Literature DB >> 32732276

Artificial Intelligence in Neuroradiology: Current Status and Future Directions.

Y W Lui1, P D Chang2, G Zaharchuk3, D P Barboriak4, A E Flanders5, M Wintermark3, C P Hess6, C G Filippi7.   

Abstract

Fueled by new techniques, computational tools, and broader availability of imaging data, artificial intelligence has the potential to transform the practice of neuroradiology. The recent exponential increase in publications related to artificial intelligence and the central focus on artificial intelligence at recent professional and scientific radiology meetings underscores the importance. There is growing momentum behind leveraging artificial intelligence techniques to improve workflow and diagnosis and treatment and to enhance the value of quantitative imaging techniques. This article explores the reasons why neuroradiologists should care about the investments in new artificial intelligence applications, highlights current activities and the roles neuroradiologists are playing, and renders a few predictions regarding the near future of artificial intelligence in neuroradiology.
© 2020 by American Journal of Neuroradiology.

Mesh:

Year:  2020        PMID: 32732276      PMCID: PMC7658873          DOI: 10.3174/ajnr.A6681

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  62 in total

1.  Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

Authors:  James H Thrall; Xiang Li; Quanzheng Li; Cinthia Cruz; Synho Do; Keith Dreyer; James Brink
Journal:  J Am Coll Radiol       Date:  2018-02-04       Impact factor: 5.532

2.  Deep Learning-Based Detection of Intracranial Aneurysms in 3D TOF-MRA.

Authors:  T Sichtermann; A Faron; R Sijben; N Teichert; J Freiherr; M Wiesmann
Journal:  AJNR Am J Neuroradiol       Date:  2018-12-20       Impact factor: 3.825

3.  Applications of a deep learning method for anti-aliasing and super-resolution in MRI.

Authors:  Can Zhao; Muhan Shao; Aaron Carass; Hao Li; Blake E Dewey; Lotta M Ellingsen; Jonghye Woo; Michael A Guttman; Ari M Blitz; Maureen Stone; Peter A Calabresi; Henry Halperin; Jerry L Prince
Journal:  Magn Reson Imaging       Date:  2019-06-24       Impact factor: 2.546

4.  Treating health disparities with artificial intelligence.

Authors:  Irene Y Chen; Shalmali Joshi; Marzyeh Ghassemi
Journal:  Nat Med       Date:  2020-01       Impact factor: 53.440

5.  Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review.

Authors:  Nick M Murray; Mathias Unberath; Gregory D Hager; Ferdinand K Hui
Journal:  J Neurointerv Surg       Date:  2019-10-08       Impact factor: 5.836

6.  Automatic Quantification of Computed Tomography Features in Acute Traumatic Brain Injury.

Authors:  Saurabh Jain; Thijs Vande Vyvere; Vasilis Terzopoulos; Diana Maria Sima; Eloy Roura; Andrew Maas; Guido Wilms; Jan Verheyden
Journal:  J Neurotrauma       Date:  2019-02-01       Impact factor: 5.269

7.  Machine Learning for Predicting Patient Wait Times and Appointment Delays.

Authors:  Catherine Curtis; Chang Liu; Thomas J Bollerman; Oleg S Pianykh
Journal:  J Am Coll Radiol       Date:  2017-10-24       Impact factor: 5.532

8.  Deep learning-based detection and segmentation-assisted management of brain metastases.

Authors:  Jie Xue; Bao Wang; Yang Ming; Xuejun Liu; Zekun Jiang; Chengwei Wang; Xiyu Liu; Ligang Chen; Jianhua Qu; Shangchen Xu; Xuqun Tang; Ying Mao; Yingchao Liu; Dengwang Li
Journal:  Neuro Oncol       Date:  2020-04-15       Impact factor: 12.300

9.  Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

Authors:  Silvia Basaia; Federica Agosta; Luca Wagner; Elisa Canu; Giuseppe Magnani; Roberto Santangelo; Massimo Filippi
Journal:  Neuroimage Clin       Date:  2018-12-18       Impact factor: 4.881

10.  Precise diagnosis of intracranial hemorrhage and subtypes using a three-dimensional joint convolutional and recurrent neural network.

Authors:  Hai Ye; Feng Gao; Youbing Yin; Danfeng Guo; Pengfei Zhao; Yi Lu; Xin Wang; Junjie Bai; Kunlin Cao; Qi Song; Heye Zhang; Wei Chen; Xuejun Guo; Jun Xia
Journal:  Eur Radiol       Date:  2019-04-30       Impact factor: 5.315

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  7 in total

1.  BPNSTs: In the eye of the beholder.

Authors:  Timothy J Kaufmann; Bradley J Erickson
Journal:  Neuro Oncol       Date:  2022-04-01       Impact factor: 12.300

Review 2.  The R-AI-DIOLOGY checklist: a practical checklist for evaluation of artificial intelligence tools in clinical neuroradiology.

Authors:  Sven Haller; Sofie Van Cauter; Christian Federau; Dennis M Hedderich; Myriam Edjlali
Journal:  Neuroradiology       Date:  2022-01-31       Impact factor: 2.804

3.  Foundations of Lesion Detection Using Machine Learning in Clinical Neuroimaging.

Authors:  Manoj Mannil; Nicolin Hainc; Risto Grkovski; Sebastian Winklhofer
Journal:  Acta Neurochir Suppl       Date:  2022

4.  Prediction of shunt failure facilitated by rapid and accurate volumetric analysis: a single institution's preliminary experience.

Authors:  Tushar R Jha; Mark F Quigley; Khashayar Mozaffari; Orgest Lathia; Katherine Hofmann; John S Myseros; Chima Oluigbo; Robert F Keating
Journal:  Childs Nerv Syst       Date:  2022-05-20       Impact factor: 1.532

5.  Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies.

Authors:  Thomas C Booth; Mariusz Grzeda; Alysha Chelliah; Andrei Roman; Ayisha Al Busaidi; Carmen Dragos; Haris Shuaib; Aysha Luis; Ayesha Mirchandani; Burcu Alparslan; Nina Mansoor; Jose Lavrador; Francesco Vergani; Keyoumars Ashkan; Marc Modat; Sebastien Ourselin
Journal:  Front Oncol       Date:  2022-01-31       Impact factor: 6.244

6.  Integrating Nanotechnology in Neurosurgery, Neuroradiology, and Neuro-Oncology Practice-The Clinicians' Perspective.

Authors:  Fred C Lam; Fateme Salehi; Ekkehard M Kasper
Journal:  Front Bioeng Biotechnol       Date:  2022-02-09

Review 7.  How to Improve the Management of Acute Ischemic Stroke by Modern Technologies, Artificial Intelligence, and New Treatment Methods.

Authors:  Kamil Zeleňák; Antonín Krajina; Lukas Meyer; Jens Fiehler; Daniel Behme; Deniz Bulja; Jildaz Caroff; Amar Ajay Chotai; Valerio Da Ros; Jean-Christophe Gentric; Jeremy Hofmeister; Omar Kass-Hout; Özcan Kocatürk; Jeremy Lynch; Ernesto Pearson; Ivan Vukasinovic
Journal:  Life (Basel)       Date:  2021-05-27
  7 in total

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