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DICOM Network Roles

Image Send. CT Image Storage SOP Class (SCP). DICOM Network Roles. Successful communication - products must play “opposite roles” Receive images = Service Class Provider (SCP) Send images = Service Class User (SCU). CT Image Storage SOP Class (SCU).

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DICOM Network Roles

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  1. Image Send CT Image StorageSOP Class (SCP) DICOM Network Roles • Successful communication - products must play “opposite roles” • Receive images = Service Class Provider (SCP) • Send images = Service Class User (SCU) CT Image StorageSOP Class (SCU) Network roles are defined for all DICOM Functions

  2. DICOM Conformance Statement • It is Required! • It is a Public Document • It Conveys a Product’s DICOM Functionality • It is Based on DICOM Vocabulary • Abstract Syntaxes (SOP Classes), Transfer Syntaxes, SCU/SCP….. • It is Used to Compare Connectivity • It is most Often on the Web @ Vendor Site • It Does Not Address All of an Application’s Capabilities, but should Address All of the Application’s DICOM ones A Major Step Towards Interoperability

  3. Language and … dictionary 128 bit inutili (non sempre) DICM

  4. “std” DICOM

  5. (0008,0000) UL 424 # 4 IdentifyingGroupLength (0008,0020) DA [20070509] # 8 StudyDate (0008,0022) DA [20070509] # 8 AcquisitionDate (0008,0023) DA [20070509] # 8 ImageDate (0008,0030) TM [163853] # 6 StudyTime (0008,0032) TM [163933] # 6 AcquisitionTime (0008,0060) CS [CT] # 2 Modality (0008,0070) LO [Philips ] # 8 Manufacturer (0008,0080) LO [OSP S.CROCE CUNEO ] # 18 InstitutionName (0008,1040) LO [RADIOLOGIA] # 10 InstitutionalDepartmentName (0008,1090) LO [Brilliance 64 ] # 14 ManufacturerModelName (0010,0010) PN [TEST CTDI 16 CM HEAD^.] # 22 PatientName (0010,0020) LO [11111 ] # 6 PatientID (0010,0030) DA [20070509] # 8 PatientBirthDate (0010,0040) CS [O ] # 2 PatientSex (0018,0050) DS [0.5 ] # 6 SliceThickness (0018,0060) DS [120 ] # 4 KVP (0018,0090) DS [500 ] # 4 DataCollectionDiameter (0018,1030) LO [Encefalo Ax Testa ] # 22 ProtocolName (0018,1100) DS [500 ] # 4 ReconstructionDiameter (0018,1120) DS [0 ] # 2 GantryDetectorTilt (0018,1140) CS [CW] # 2 RotationDirection (0018,1150) IS [3000] # 4 ExposureTime (0018,1151) IS [30] # 2 XrayTubeCurrent (0018,5100) CS [HFS ] # 4 PatientPosition (0028,0030) DS [0.9765625\0.9765625 ] # 20 PixelSpacing DICOM

  6. Images dimension: Ammettendo che ogni voxel occupi 32 byte qual è lo spazio RAM necessario a simulare 40 cm di TAC di cui il seguente è parte dell’header DICOM di un’immagine? • circa 170 MByte • circa 2 Mbyte • circa 670 Mbyte

  7. Geant4-DICOM interface • Developed by L. Archambault, L. Beaulieu, V.-H. Tremblay (Univ. Laval and l'Hôtel-Dieu, Québec) • Donated to Geant4 for the common profit of the scientific community • under the condition that further improvements and developments are made publicly available to the community • Released with Geant4 5.2, June 2003 in an extended example • by S. Guatelli mainly • Deeply revised in by Pedro Arce in 2007 • Small improvements by S. Chauvie T. Aso & A.Kimura Ashikaga Institute of Technology Geant4 examples/extended/medical/DICOM

  8. Rows,columns(#): 512 512 PixelSpacing_X,Y(mm): 0.875 0.875 SliceTickness(mm): 5.0 SliceLocation(mm): 20.0 Header + DATA SETS From phantom to MC

  9. 3-D view …cont… #######################################        #     Density Range                   Materials              #---------------------------------------------------           #       g/cm3                            -                    #---------------------------------------------------           #  [ 0.100 , 0.351 ]                 Lungs (inhale)            #  [ 0.351 , 0.800 ]                 Lungs (exhale)            #  [ 0.919 , 0.979 ]                 Adipose                   #  ] 0.979 , 1.004 ]                 Breast                    #  ] 1.004 , 1.043 ]                 Phantom                   #  ] 1.043 , 1.109 ]                 Liver                     #  ] 1.109 , 1.113 ]                 Muscle                    #  ] 1.113 , 1.400 ]                 Trabecular Bone           #  [ 1.496 , 1.654 ]                 Dense Bone                ####################################### ICRU 46

  10. … and ends.

  11. The structure

  12. reverse engineering by S. Guatelli From DICOM image to Geant4 geometry • Reading image information • Transformation of pixel data into densities • Association of densities to a list of corresponding materials • Defining the voxels • Geant4 parameterised volumes • parameterisation function: material

  13. Start reading DICOM files

  14. Tranlsate TAGS with DICT

  15. Read the header and create the tag

  16. Implicit Endian Explicit VR, special cases

  17. Implicit Endian Explicit VR, other cases

  18. Implicit Endian Implicit VR

  19. Create .g4dcm

  20. Data.dat

  21. CT2Density.dat

  22. Write density Splitting materials in density intervals: In the class DicomDetectorConstruction, it is defined a density interval G4double densityDiff = 0.1;

  23. Navigation…. • : • The 1D optimisation . It will be very slow because each time a track exits a voxel it has to loop to all other voxels to know which one it may enter • The 3D optimisation with G4SmartVoxel: a 3D grid is built, so that the location of voxels is fast, but it requires a lot of memory • Using G4NestedParameterisation. The search is done hierarchically in X, Y and Z. It is fast and does not require big memory • Using G4PhantomParameterisation/G4RegularNavigation: an special algorithm to navigate in regular voxelised geometries (see GEANT4 doc). This is the fastest way without any extra memory requirement (and it is the default in this example). It includes an option (default) to skip frontiers between voxels when they have the same material. When using this option at each step the energy is all deposited in the last voxel; for properly distribution of the dose (=energy/volume) the G4PSDoseDeposit_RegNav scorer can be used

  24. MC Dose calculation in Radiotherapy How accurate is the dose calculation ? Description of patients Energy deposition Physics Geometry Validation studies DICOM

  25. Grazie per l’attenzione!

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