Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticlePediatrics

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study

J.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier and K.W. Yeom
American Journal of Neuroradiology September 2020, 41 (9) 1718-1725; DOI: https://doi.org/10.3174/ajnr.A6704
J.L. Quon
aFrom the Departments of Neurosurgery (J.L.Q., G.A.G., M.S.B.E.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for J.L. Quon
W. Bala
eDepartment of Radiology (W.B., J.S., M.P.L., K.W.Y.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for W. Bala
L.C. Chen
gDepartment of Urology (L.C.C.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for L.C. Chen
J. Wright
iDepartment of Radiology (J.W.), Seattle Children's Hospital, University of Washington School of Medicine, Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for J. Wright
L.H. Kim
hStanford University School of Medicine (L.H.K., M.H., K.S.), Stanford, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for L.H. Kim
M. Han
hStanford University School of Medicine (L.H.K., M.H., K.S.), Stanford, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M. Han
K. Shpanskaya
hStanford University School of Medicine (L.H.K., M.H., K.S.), Stanford, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for K. Shpanskaya
E.H. Lee
bElectrical Engineering (E.H.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for E.H. Lee
E. Tong
cRadiology (E.T., M.I.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for E. Tong
M. Iv
cRadiology (E.T., M.I.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M. Iv
J. Seekins
eDepartment of Radiology (W.B., J.S., M.P.L., K.W.Y.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for J. Seekins
M.P. Lungren
eDepartment of Radiology (W.B., J.S., M.P.L., K.W.Y.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M.P. Lungren
K.R.M. Braun
jDepartments of Clinical Radiology & Imaging Sciences (K.R.M.B., C.Y.H.), Riley Children's Hospital, Indiana University, Indianapolis, Indiana
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for K.R.M. Braun
T.Y. Poussaint
kDepartments of Radiology (T.Y.P.), Boston Children's Hospital, Boston, Massachusetts
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for T.Y. Poussaint
S. Laughlin
lDepartments of diagnostic Imaging (S.L.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for S. Laughlin
M.D. Taylor
mand Neurosurgery (M.D.T.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M.D. Taylor
R.M. Lober
oDepartment of Neurosurgery (R.M.L.), Dayton Children's Hospital, Wright State University Boonshoft School of Medicine, Dayton, Ohio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for R.M. Lober
H. Vogel
dand Pathology (H.V.), Stanford University, Stanford, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for H. Vogel
P.G. Fisher
fDivision of Child Neurology (P.G.F.), Lucile Packard Children's Hospital, Stanford University, Palo Alto, California
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for P.G. Fisher
G.A. Grant
aFrom the Departments of Neurosurgery (J.L.Q., G.A.G., M.S.B.E.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for G.A. Grant
V. Ramaswamy
n and Haematology/Oncology (V.R.), The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for V. Ramaswamy
N.A. Vitanza
pDivision of Pediatric Hematology/Oncology (N.A.V.), Department of Pediatrics, University of Washington, Seattle Children's Hospital, Seattle Washington
qFred Hutchinson Cancer Research Center (N.A.V.), Seattle, Washington
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for N.A. Vitanza
C.Y. Ho
jDepartments of Clinical Radiology & Imaging Sciences (K.R.M.B., C.Y.H.), Riley Children's Hospital, Indiana University, Indianapolis, Indiana
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for C.Y. Ho
M.S.B. Edwards
aFrom the Departments of Neurosurgery (J.L.Q., G.A.G., M.S.B.E.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for M.S.B. Edwards
S.H. Cheshier
rDepartments of Neurosurgery (S.H.C.), University of Utah School of Medicine, Salt Lake City, Utah.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for S.H. Cheshier
K.W. Yeom
eDepartment of Radiology (W.B., J.S., M.P.L., K.W.Y.)
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for K.W. Yeom
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

