On the public citation graph

Radiology and Enterprise Medical Imaging Extensions (REMIX)

https://doi.org/10.1007/s10278-017-0010-6

0 signed · 50 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10278-013-9622-7openalex-snapshot

The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository

inferredcites →https://doi.org/10.1007/s10278-018-0082-yopenalex-snapshot

The Orthanc Ecosystem for Medical Imaging

inferredcites →https://doi.org/10.1016/1350-4533(94)90015-9openalex-snapshot

Digital image processing: W.K. Pratt John Wiley, Chichester; 1991, 686pp. UK£55.15, ISBN 0-471-85766-1

inferredcites →https://doi.org/10.1016/j.ejrad.2013.06.024openalex-snapshot

Texture-based classification of different gastric tumors at contrast-enhanced CT

inferredcites →https://doi.org/10.1016/j.media.2012.02.005openalex-snapshot

Machine learning and radiology

inferredcites →https://doi.org/10.1016/j.mri.2012.06.009openalex-snapshot

Promise and pitfalls of quantitative imaging in oncology clinical trials

inferredcites →https://doi.org/10.1016/j.mri.2012.06.010openalex-snapshot

Radiomics: the process and the challenges

inferredcites →https://doi.org/10.1016/j.neunet.2014.09.003openalex-snapshot

Deep learning in neural networks: An overview

inferredcites →https://doi.org/10.1016/s0168-8278(01)00130-1openalex-snapshot

Clinical Management of Hepatocellular Carcinoma. Conclusions of the Barcelona-2000 EASL Conference

inferredcites →https://doi.org/10.1038/nature11971openalex-snapshot

Magnetic resonance fingerprinting

inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot

Deep learning

inferredcites →https://doi.org/10.1038/ncomms5006openalex-snapshot

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

inferredcites →https://doi.org/10.1055/s-0030-1247132openalex-snapshot

Modified RECIST (mRECIST) Assessment for Hepatocellular Carcinoma

inferredcites →https://doi.org/10.1093/cesifo/ift014openalex-snapshot

Has Medical Innovation Reduced Cancer Mortality?

inferredcites →https://doi.org/10.1093/jnci/92.3.205openalex-snapshot

New Guidelines to Evaluate the Response to Treatment in Solid Tumors

inferredcites →https://doi.org/10.1097/rli.ob013e3181dzfeecopenalex-snapshot

Reducing Abdominal CT Radiation Dose With Adaptive Statistical Iterative Reconstruction Technique

inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot

Going deeper with convolutions

inferredcites →https://doi.org/10.1109/mcse.2011.37openalex-snapshot

The NumPy Array: A Structure for Efficient Numerical Computation

inferredcites →https://doi.org/10.1109/tsmc.1973.4309314openalex-snapshot

Textural Features for Image Classification

inferredcites →https://doi.org/10.1117/3.2197756openalex-snapshot

Computed Tomography: Principles, Design, Artifacts, and Recent Advances

inferredcites →https://doi.org/10.1118/1.2409481openalex-snapshot

Noise and resolution in images reconstructed with FBP and OSC algorithms for CT

inferredcites →https://doi.org/10.1118/1.3180955openalex-snapshot

A hierarchical spectral clustering and nonlinear dimensionality reduction scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS)

inferredcites →https://doi.org/10.1118/1.3611983openalex-snapshot

SU‐E‐T‐33: Pydicom: An Open Source DICOM Library

inferredcites →https://doi.org/10.1118/1.3676687openalex-snapshot

Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models

inferredcites →https://doi.org/10.1145/2647868.2654889openalex-snapshot

Caffe

inferredcites →https://doi.org/10.1148/radiol.2015151169openalex-snapshot

Radiomics: Images Are More than Pictures, They Are Data

inferredcites →https://doi.org/10.1148/radiol.2017162664openalex-snapshot

Automated Critical Test Findings Identification and Online Notification System Using Artificial Intelligence in Imaging

