Detailed Description | |
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Modalities | MR | Number of Patients | 346 | Number of Studies | 349 | Number of Series | 18,321 | Number of Images | 309,251 | Images Size (GB) | 15.1 |
PROSTATEx-1 Challenge (November 21, 2016 to February 16, 2017)SPIE, along with the support of the American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI), conducted a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of clinically significant prostate lesions. As part of the 2017 SPIE Medical Imaging Symposium, the PROSTATEx Challenge provided a unique opportunity for participants to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets. For more details, go to http://www.spie.org/PROSTATEx/. - Release date of training set cases with truth: November 21, 2016
- Release date of test set cases without truth: December 12, 2016
- Submission date for participants’ test set classification output: January 16, 2017
- Challenge results released to participants: January 20, 2017
- SPIE Medical Imaging Symposium: February 13-16, 2017
The PROSTATEx Challenge Organizers have provided the following options for download. The significance of these subsets are explained on the the challenge web site: http://spiechallenges.cloudapp.net/competitions/6. Data Type | Training Cohort (204 subjects) | Test Cohort (140 subjects) |
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Download images (DICOM) |
| | Download Ktrans images (.mhd) | | | Download lesion information (.zip) | | | Download lesion reference thumbnails (.bmp) | | |
The images come in two encodings. The acquired MR is provided in DICOM encoding. Additionally Ktrans images are provided. They come in mhd format. Ktrans is a key pharmacokinetic parameter computed from the available Dynamic contrast enhanced T1-weighted series. Each patient has one study with several DICOM images and one Ktrans image. The Ktrans image is encoded in two files ProstateX-[ProxID]-Ktrans.[mhd/zraw], where ProxID is the ProstateX patient identifier. The DICOM images comprise several Series each comprising several Instances. The DICOM files are documented in the ProstateX-Images.csv file. The columns in that file encode the following: ProxID – ProstateX patient identifier. Name – Series Description Studydate – Study Date fid – Finding ID Pos – Scanner Coordinate position of the finding WorldMatrix – Matrix describing image orientation and scaling ijk – image col,row,slice coordinate of finding ImageUID – Image Identifier TopLevel 0 - Series forms one image 1 – A set of Series forms a 4D image (e.g. Dynamic MR) NA – Series form one image, but is part of a Level 1 4D image
SpacingBetweenSlices – Scalar Spacing between slices VoxelSpacing – Vector with x,y,z spacing scalars Dim – Vector with 4D dimensions of the image DCMSerDescr – The original DICOM Series Description DCMSerUID – The DICOM Series UID DCMSerNum – The DICOM Series Number InstanceUIDList – DICOM Instances that make up this series ImageUIDList – TopLevel-NA Images the make up this Toplevel 1 image
For example, to get the ADC image of Patient ProstateX-0123 do the following. After you imported the DICOM files into your environment, go to patient ProstateX-0123 and find the series with ADC in it. In this case it is ‘ep2d_diff_tra_DYNDIST_ADC’. It has SeriesNumber 8. The DICOM images in that series form the ADC image for this challenge. Image slice j at coordinate i,j contains a finding fid. See findings for more details. FindingsThe findings are documented in the ProstateX-Findings.csv table. Documentation for the columns in that table is as follows: pos - Scanner Coordinate position of the finding ClinSig – Identifier available in training set that identifies whether this is a clinically significant finding. Either the biopsy GleasonScore was 7 or higher. Findings with a PIRADS score 2 were not biopsied and are not considered clinically significant. In our center the occurrence of clinically significant cancer in PIRADS 2 lesions is less than 5%.
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