References

  1. 1.↵
    1. Pollack IF,
    2. Agnihotri S,
    3. Broniscer A
    . Childhood brain tumors: current management, biological insights, and future directions. J Neurosurg Pediatr 2019;23:261–73 doi:10.3171/2018.10.PEDS18377 pmid:30835699
    CrossRefPubMed
  2. 2.↵
    1. Segal D,
    2. Karajannis MA
    . Pediatric brain tumors: an update. Curr Probl Pediatr Adolesc Health Care 2016;46:242–50 doi:10.1016/j.cppeds.2016.04.004 pmid:27230809
    CrossRefPubMed
  3. 3.↵
    1. Medina LS,
    2. Kuntz KM,
    3. Pomeroy S
    . Children with headache suspected of having a brain tumor: a cost-effectiveness analysis of diagnostic strategies. Pediatrics 2001;108:255–63 doi:10.1542/peds.108.2.255 pmid:11483785
    Abstract/FREE Full Text
  4. 4.↵
    1. Zhou M,
    2. Scott J,
    3. Chaudhury B, et al
    . Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches. AJNR Am J Neuroradiol 2018;39:208–16 doi:10.3174/ajnr.A5391 pmid:28982791
    Abstract/FREE Full Text
  5. 5.↵
    1. Northcott PA,
    2. Korshunov A,
    3. Witt H, et al
    . Medulloblastoma comprises four distinct molecular variants. J Clin Oncol 2011;29:1408–14 doi:10.1200/JCO.2009.27.4324 pmid:20823417
    Abstract/FREE Full Text
  6. 6.↵
    1. Ramaswamy V,
    2. Remke M,
    3. Bouffet E, et al
    . Risk stratification of childhood medulloblastoma in the molecular era: the current consensus. Acta Neuropathol 2016;131:821–31 doi:10.1007/s00401-016-1569-6
    CrossRefPubMed
  7. 7.↵
    1. Nejat F,
    2. El Khashab M,
    3. Rutka JT
    . Initial management of childhood brain tumors: neurosurgical considerations. J Child Neurol 2008;23:1136–48 doi:10.1177/0883073808321768 pmid:18952580
    CrossRefPubMedWeb of Science
  8. 8.↵
    1. Capper D,
    2. Jones DTW,
    3. Sill M, et al
    . DNA methylation-based classification of central nervous system tumours. Nature 2018;555:469–74 doi:10.1038/nature26000 pmid:29539639
    CrossRefPubMed
  9. 9.↵
    1. Louis DN
    . WHO Classification of Tumours of the Central Nervous System. International Agency for Research on Cancer; 2016
  10. 10.↵
    1. Park A,
    2. Chute C,
    3. Rajpurkar P, et al
    . Deep learning-assisted diagnosis of cerebral aneurysms using the HeadXNet model. JAMA Netw Open 2019;2:e195600 doi:10.1001/jamanetworkopen.2019.5600 pmid:31173130
    CrossRefPubMed
  11. 11.↵
    1. El-Dahshan ES,
    2. Mohsen HM,
    3. Revett K, et al
    . Computer-aided diagnosis of human brain tumor through MRI: a survey and a new algorithm. Expert Systems with Applications 2014;41:5526–45 doi:10.1016/j.eswa.2014.01.021
    CrossRef
  12. 12.↵
    1. Deng J,
    2. Dong W,
    3. Socher R, et al
    . ImageNet: a large-scale hierarchical image database. In: Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, Florida. June 20–25, 2009:248–55
  13. 13.↵
    1. Krizhevsky A,
    2. Sutskever I,
    3. Hinton GE
    . Imagenet classification with deep convolutional neural networks. In: Proccedings of the Advances in Neural Information Processing Systems Conference, Lake Tahoe, California. December 3–8, 2012;1097–1105
  14. 14.↵
    1. Arrieta AB,
    2. Díaz-Rodríguez N,
    3. Del Ser J, et al
    . Explainable Artificial Intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion 2019;58:82–115 doi:10.1016/j.inffus.2019.12.012
    CrossRef
  15. 15.↵
    1. Simonyan K,
    2. Vedaldi A,
    3. Zisserman A
    . Deep inside convolutional networks: visualising image classification models and saliency maps. arXiv December 2013. https://arxiv.org/pdf/1312.6034.pdf. Accessed April 5, 2020
  16. 16.↵
    1. Zhou B,
    2. Khosla A,
    3. Lapedriza A, et al
    . Learning deep features for discriminative localization. In: Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, Nevada. June 27–30, 2016:2921–29
  17. 17.↵
    1. Dice LR
    . Measures of the amount of ecologic association between species. Ecology 1945;26:297–302 doi:10.2307/1932409
    CrossRefWeb of Science
  18. 18.↵
    1. van der Maaten L,
    2. Hinton G
    . Visualizing data using t-SNE. Journal of Machine Learning Research 2008;9:2579–2605
  19. 19.↵
    1. Hosny A,
    2. Parmar C,
    3. Quackenbush J, et al
    . Artificial intelligence in radiology. Nat Rev Cancer 2018;18:500–10 doi:10.1038/s41568-018-0016-5 pmid:29777175
    CrossRefPubMed
  20. 20.↵
    1. Savadjiev P,
    2. Chong J,
    3. Dohan A, et al
    . Demystification of AI-driven medical image interpretation: past, present and future. Eur Radiol 2019;29:1616–24 doi:10.1007/s00330-018-5674-x pmid:30105410
    CrossRefPubMed
  21. 21.↵
    1. Chang K,
    2. Balachandar N,
    3. Lam C, et al
    . Distributed deep learning networks among institutions for medical imaging. J Am Med Inform Assoc 2018;25:945–54 doi:10.1093/jamia/ocy017 pmid:29617797
    CrossRefPubMed
  22. 22.↵
    1. Rodriguez Gutierrez D,
    2. Awwad A,
    3. Meijer L, et al
    . Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors. AJNR Am J Neuroradiol 2014;35:1009–15 doi:10.3174/ajnr.A3784 pmid:24309122
    Abstract/FREE Full Text
  23. 23.↵
    1. Arle JE,
    2. Morriss C,
    3. Wang ZJ, et al
    . Prediction of posterior fossa tumor type in children by means of magnetic resonance image properties, spectroscopy, and neural networks. J Neurosurg 1997;86:755–61 doi:10.3171/jns.1997.86.5.0755 pmid:9126888
    CrossRefPubMed
  24. 24.↵
    1. Bidiwala S,
    2. Pittman T
    . Neural network classification of pediatric posterior fossa tumors using clinical and imaging data. Pediatr Neurosurg 2004;40:8–15 doi:10.1159/000076571 pmid:15007223
    CrossRefPubMed
  25. 25.↵
    1. Abujudeh HH,
    2. Boland GW,
    3. Kaewlai R, et al
    . Abdominal and pelvic computed tomography (CT) interpretation: discrepancy rates among experienced radiologists. Eur Radiol 2010;20:1952–57 doi:10.1007/s00330-010-1763-1 pmid:20336300
    CrossRefPubMed
  26. 26.↵
    1. Allen B, Jr..,
    2. Seltzer SE,
    3. Langlotz CP, et al
    . A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop. J Am Coll Radiology 2019;16:1179–89 doi:10.1016/j.jacr.2019.04.014 pmid:31151893
    CrossRefPubMed
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 41 (9)
American Journal of Neuroradiology
Vol. 41, Issue 9
1 Sep 2020
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
J.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier, K.W. Yeom
Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study
American Journal of Neuroradiology Sep 2020, 41 (9) 1718-1725; DOI: 10.3174/ajnr.A6704

