3
我是新來處理DICOM圖像從他們的本土廠商的軟件了。我正在嘗試將一組重建的橫軸切片中的PET圖像分成MatLab。我的目標是做一些簡單的分割，並最終確定段中的最大和最小像素值。不過，我在將存儲的值轉換爲在本機系統上看到的值時遇到了問題。打開正電子發射斷層掃描（PET）在DICOM MATLAB的圖像和正確地解釋像素值？
的圖像被加載到MATLAB作爲INT16類。無論我從系列中加載哪個片，最大像素值始終爲32767。通過查看其本地系統上的圖像，我知道每個切片中的最大像素值是不同的。
我已經檢查重新調整值和重新調整截距值和重新調整的關係似乎是線性的。我應該做另一個更正嗎？我假設所有其他修正（例如衰減，分散和隨機）都是在重建過程中進行的。我發佈了下面標題中檢索到的DICOM信息（不要擔心，圖像是幻影，因此沒有患者識別數據）。
問候，
羅斯
Filename: [1x76 char]
FileModDate: '26-Jul-2013 10:50:42'
FileSize: 38356
Format: 'DICOM'
FormatVersion: 3
Width: 128
Height: 128
BitDepth: 16
ColorType: 'grayscale'
FileMetaInformationGroupLength: 182
FileMetaInformationVersion: [2x1 uint8]
MediaStorageSOPClassUID: '1.2.840.10008.5.1.4.1.1.128'
MediaStorageSOPInstanceUID: [1x49 char]
TransferSyntaxUID: '1.2.840.10008.1.2.1'
ImplementationClassUID: '1.2.840.113619.6.55'
SourceApplicationEntityTitle: 'dst01'
IdentifyingGroupLength: 484
SpecificCharacterSet: 'ISO_IR 100'
ImageType: 'ORIGINAL\PRIMARY'
InstanceCreationDate: '20130522'
InstanceCreationTime: '171655'
InstanceCreatorUID: '1.2.840.113619.1.131'
SOPClassUID: '1.2.840.10008.5.1.4.1.1.128'
SOPInstanceUID: [1x49 char]
StudyDate: '20130514'
SeriesDate: '20130514'
AcquisitionDate: '20130514'
ContentDate: '20130522'
StudyTime: '142911'
SeriesTime: '143208.00'
AcquisitionTime: '143208.00'
ContentTime: '171655'
AccessionNumber: ''
Modality: 'PT'
Manufacturer: 'GE MEDICAL SYSTEMS'
InstitutionName: 'NHS TRUST'
ReferringPhysicianName: [1x1 struct]
StationName: 'dst01'
StudyDescription: ''
SeriesDescription: 'WB_3D_VuePoint'
PhysicianReadingStudy: [1x1 struct]
OperatorName: [1x1 struct]
ManufacturerModelName: 'Discovery STE'
Private_0009_GroupLength: 2714
Private_0009_10xx_Creator: 'GEMS_PETD_01'
Private_0009_11xx_Creator: 'GEMS_GENIE_1'
Private_0009_1002: 'SOLID_TEST'
Private_0009_1005: '20130514143030.00'
Private_0009_1006: 0
Private_0009_100a: [1x45 char]
Private_0009_100d: '20130514143208.00'
Private_0009_100e: '20130514143055.00'
Private_0009_1013: [1x59 char]
Private_0009_1014: 'Sternal Notch'
Private_0009_1015: 'SN'
Private_0009_1016: 0
Private_0009_1017: 0
Private_0009_1018: 0
Private_0009_1019: 0
Private_0009_101a: 1
Private_0009_101b: 0
Private_0009_101c: 1
Private_0009_101d: 0
Private_0009_101e: 1
Private_0009_101f: 1
Private_0009_1020: 0
Private_0009_1021: 1
Private_0009_1022: 0
Private_0009_1023: 0
Private_0009_1024: 2
Private_0009_1025: 2
Private_0009_1026: 23
Private_0009_1027: 1
Private_0009_1028: 1
Private_0009_1029: 0
Private_0009_102a: 0
Private_0009_102b: 70
Private_0009_102c: 153
Private_0009_102d: 0
Private_0009_102e: 0
Private_0009_1034: 0
Private_0009_1035: 0
Private_0009_1036: 'FDG -- fluorodeoxyglucose'
Private_0009_1037: ''
Private_0009_1038: 0
Private_0009_1039: ''
Private_0009_103a: 0
Private_0009_103b: ''
Private_0009_103c: 0
