Fedorov A, Vangel MG, Tempany CM, Fennessy FM. Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Investigative Radiology; 2017;52(9):538–546 http://dx.doi.org/10.1097/RLI.0000000000000382.
<Patient>/<Study>/<Series>/orig-img-dicom/
. Since one required input of the converter are all dicom files which represent the original image on which the segmentation was created. Organizing the data as described above will allow us to just provide the correct series directory instead of listing all files of that series.<Patient>/<Study>/<Series>/segmentations/
. Into this folder we will also put the meta-information JSON file required to convert the segmentations.dcmqi
SEG converter is always http://qiicr.org/dcmqi/#/seg.BodyPartExamined
should be PROSTATE
(all caps is important! ... we should add explanation to this ...)SegmentDescription
can be populated with an abbreviated name reflecting the structure being segmented (note: this attribute can be at most 64 characters long!)SegmentAlgorithmName
not applicable, since segmentation was done manuallySegmentAlgorithmType
to MANUAL
, since that is how segmentations were created@[email protected]
and @[email protected]
. While all other properties in the JSON file are valid for all segmentation files, these two properties will differ for different segmentation files:<SeriesNumber of the image series>+1000
.<Patient>/<Study>/<Series>/segmentations/
folder.<Patient>/<Study>/<Series>/segmentations/
folder. Then run the converter like this:<out-name>.SEG.dcm
into the segmentations folder. The SEG object will contain all four segmentations.--inputImageList
has to exactly match the order of the segmentAttributes
list in the meta.json. If the order of files in --inputImageList
is different or contains less or more files, we need to adjust the meta.json accordingly.dcmqi
tool tid1500writer
. This tool expects as input the following items:SeriesNumber
is not formalized by DICOM, it is usually expected by the users that it should be unique. We can follow the following formula (or similar) to assign series number: <SeriesNumber of the image series being segmented>+2000
.imageLibrary
should contain the list of all DICOM instances from the source image series being segmented. A component of the output SR document will include certain attributes of these instances, and will reference them by SOPInstanceUID
.timePoint
, which should have values of 1 for baseline, and 2 for the followup.Measurements
. Each of the items (measurement groups) in this list will contain a list of attributes that apply to all individual measurements within the group, and a list of individual measurements.TrackingIdentifier
is a human-readable description of the measurements group. We can use the pattern <structure name> measurements
, i.e., Whole gland measurements
etc.ReferencedSegment
: The SegmentNumber for the corresponding segment in the DICOM segmentation object.sourceSeriesInstanceUID
: The SeriesInstanceUID of the actual image from which the segmentation was created.segmentationSOPInstanceUID
: The SOPInstanceUID of the segmentation object.Finding
and FindingSite
-- are code tuples that allows us to encode what was the region over which measurement was done, and where it was located. These items are somewhat similar to what we had to specify for encoding segmentation.(CodeMeaning, CodingSchemeDesignator, CodeValue)
:("Entire Gland", "SRT", T-F6078)
("Prostate", "SRT", "T-9200B")
("Entire", "SRT", "R-404A4")
("Peripheral zone of the prostate", "SRT", "T-D05E4")
("Abnormal", "SRT", "R-42037")
("Peripheral zone of the prostate", "SRT", "T-D05E4")
("Normal", "SRT", "G-A460")
("Peripheral zone of the prostate", "SRT", "T-D05E4")
value
: the measurement valuequantity
, units
, and derivationModifier
: coded tuples describing the quantity. In our case, measurements are either volume of the segmented regions, or the mean value of the Apparent Diffusion Coefficient (ADC).derivationModifier
):<out-name>.SR.dcm
which contains the structured report with all measurements referencing the original images and the segmentations from which the measurements originated.