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study
J.L. Quon, W. Bala, L.C. Chen, J. Wright, L.H. Kim, M. Han, K. Shpanskaya, E.H. Lee, E. Tong, M. Iv, J. Seekins, M.P. Lungren, K.R.M. Braun, T.Y. Poussaint, S. Laughlin, M.D. Taylor, R.M. Lober, H. Vogel, P.G. Fisher, G.A. Grant, V. Ramaswamy, N.A. Vitanza, C.Y. Ho, M.S.B. Edwards, S.H. Cheshier, K.W. Yeom
American Journal of Neuroradiology Sep 2020, 41 (9) 1718-1725; DOI: 10.3174/ajnr.A6704
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • ABBREVIATIONS:
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSIONS
    • Footnotes
    • References
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Pediatric brain tumor classification using deep learning on MR-images with age fusion
  • Deep Learning Outperforms Classical Machine Learning Methods in Pediatric Brain Tumor Classification through Mass Spectra
  • Pediatric brain tumor classification using deep learning on MR-images from the childrens brain tumor network
  • Pediatric brain tumor classification using deep learning on MR-images from the childrens brain tumor network
  • Pediatric brain tumor type classification using deep learning on MR images from the childrens brain tumor network
  • Radiomics Can Distinguish Pediatric Supratentorial Embryonal Tumors, High-Grade Gliomas, and Ependymomas
  • Crossref (27)
  • Google Scholar

