induction Ultrasound (~1mm)

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 Exhalation Inhalation

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 2 12 = 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 Mimics Software  Mimics (www.materialise.com/mimics) is the leading commercial software program for reconstruction of CT & MR image datawww.materialise.com/mimics

21 What Data Format Does Mimics 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 Mimics is happiest when reading DICOM images

22 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

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 = 2 16 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 Mimics  You should find a Mimics icon on the desktop… or  Find “Materialise Software” in Start menu… or  Type “Mimics” in the Start menu search box  Run Mimics  The software should ask if you want to reboot… click “No” or “Reboot Later”  If Mimics doesn’t start then on it’s own, attempt to start it again

28 Mimics Tutorials  Complete Lessons 1 and 2 in Mimics SE Course Book, pages 8-28  You will need the Mimics SE Course Data, which is posted on the front page of the class website  If you don’t have your Course Book, it is also posted on the class website


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