Literature DB >> 34046708

The current and future roles of artificial intelligence in pediatric radiology.

Jeffrey P Otjen1, Michael M Moore2, Erin K Romberg1, Francisco A Perez1, Ramesh S Iyer3.   

Abstract

Artificial intelligence (AI) is a broad and complicated concept that has begun to affect many areas of medicine, perhaps none so much as radiology. While pediatric radiology has been less affected than other radiology subspecialties, there are some well-developed and some nascent applications within the field. This review focuses on the use of AI within pediatric radiology for image interpretation, with descriptive summaries of the literature to date. We highlight common features that enable successful application of the technology, along with some of the limitations that can inhibit the development of this field. We present some ideas for further research in this area and challenges that must be overcome, with an understanding that technology often advances in unpredictable ways.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Applications; Artificial intelligence; Children; Convolutional neural network; Pediatric radiology; Research; Technology

Mesh:

Year:  2021        PMID: 34046708     DOI: 10.1007/s00247-021-05086-9

Source DB:  PubMed          Journal:  Pediatr Radiol        ISSN: 0301-0449


  39 in total

1.  Global Trend in Artificial Intelligence-Based Publications in Radiology From 2000 to 2018.

Authors:  Elizabeth West; Simukayi Mutasa; Zelos Zhu; Richard Ha
Journal:  AJR Am J Roentgenol       Date:  2019-08-15       Impact factor: 3.959

2.  Conditional generative adversarial network for 3D rigid-body motion correction in MRI.

Authors:  Patricia M Johnson; Maria Drangova
Journal:  Magn Reson Med       Date:  2019-04-22       Impact factor: 4.668

Review 3.  Machine learning concepts, concerns and opportunities for a pediatric radiologist.

Authors:  Michael M Moore; Einat Slonimsky; Aaron D Long; Raymond W Sze; Ramesh S Iyer
Journal:  Pediatr Radiol       Date:  2019-03-29

4.  Computer-aided diagnosis for World Health Organization-defined chest radiograph primary-endpoint pneumonia in children.

Authors:  Nasreen Mahomed; Bram van Ginneken; Rick H H M Philipsen; Jaime Melendez; David P Moore; Halvani Moodley; Tanusha Sewchuran; Denny Mathew; Shabir A Madhi
Journal:  Pediatr Radiol       Date:  2020-01-13

5.  Learning Based Segmentation of CT Brain Images: Application to Postoperative Hydrocephalic Scans.

Authors:  Venkateswararao Cherukuri; Peter Ssenyonga; Benjamin C Warf; Abhaya V Kulkarni; Vishal Monga; Steven J Schiff
Journal:  IEEE Trans Biomed Eng       Date:  2017-12-13       Impact factor: 4.538

6.  The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database.

Authors:  Stan Benjamens; Pranavsingh Dhunnoo; Bertalan Meskó
Journal:  NPJ Digit Med       Date:  2020-09-11

Review 7.  Artificial intelligence applications for pediatric oncology imaging.

Authors:  Heike Daldrup-Link
Journal:  Pediatr Radiol       Date:  2019-10-16

Review 8.  Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians.

Authors:  Dana J Lin; Patricia M Johnson; Florian Knoll; Yvonne W Lui
Journal:  J Magn Reson Imaging       Date:  2020-02-12       Impact factor: 4.813

Review 9.  Artificial intelligence in paediatric radiology: Future opportunities.

Authors:  Natasha Davendralingam; Neil J Sebire; Owen J Arthurs; Susan C Shelmerdine
Journal:  Br J Radiol       Date:  2020-09-17       Impact factor: 3.039

10.  Are semi-automated software program designed for adults accurate for the identification of vertebral fractures in children?

Authors:  Fawaz F Alqahtani; Fabrizio Messina; Amaka C Offiah
Journal:  Eur Radiol       Date:  2019-05-22       Impact factor: 5.315

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  2 in total

1.  European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.

Authors:  Lene Bjerke Laborie; Jaishree Naidoo; Erika Pace; Pierluigi Ciet; Christine Eade; Matthias W Wagner; Thierry A G M Huisman; Susan C Shelmerdine
Journal:  Pediatr Radiol       Date:  2022-06-22

2.  Diagnostic performance of artificial intelligence approved for adults for the interpretation of pediatric chest radiographs.

Authors:  Hyun Joo Shin; Nak-Hoon Son; Min Jung Kim; Eun-Kyung Kim
Journal:  Sci Rep       Date:  2022-06-17       Impact factor: 4.996

  2 in total

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