Literature DB >> 29161580

Artificial intelligence and deep learning - Radiology's next frontier?

Ray Cody Mayo1, Jessica Leung2.   

Abstract

Tracing the use of computers in the radiology department from administrative functions through image acquisition, storage, and reporting, to early attempts at improved diagnosis, we begin to imagine possible new frontiers for their use in exam interpretation. Given their initially slow but ultimately substantial progress in the noninterpretive areas, we are left desiring and even expecting more in the interpretation realm. New technological advances may provide the next wave of progress and radiologists should be early adopters. Several potential applications are discussed and hopefully will serve to inspire future progress. Published by Elsevier Inc.

Keywords:  Artificial intelligence; Big data; Computer aided detection; Deep learning; Neural networks

Mesh:

Year:  2017        PMID: 29161580     DOI: 10.1016/j.clinimag.2017.11.007

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  18 in total

Review 1.  The Continuing Evolution of Molecular Functional Imaging in Clinical Oncology: The Road to Precision Medicine and Radiogenomics (Part I).

Authors:  Tanvi Vaidya; Archi Agrawal; Shivani Mahajan; Meenakshi H Thakur; Abhishek Mahajan
Journal:  Mol Diagn Ther       Date:  2019-02       Impact factor: 4.074

Review 2.  Artificial Intelligence: A Primer for Breast Imaging Radiologists.

Authors:  Manisha Bahl
Journal:  J Breast Imaging       Date:  2020-06-19

3.  Simulation and Synthesis in Medical Imaging.

Authors:  Alejandro F Frangi; Sotirios A Tsaftaris; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2018-03       Impact factor: 10.048

4.  Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings.

Authors:  Máté E Maros; Chang Gyu Cho; Andreas G Junge; Benedikt Kämpgen; Victor Saase; Fabian Siegel; Frederik Trinkmann; Thomas Ganslandt; Christoph Groden; Holger Wenz
Journal:  Sci Rep       Date:  2021-03-09       Impact factor: 4.379

5.  Positive predictive value and stroke workflow outcomes using automated vessel density (RAPID-CTA) in stroke patients: One year experience.

Authors:  Julie Adhya; Charles Li; Laura Eisenmenger; Russell Cerejo; Ashis Tayal; Michael Goldberg; Warren Chang
Journal:  Neuroradiol J       Date:  2021-04-28

Review 6.  Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States.

Authors:  Filippo Pesapane; Caterina Volonté; Marina Codari; Francesco Sardanelli
Journal:  Insights Imaging       Date:  2018-08-15

7.  Overview of artificial intelligence in medicine.

Authors:  Paras Malik; Monika Pathania; Vyas Kumar Rathaur
Journal:  J Family Med Prim Care       Date:  2019-07

8.  Reduction of False-Positive Markings on Mammograms: a Retrospective Comparison Study Using an Artificial Intelligence-Based CAD.

Authors:  Ray Cody Mayo; Daniel Kent; Lauren Chang Sen; Megha Kapoor; Jessica W T Leung; Alyssa T Watanabe
Journal:  J Digit Imaging       Date:  2019-08       Impact factor: 4.056

Review 9.  Applications of Deep Learning to Neuro-Imaging Techniques.

Authors:  Guangming Zhu; Bin Jiang; Liz Tong; Yuan Xie; Greg Zaharchuk; Max Wintermark
Journal:  Front Neurol       Date:  2019-08-14       Impact factor: 4.003

10.  Editorial: Artificial Intelligence (AI) in Clinical Medicine and the 2020 CONSORT-AI Study Guidelines.

Authors:  Dinah V Parums
Journal:  Med Sci Monit       Date:  2021-06-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.