ArticleScientific data2018
An annotated test-retest collection of prostate multiparametric MRI.
Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed.
- "Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence.Proceedings of machine learning research · 2025Article
- AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons.Scientific data · 2024Article
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- Open access EEG dataset of repeated measurements from a single subject for microstate analysis.Scientific data · 2024Article
- Addressing challenges in radiomics research: systematic review and repository of open-access cancer imaging datasets.Insights into imaging · 2023Article
- National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence.Radiographics : a review publication of the Radiological Society of North America, Inc · 2023Article
- Stability of Multi-Parametric Prostate MRI Radiomic Features to Variations in Segmentation.Journal of personalized medicine · 2023Article
- Dataset of prostate MRI annotated for anatomical zones and cancer.Data in brief · 2022Article
- Assessing radiomics feature stability with simulated CT acquisitions.Scientific reports · 2022Article
- Domain Adaptation for Medical Image Analysis: A Survey.IEEE transactions on bio-medical engineering · 2022Review
- Artificial intelligence and machine learning in cancer imaging.Communications medicine · 2022Review
- How does DICOM support big data management? Investigating its use in medical imaging community.Insights into imaging · 2021Article
- An integrated nomogram combining deep learning, Prostate Imaging-Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study.The Lancet. Digital health · 2021Article
- Radiomics for Identification and Prediction in Metastatic Prostate Cancer: A Review of Studies.Frontiers in oncology · 2021Review
- DICOM re-encoding of volumetrically annotated Lung Imaging Database Consortium (LIDC) nodules.Medical physics · 2020Article
- Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer.Magnetic resonance in medicine · 2020Article
- Quantitative Imaging Informatics for Cancer Research.JCO clinical cancer informatics · 2020Article
- Boundary-Weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation.IEEE transactions on medical imaging · 2020Article
- Open Source Platform for Transperineal In-Bore MRI-Guided Targeted Prostate Biopsy.IEEE transactions on bio-medical engineering · 2020Article
- Repeatability of Quantitative Imaging Features in Prostate Magnetic Resonance Imaging.Frontiers in oncology · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Multiparametric Magnetic Resonance Imaging (mpMRI) is widely used for characterizing prostate cancer. Standard of care use of mpMRI in clinic relies on visual interpretation of the images by an expert. mpMRI is also increasingly used as a quantitative imaging biomarker of the disease. Little is known about repeatability of such quantitative measurements, and no test-retest datasets have been available publicly to support investigation of the technical characteristics of the MRI-based quantification in the prostate. Here we present an mpMRI dataset consisting of baseline and repeat prostate MRI exams for 15 subjects, manually annotated to define regions corresponding to lesions and anatomical structures, and accompanied by region-based measurements. This dataset aims to support further investigation of the repeatability of mpMRI-derived quantitative prostate measurements, study of the robustness and reliability of the automated analysis approaches, and to support development and validation of new image analysis techniques. The manuscript can also serve as an example of the use of DICOM for standardized encoding of the image annotation and quantification results.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.