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CY4E2 BIONICS. Medical Image Processing and Analysis Dr Virginie F. Ruiz Cybernetics, room 184. So much to talk about!. What is medical image processing and analysis? Image segmentation Morphological methods Feature extraction Medical image interpretation

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cy4e2 bionics


Medical Image Processing and Analysis

Dr Virginie F. Ruiz

Cybernetics, room 184

so much to talk about
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

CY4E2: Bionics

  • 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
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

CY4E2: Bionics

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
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
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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CT scan

Same patient

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MRI angiogram

X-ray angiograms

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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.

CY4E2: Bionics



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

CY4E2: Bionics