Private_0009_103d: ''
Private_0009_103e: '18F'
Private_0009_103f: 6588
Private_0009_1040: 0.9700
Private_0009_104d: 0
Private_0009_104e: 23
Private_0009_104f: 23
Private_0009_1050: 7
Private_0009_1051: 7
Private_0009_1052: 32
Private_0009_1053: 800
Private_0009_1054: 650
Private_0009_1055: 425
Private_0009_1056: [1x49 char]
Private_0009_1057: [1x48 char]
Private_0009_1059: [1x49 char]
Private_0009_105a: 0
Private_0009_105c: [1x49 char]
Private_0009_105d: [1x45 char]
Private_0009_105e: [1x51 char]
Private_0009_105f: 'SOLID_TEST'
Private_0009_1062: [1x44 char]
Private_0009_1063: 0
Private_0009_1064: 0
Private_0009_1066: 119.5000
Private_0009_1067: -79.8540
Private_0009_1068: '20130514143123.00'
Private_0009_1069: 553
Private_0009_106a: -79.9000
Private_0009_106b: 0
Private_0009_106c: '20130514143208.00'
Private_0009_106d: 180
Private_0009_1070: 0
Private_0009_1071: 90674329
Private_0009_1072: 0
Private_0009_1073: 1
Private_0009_1074: 255
Private_0009_107c: 0
Private_0009_107d: 2
Private_0009_107e: 0
Private_0009_107f: 0
Private_0009_1080: 0
Private_0009_1081: 0
Private_0009_108b: 5
Private_0009_108c: 2
Private_0009_108d: 0.0960
Private_0009_108e: 0
Private_0009_108f: 0
Private_0009_1090: 0
Private_0009_1091: 0
Private_0009_1092: 0
Private_0009_1093: 0
Private_0009_1094: 0
Private_0009_1095: 0
Private_0009_1096: [1x49 char]
Private_0009_1097: [1x51 char]
Private_0009_1098: [1x49 char]
Private_0009_1099: ''
Private_0009_109a: 0
Private_0009_109b: 0
Private_0009_109c: ''
Private_0009_109d: 0
Private_0009_109e: 0
Private_0009_109f: 0
Private_0009_10a0: 0
Private_0009_10a1: 0
Private_0009_10a2: 0
Private_0009_10a3: 0
Private_0009_10a6: 26
Private_0009_10a7: 0
Private_0009_10ab: 0
Private_0009_10ac: 0
Private_0009_10ad: ''
Private_0009_10ae: ''
Private_0009_10b2: 2
Private_0009_10b3: 20
Private_0009_10b4: 70
Private_0009_10b5: 0
Private_0009_10b6: 0
Private_0009_10b7: 0
Private_0009_10b8: 0
Private_0009_10b9: 0
Private_0009_10ba: 1
Private_0009_10bb: 6
Private_0009_10bc: 0
Private_0009_10bd: 0
Private_0009_10be: 0
Private_0009_10bf: 0
Private_0009_10c0: 0
Private_0009_10c1: 0
Private_0009_10c2: 0
Private_0009_10c3: 0
Private_0009_10c4: 6
Private_0009_10c5: 0
Private_0009_10c6: 0
Private_0009_10c7: 0
Private_0009_10cb: 0.8601
Private_0009_10cc: 0.1256
Private_0009_10cd: 0.8240
Private_0009_10ce: -0.0254
Private_0009_10cf: 0.5000
Private_0009_10d0: -0.0483
Private_0009_10d5: 0
Private_0009_10d6: 70.5000
Private_0009_10d7: -79.9000
Private_0009_10d8: 1
Private_0009_10db: 3
Private_0009_10dc: 2
Private_0009_10df: 47
Private_0009_10e2: 10
Private_0009_10e4: '3D_AC'
Private_0009_10e5: 0
Private_0009_10e6: 0
Private_0009_10e7: 0
Private_0009_10e9: 0
Private_0009_10ea: 0
Private_0009_10eb: 0
Private_0009_10ec: 0
