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Gleb Orlikov
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Software Engineering Department Department of Nuclear Medicine Rambam Health Care Campus
Nuclear Medicine Nuclear medicine is a branch of medical imaging that uses small amounts of radioactive material to diagnose and determine the severity of treat or a variety of diseases.
Nuclear Medicine – PET/CT camera
PET/CT camera QA Test
QA testing of PET camera The Nuclear Medicine Accreditation Committee Standards PET Phantom Phantom image
QA testing of PET camera Testing Result: Image including calculated values such as: minValue maxValue Mean Ratios
The goal The project goal is to automate PET/SPECT cameras QA procedure in order to reduce time.
Possible Problems Bad slice: Good slice:
Our application Application does the following steps: • Define template (mask). • Choose the “best” slice. • Fit the template to the PET image slice. • Calculate values and generate report.
Find the “best” slice Problem: Choose “best” slice from all slices, given by the camera Solution: Walk through all PET Dicom images, adjust contrasts (leave only HOT rods) and find circles using HOUGH algorithm.
Template definition Problem: Find ROIs on Best PET slice. Solution: Apply the PHANTOM MASK on the Best PET slice to get ROIs.
Fit the MASK Problem: Fit the PHANTOM MASK to the PET image slice. Solution: Scale the MASK and apply (move/rotate) on the image.
Use case diagram
Class diagram + CenterClosingCT(img : Image<Gray, Byte>) : Image<Gray, Byt... + ClosingImage(img : Image<Gray, Byte>, erodeElement : IntPtr,... + ConvertFromImageCoordinates(img : Image<Gray, Byte>, pnt ... + FindBestSlice(slices : List<DicomFile>, mask : CircleMask) : Dico... + FitCircleMask(img : Image<Gray, Byte>, msk : CircleMask) : Circ... + MakeBinaryImage(img : Image<Gray, Byte>, intensityThreshol... + SearchPhantomCenter(image : Image<Gray, Byte>, cannyThre... + SearchPhantomRadius(image : Image<Gray, Byte>, cannyThre... - shapes : List<Shape> + CircleMask(shapes : List<Shape>) + CircleMask(center : PointF, radius : Single, shapes :...
Class diagram cont. + lstReturn : List<Di... - allList : List<DicomF... + ChooseSeries(strLi... - SortList(list : List<D... - masks : Dictionary<... - PETimagesList : List... - PETimagesList3D : L... - SortList(list : List<D... - allList : List<DicomF... + SliceFitForm(allList ... - PETimagesList : List... - SortList(list : List<D... - shapes : Dictionary...
GUI – Main window
GUI – Select series
GUI – Manual MASK adjustment
GUI – Options
GUI – MASK generator
GUI – Help
Testing • GUI Testing. • QA Test results testing (comparing received results from the system with the test result made by physicians).
Final Conclusions • In a work with image processing, you need to pay attention that the image processing result generally are not accurate, and if there is a need in precision you need to try additional techniques in order to double check your results. • If there are similar images but with different quality you need to adjust the contrast in order to improve your image. • Our work was based only on two kinds of GE cameras, so the project is oriented for them. Any additions may cause additional changes in algorithms and calculations.
References [1] J. P. Pluim, J. B. Maintz, and M. A. Viergever, ‘‘Image registration by maximization of combined mutual information and gradient information,’’IEEE Trans. Med. Imaging 19, 809– 814 ~2000. [2] W. M. Wells III, P. Viola, H. Atsumi, S. Nakajima, and R. Kikinis, ‘‘Multi-modal volume registration by maximization of mutual information,’’ Med. Image Anal 1, 35–51 ~1996. [3] Matthew Y. Wang, Calvin R. Maurer, Jr., J. Michael Fitzpatrick,* Member, IEEE, and Robert J. Maciunas, “IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 43, NO. 6, JUNE 1996.” [4] Use of the Hough transformation to detect lines and curves in pictures. Technical note 36. April 1971. By: Richard O.Duda and Peter E. Hart. Artificial intelligence center.
Questions ???

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Project_A_presentation

  • 1. Software Engineering Department Department of Nuclear Medicine Rambam Health Care Campus
  • 2. Nuclear Medicine Nuclear medicine is a branch of medical imaging that uses small amounts of radioactive material to diagnose and determine the severity of treat or a variety of diseases.
  • 3. Nuclear Medicine – PET/CT camera
  • 5. QA testing of PET camera The Nuclear Medicine Accreditation Committee Standards PET Phantom Phantom image
  • 6. QA testing of PET camera Testing Result: Image including calculated values such as: minValue maxValue Mean Ratios
  • 7. The goal The project goal is to automate PET/SPECT cameras QA procedure in order to reduce time.
  • 9. Our application Application does the following steps: • Define template (mask). • Choose the “best” slice. • Fit the template to the PET image slice. • Calculate values and generate report.
  • 10. Find the “best” slice Problem: Choose “best” slice from all slices, given by the camera Solution: Walk through all PET Dicom images, adjust contrasts (leave only HOT rods) and find circles using HOUGH algorithm.
  • 11. Template definition Problem: Find ROIs on Best PET slice. Solution: Apply the PHANTOM MASK on the Best PET slice to get ROIs.
  • 12. Fit the MASK Problem: Fit the PHANTOM MASK to the PET image slice. Solution: Scale the MASK and apply (move/rotate) on the image.
  • 14. Class diagram + CenterClosingCT(img : Image<Gray, Byte>) : Image<Gray, Byt... + ClosingImage(img : Image<Gray, Byte>, erodeElement : IntPtr,... + ConvertFromImageCoordinates(img : Image<Gray, Byte>, pnt ... + FindBestSlice(slices : List<DicomFile>, mask : CircleMask) : Dico... + FitCircleMask(img : Image<Gray, Byte>, msk : CircleMask) : Circ... + MakeBinaryImage(img : Image<Gray, Byte>, intensityThreshol... + SearchPhantomCenter(image : Image<Gray, Byte>, cannyThre... + SearchPhantomRadius(image : Image<Gray, Byte>, cannyThre... - shapes : List<Shape> + CircleMask(shapes : List<Shape>) + CircleMask(center : PointF, radius : Single, shapes :...
  • 15. Class diagram cont. + lstReturn : List<Di... - allList : List<DicomF... + ChooseSeries(strLi... - SortList(list : List<D... - masks : Dictionary<... - PETimagesList : List... - PETimagesList3D : L... - SortList(list : List<D... - allList : List<DicomF... + SliceFitForm(allList ... - PETimagesList : List... - SortList(list : List<D... - shapes : Dictionary...
  • 16. GUI – Main window
  • 17. GUI – Select series
  • 18. GUI – Manual MASK adjustment
  • 20. GUI – MASK generator
  • 22. Testing • GUI Testing. • QA Test results testing (comparing received results from the system with the test result made by physicians).
  • 23. Final Conclusions • In a work with image processing, you need to pay attention that the image processing result generally are not accurate, and if there is a need in precision you need to try additional techniques in order to double check your results. • If there are similar images but with different quality you need to adjust the contrast in order to improve your image. • Our work was based only on two kinds of GE cameras, so the project is oriented for them. Any additions may cause additional changes in algorithms and calculations.
  • 24. References [1] J. P. Pluim, J. B. Maintz, and M. A. Viergever, ‘‘Image registration by maximization of combined mutual information and gradient information,’’IEEE Trans. Med. Imaging 19, 809– 814 ~2000. [2] W. M. Wells III, P. Viola, H. Atsumi, S. Nakajima, and R. Kikinis, ‘‘Multi-modal volume registration by maximization of mutual information,’’ Med. Image Anal 1, 35–51 ~1996. [3] Matthew Y. Wang, Calvin R. Maurer, Jr., J. Michael Fitzpatrick,* Member, IEEE, and Robert J. Maciunas, “IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 43, NO. 6, JUNE 1996.” [4] Use of the Hough transformation to detect lines and curves in pictures. Technical note 36. April 1971. By: Richard O.Duda and Peter E. Hart. Artificial intelligence center.