CY4E2 BIONICS

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CY4E2 BIONICS

• Medical Image Processing and Analysis
• Dr Virginie F. Ruiz
• v.f.ruiz_at_reading.ac.uk
• Cybernetics, room 184

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So much to talk about!

• What is medical image processing and analysis?
• Image segmentation
• Morphological methods
• Feature extraction
• Medical image interpretation
• Validation of image analysis techniques
• Computer-aided diagnosis in mammography
• Other medical applications
• Echocardiography
• Cardiac Image Analysis motion and deformation
• Angiography and Intravascular Ultrasound
• Vascular Imaging and Analysis
• Pulmonary Imaging and Analysis
• Brain Image Analysis and Atlas Construction
• etc

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Books

• Some in the Library
• Digital Image Processing Algorithms and
  Applications, I. Pitas, Wiley
• Digital Image Processing, Castleman, Prentice
  Hall.
• Digital Image Processing, Gonzales and Woods,
  Addison Wesley
• Foundations of Medical Imaging, Z.H. Cho, Joie
  P.Jones, Manbir Singh, Wiley
• An Introduction to the principles of medical
  imaging, Chris C.N. Guy, Dominic Ffytche,
  Imperial College Press.
• The essential physics of medical imaging, Jerrod
  T. Bushberg et al., Williams Wilkins.
• IEEE Transactions on Medical Imaging.
• some more
• Handbook of Medical Imaging, M. Sanka and J. M.
  Fitzpatrick eds, SPIE Press 2000
• Vol. 1 Medical physics and psychophysics.
• Vol. 2 Medical image processing and analysis.
• Vol. 3 Display and PACs

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Medical Image Systems

• The last few decades of the 20th century has seen
  the development of
• Computed Tomography (CT)
• Magnetic Resonance Imaging (MRI)
• Digital Subtraction Angiography
• Doppler Ultrasound Imaging
• Other techniques based on nuclear emission e.g
• PET Positron Emission Tomography
• SPECT Single Photon Emission Computed Tomography
• Provide a valuable addition to radiologists
  imaging tools towards ever more reliable
  detection and diagnosis of diseases.
• More recently conventional x-ray imaging is
  challenged by the emerging flat panel x-ray
  detectors.

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• General image processing whether it is applied
  to
• Robotics
• Computer vision
• Medicine
• etc.
• will treat
• imaging geometry
• linear transforms
• shift invariance
• frequency domain
• digital vs continuous domains
• segmentation
• histogram analysis
• etc
• that apply to any image modality and any
  application

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• General image analysis regardless of its
  application area encompasses
• incorporation of prior knowledge
• classification of features
• matching of model to sub-images
• description of shape
• many other problems and approaches of AI...
• While these classic approaches to general images
  and to general applications are important, the
  special nature of medical images and medical
  applications requires special treatments.

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Special nature of medical images

• Derived from
• method of acquisition
• the subject whose images are being acquired
• Ability to provide information about the volume
  beneath the surface
• though surface imaging is used in some
  applications
• Image obtained for medical purposes almost
  exclusively probe the otherwise invisible anatomy
  below the skin.
• Information may be from
• 2D projection acquired by conventional
  radiography
• 2D slices of B-mode ultrasound
• full 3D mapping from CT, MRI, SPECT, PET and 3D
  ultrasound.

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difficulties/specificities

• Radiology perspective projection maps physical
  points into image space
• but, detection and classification of objects is
  confounded to over- and underlying tissue (not
  the case in general image processing).
• Tomography 3D images bring both complication and
  simplifications
• 3D topography is more complex than 2D one.
• problem associated with perspective and occlusion
  are gone.
• Additional limitation to image quality
• distortion and burring associated with relatively
  long acquisition time (due to anatomical motion).
• reconstruction errors associated with noise, beam
  hardening etc.
• All these and others account for the differences
  between medical and non medical approaches to
  processing and analysis.

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• Advantage of dealing with medical images
• knowledge of what is and what is not normal human
  anatomy.
• selective enhancement of specific organs or
  objects via injection of contrast-enhancing
  material.
• All these differences affect the way in which
  images are processed and analysed.
• Validation of medical image processing and
  analysis techniques is also a major part of
  medical application
• validating results is always important
• the scarcity of accurate and reliable independent
  standards create another challenge for medical
  imaging field.

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Processing and Analysis

• Medical image processing
• Deals with the development of problem specific
  approaches to enhancement of raw medical data for
  the purposes of selective visualisation as well
  as further analysis.
• Medical image analysis
• Concentrates on the development of techniques to
  supplement the mostly qualitative and frequently
  subjective assessment of medical images by human
  experts.
• Provides a variety of new information that is
  quantitative, objective and reproducible

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MRI
CT scan
Same patient
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MRI PET
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MRI angiogram
X-ray angiograms
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ultrasound
Kidney
Breast
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fMRI
UCLA Brain Mapping DivisionLos Angeles, CA 90095
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Virtual sinus endoscopy of chronic sinusitis.
The red structure means inflammatory
portion. The trip starts from right nasal cavity
and goes through right maxillary sinus and ends
at right frontal sinus.
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NeuroSurgery This animation is derived from MRI
data of a patient with a glioma
This demonstrates planning of a stereotactic
procedure using computerized simulation.
This shows three alternative approaches for a
surgical removal of the tumor.
This demonstrates registration of vessels derived
from a phase contrast angiogram and anatomy
derived from double-echo MR scans.
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Flow Analysis
Here is an example using Visage on a data source
totally different than its original design had
anticipated. In this case the data comes from an
MR scanner
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