Private_0009_111e: [1x49 char]
Private_0009_1146: [1x49 char]
PatientGroupLength: 96
PatientName: [1x1 struct]
PatientID: 'SOLID_TEST'
PatientBirthDate: ''
PatientSex: ''
PatientAge: ''
PatientSize: 0
PatientWeight: 0
EthnicGroup: ''
AdditionalPatientHistory: ''
Private_0017_GroupLength: 46
Private_0017_10xx_Creator: 'GEMS_PETD_01'
Private_0017_1004: '20130207140047.00'
AcquisitionGroupLength: 230
SliceThickness: 3.2700
AcquisitionTerminationCondition: 'TIME'
AcquisitionStartCondition: 'MANU'
AcquisitionStartConditionData: 0
AcquisitionTerminationConditionData: 0
SoftwareVersion: '41.04'
ProtocolName: 'WB 3D'
TriggerTime: 0
FrameTime: 0
IntervalsAcquired: 0
IntervalsRejected: 0
ReconstructionDiameter: 700
GantryDetectorTilt: 0
FieldOfViewShape: 'CYLINDRICAL RING'
FieldOfViewDimensions: [2x1 double]
CollimatorType: 'NONE'
ActualFrameDuration: 180000
PatientPosition: 'HFS'
Private_0019_GroupLength: 42
Private_0019_10xx_Creator: 'GEMS_PETD_01'
Private_0019_1004: '20130207140602'
RelationshipGroupLength: 322
StudyInstanceUID: [1x51 char]
SeriesInstanceUID: [1x49 char]
StudyID: '6893'
SeriesNumber: 401
InstanceNumber: 22
ImagePositionPatient: [3x1 double]
ImageOrientationPatient: [6x1 double]
FrameOfReferenceUID: [1x59 char]
PositionReferenceIndicator: 'SN'
SliceLocation: 1.8500
ImagePresentationGroupLength: 218
SamplesPerPixel: 1
PhotometricInterpretation: 'MONOCHROME2'
Rows: 128
Columns: 128
PixelSpacing: [2x1 double]
CorrectedImage: [1x40 char]
BitsAllocated: 16
BitsStored: 16
HighBit: 15
PixelRepresentation: 1
SmallestImagePixelValue: 0
LargestImagePixelValue: 32767
RescaleIntercept: 0
RescaleSlope: 0.3555
LossyImageCompression: '00'
Unknown_0040_0000: 158
AcquisitionContextSequence: [1x1 struct]
NuclearAcquisitionGroupLength: 808
EnergyWindowRangeSequence: [1x1 struct]
RadiopharmaceuticalInformationSequence: [1x1 struct]
NumberOfSlices: 47
TypeOfDetectorMotion: 'NONE'
PatientOrientationCodeSequence: [1x1 struct]
PatientOrientationModifierCodeSequence: [1x1 struct]
PatientGantryRelationshipCodeSequence: [1x1 struct]
SeriesType: 'STATIC\IMAGE'
Units: 'BQML'
CountsSource: 'EMISSION'
RandomsCorrectionMethod: 'SING'
AttenuationCorrectionMethod: 'measured,, 0.096000 cm-1,'
DecayCorrection: 'START'
ReconstructionMethod: '3D IR'
DetectorLinesOfResponseUsed: '0'
ScatterCorrectionMethod: 'Model Based'
AxialMash: [2x1 double]
TransverseMash: 2
CoincidenceWindowWidth: 0
FrameReferenceTime: 0
PrimaryPromptsCountsAccumulated: 0
SecondaryCountsAccumulated: 0
SliceSensitivityFactor: 1
DecayFactor: 1.0095
DoseCalibrationFactor: 1139
ScatterFractionFactor: 0.3174
DeadTimeFactor: 1.1243
ImageIndex: 26
PixelDataGroupLength: 32780
感謝medPhys-PL，這正是問題。我曾假定每個切片/研究的重新定標值都是固定的，並且僅取決於我們將數據轉換爲半定量值的校準。我很高興這很容易......我花了很長時間看着它，我錯過了明顯的。 – PercyP