inferredcites →https://doi.org/10.1148/rg.262055138openalex-snapshot

CT Dose Reduction and Dose Management Tools: Overview of Available Options

inferredcites →https://doi.org/10.1186/s40169-016-0091-8openalex-snapshot

Cancer Moonshot 2020: a new march of clinical and translational medicine

inferredcites →https://doi.org/10.1200/jco.2006.07.3049openalex-snapshot

Correlation of Computed Tomography and Positron Emission Tomography in Patients With Metastatic Gastrointestinal Stromal Tumor Treated at a Single Institution With Imatinib Mesylate: Proposal of New Computed Tomography Response Criteria

inferredcites →https://doi.org/10.1378/chest.11-2027openalex-snapshot

Quantitative Computerized Two-Point Correlation Analysis of Lung CT Scans Correlates With Pulmonary Function in Pulmonary Sarcoidosis

inferredcites →https://doi.org/10.1593/tlo.13832openalex-snapshot

The Quantitative Imaging Network: NCI's Historical Perspective and Planned Goals

inferredcites →https://doi.org/10.1593/tlo.13862openalex-snapshot

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

inferredcites →https://doi.org/10.2214/ajr.06.0601openalex-snapshot

Predicting Response of Colorectal Hepatic Metastasis: Value of Pretreatment Apparent Diffusion Coefficients

inferredcites →https://doi.org/10.2214/ajr.06.1524openalex-snapshot

Impact of Operator-Selected Image Noise Index and Reconstruction Slice Thickness on Patient Radiation Dose in 64-MDCT

inferredcites →https://doi.org/10.2214/ajr.09.2397openalex-snapshot

Iterative Reconstruction Technique for Reducing Body Radiation Dose at CT: Feasibility Study

inferredcites →https://doi.org/10.2214/ajr.14.14147openalex-snapshot

CT Gray-Level Texture Analysis as a Quantitative Imaging Biomarker of Epidermal Growth Factor Receptor Mutation Status in Adenocarcinoma of the Lung

inferredcites →https://doi.org/10.2967/jnumed.108.057307openalex-snapshot

From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3530598openalex-extracted

Barriers to Artificial Intelligence Adoption in Healthcare Management: A Systematic Review

inferred← citeshttps://doi.org/10.1007/978-3-319-94878-2_19openalex-snapshot

The Role of an Artificial Intelligence Ecosystem in Radiology

inferred← citeshttps://doi.org/10.1007/s11547-021-01351-xopenalex-snapshot

Interventional Radiology ex-machina: impact of Artificial Intelligence on practice

inferred← citeshttps://doi.org/10.1007/s12032-020-01368-8openalex-snapshot

Myths and facts about artificial intelligence: why machine- and deep-learning will not replace interventional radiologists

inferred← citeshttps://doi.org/10.1016/j.acra.2019.07.031openalex-snapshot

Artificial Intelligence in Radiology: Summary of the AUR Academic Radiology and Industry Leaders Roundtable

inferred← citeshttps://doi.org/10.1016/j.compmedimag.2020.101721openalex-snapshot

Automated coronary artery atherosclerosis detection and weakly supervised localization on coronary CT angiography with a deep 3-dimensional convolutional neural network

inferred← citeshttps://doi.org/10.1016/j.jacr.2019.06.002openalex-snapshot

Quality and Data Science

inferred← citeshttps://doi.org/10.1145/3239438.3239449openalex-snapshot

Development of a Flexible Imaging Data Integration Tool for Multicenter Clinical Trials

inferred← citeshttps://doi.org/10.17140/roj-3-119openalex-snapshot

Enterprise Imaging: The Next Frontier in Healthcare Technology–A Liturature Review

inferred← citeshttps://doi.org/10.3390/s24092705openalex-snapshot

Temporal Relationship-Aware Treadmill Exercise Test Analysis Network for Coronary Artery Disease Diagnosis

inferred← citeshttps://doi.org/10.48550/arxiv.2303.10473openalex-snapshot

Report of the Medical Image De-Identification (MIDI) Task Group -- Best Practices and Recommendations

inferred← citeshttps://doi.org/10.7759/cureus.37022openalex-snapshot

Optimizing Primary Healthcare in Hong Kong: Strategies for the Successful Integration of Radiology Services

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.