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

  • A Survey of Brain Tumor Segmentation and Classification Algorithms
    Erena Siyoum Biratu, Friedhelm Schwenker, Yehualashet Megersa Ayano, Taye Girma Debelee
    Journal of Imaging 2021 7 9
  • Deep Learning Techniques for the Classification of Brain Tumor: A Comprehensive Survey
    Ayesha Younis, Qiang Li, Mudassar Khalid, Beatrice Clemence, Mohammed Jajere Adamu
    IEEE Access 2023 11
  • Predicting EGFR mutation status by a deep learning approach in patients with non-small cell lung cancer brain metastases
    Oz Haim, Shani Abramov, Ben Shofty, Claudia Fanizzi, Francesco DiMeco, Netanell Avisdris, Zvi Ram, Moran Artzi, Rachel Grossman
    Journal of Neuro-Oncology 2022 157 1
  • Applications of Artificial Intelligence Based on Medical Imaging in Glioma: Current State and Future Challenges
    Jiaona Xu, Yuting Meng, Kefan Qiu, Win Topatana, Shijie Li, Chao Wei, Tianwen Chen, Mingyu Chen, Zhongxiang Ding, Guozhong Niu
    Frontiers in Oncology 2022 12
  • Brain tumor segmentation and classification with hybrid clustering, probabilistic neural networks
    M.D. Javeed, Regonda Nagaraju, Raja Chandrasekaran, Govinda Rajulu, Praveen Tumuluru, M. Ramesh, Sanjay Kumar Suman, Rajeev Shrivastava
    Journal of Intelligent & Fuzzy Systems 2023 45 4
  • Classification of Pediatric Posterior Fossa Tumors Using Convolutional Neural Network and Tabular Data
    Moran Artzi, Erez Redmard, Oron Tzemach, Jonathan Zeltser, Omri Gropper, Jonathan Roth, Ben Shofty, Danil A. Kozyrev, Shlomi Constantini, Liat Ben-Sira
    IEEE Access 2021 9
  • Radiomics Can Distinguish Pediatric Supratentorial Embryonal Tumors, High-Grade Gliomas, and Ependymomas
    M. Zhang, L. Tam, J. Wright, M. Mohammadzadeh, M. Han, E. Chen, M. Wagner, J. Nemalka, H. Lai, A. Eghbal, C.Y. Ho, R.M. Lober, S.H. Cheshier, N.A. Vitanza, G.A. Grant, L.M Prolo, K.W. Yeom, A. Jaju
    American Journal of Neuroradiology 2022 43 4
  • Deep Learning Model for Intracranial Hemangiopericytoma and Meningioma Classification
    Ziyan Chen, Ningrong Ye, Nian Jiang, Qi Yang, Siyi Wanggou, Xuejun Li
    Frontiers in Oncology 2022 12
  • Artificial intelligence applications in pediatric oncology diagnosis
    Yuhan Yang, Yimao Zhang, Yuan Li
    Exploration of Targeted Anti-tumor Therapy 2023
  • Clinical Artificial Intelligence Applications in Radiology
    Felipe Campos Kitamura, Ian Pan, Suely Fazio Ferraciolli, Kristen W. Yeom, Nitamar Abdala
    Radiologic Clinics of North America 2021 59 6

More in this TOC Section

Pediatrics

  • Early Ultrasonic Monitoring of Brain Growth and Later Neurodevelopmental Outcome in Very Preterm Infants
  • Diagnostic Value of Sylvian Fissure Hyperechogenicity in Fetal SAH
  • Feasibility and Added Value of Fetal DTI Tractography in the Evaluation of an Isolated Short Corpus Callosum: Preliminary Results
Show more Pediatrics

Functional

  • Kurtosis and Epileptogenic Tubers: A Pilot Study
  • Glutaric Aciduria Type 1: DK vs. Conventional MRI
  • WM Neuroaxonal Loss in Type 1 Diabetes
Show more Functional

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner
  • Book Reviews

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire