Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

L. Pennig; R. Shahzad; L. Caldeira; S. Lennartz; F. Thiele; L. Goertz; D. Zopfs; A.-K. Meißner; G. Fürtjes; M. Perkuhn; C. Kabbasch; S. Grau; J. Borggrefe; K.R. Laukamp

doi:10.3174/ajnr.A6982

Research ArticleAdult Brain

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

L. Pennig, R. Shahzad, L. Caldeira, S. Lennartz, F. Thiele, L. Goertz, D. Zopfs, A.-K. Meißner, G. Fürtjes, M. Perkuhn, C. Kabbasch, S. Grau, J. Borggrefe and K.R. Laukamp

American Journal of Neuroradiology April 2021, 42 (4) 655-662; DOI: https://doi.org/10.3174/ajnr.A6982

L. Pennig

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for L. Pennig

R. Shahzad

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

cPhilips Innovative Technologies (R.S., F.T., M.P.), Aachen, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for R. Shahzad

L. Caldeira

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for L. Caldeira

S. Lennartz

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for S. Lennartz

F. Thiele

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

cPhilips Innovative Technologies (R.S., F.T., M.P.), Aachen, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for F. Thiele

L. Goertz

bCenter for Neurosurgery (L.G., G.F., S.G.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for L. Goertz

D. Zopfs

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for D. Zopfs

A.-K. Meißner

dDepartment of Stereotaxy and Functional Neurosurgery (A.-K.M., G.F.), Center for Neurosurgery, University Hospital Cologne, Cologne, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for A.-K. Meißner

G. Fürtjes

bCenter for Neurosurgery (L.G., G.F., S.G.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

dDepartment of Stereotaxy and Functional Neurosurgery (A.-K.M., G.F.), Center for Neurosurgery, University Hospital Cologne, Cologne, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for G. Fürtjes

M. Perkuhn

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

cPhilips Innovative Technologies (R.S., F.T., M.P.), Aachen, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for M. Perkuhn

C. Kabbasch

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for C. Kabbasch

S. Grau

bCenter for Neurosurgery (L.G., G.F., S.G.), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for S. Grau

J. Borggrefe

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for J. Borggrefe

K.R. Laukamp

aFrom the Institute for Diagnostic and Interventional Radiology (L.P., R.S., L.C., S.L., F.T., D.Z., M.P., C.K., J.B., K.R.L.)

eDepartment of Radiology (K.R.L.), University Hospitals Cleveland Medical Center, Cleveland, Ohio

fDepartment of Radiology (K.R.L.), Case Western Reserve University, Cleveland, Ohio

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for K.R. Laukamp

Article
Figures & Data
Supplemental
Info & Metrics
Responses
References
PDF

Submit a Response to This Article

Compose eLetter

Title *

Contents

More information about text formats

Plain text

No HTML tags allowed.
Web page addresses and e-mail addresses turn into links automatically.
Lines and paragraphs break automatically.

Author Information

Contributors
First Name and Middle Initial * First or given name, e.g. 'Peter'. Last Name * Your last, or family, name, e.g. 'MacMoody'. Email Address * Your email address, e.g. higgs-boson@gmail.com Occupation * Your role and/or occupation, e.g. 'Orthopedic Surgeon'. Affiliation * Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.

Statement of Competing Interests

Competing interests? *

Yes

Please describe the competing interests

Vertical Tabs

Jump to comment:

No eLetters have been published for this article.

PreviousNext

In this issue

American Journal of Neuroradiology

Vol. 42, Issue 4

1 Apr 2021

Table of Contents
Index by author
Complete Issue (PDF)

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.

Your Email *

Your Name *

Send To *

Enter multiple addresses on separate lines or separate them with commas.

You are going to email the following Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

Message Subject (Your Name) has sent you a message from American Journal of Neuroradiology

Message Body (Your Name) thought you would like to see the American Journal of Neuroradiology web site.

Your Personal Message

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

Cite this article

L. Pennig, R. Shahzad, L. Caldeira, S. Lennartz, F. Thiele, L. Goertz, D. Zopfs, A.-K. Meißner, G. Fürtjes, M. Perkuhn, C. Kabbasch, S. Grau, J. Borggrefe, K.R. Laukamp

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

American Journal of Neuroradiology Apr 2021, 42 (4) 655-662; DOI: 10.3174/ajnr.A6982

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

Bookmark this article

User Name *

Password *

Remember my user name & password.

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

L. Pennig, R. Shahzad, L. Caldeira, S. Lennartz, F. Thiele, L. Goertz, D. Zopfs, A.-K. Meißner, G. Fürtjes, M. Perkuhn, C. Kabbasch, S. Grau, J. Borggrefe, K.R. Laukamp

American Journal of Neuroradiology Apr 2021, 42 (4) 655-662; DOI: 10.3174/ajnr.A6982

Share This Article:

Tweet Widget
Facebook Like
Google Plus One

Purchase

Jump to section

Article
Figures & Data
Supplemental
Info & Metrics
Responses
References
PDF

PubMed
Google Scholar

Cited By...

Development of an optimized machine learning approach for assessing brain metastatic burden in preclinical models
Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post Stereotactic Radiosurgery

Crossref (33)
Google Scholar

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

Automatic Classification of Melanoma Skin Cancer with Deep Convolutional Neural Networks

Khalil Aljohani, Turki Turki

AI 2022 3 2
Fully Automated MR Detection and Segmentation of Brain Metastases in Non‐small Cell Lung Cancer Using Deep Learning

Stephanie T. Jünger, Ulrike Cornelia Isabel Hoyer, Diana Schaufler, Kai Roman Laukamp, Lukas Goertz, Frank Thiele, Jan‐Peter Grunz, Marc Schlamann, Michael Perkuhn, Christoph Kabbasch, Thorsten Persigehl, Stefan Grau, Jan Borggrefe, Matthias Scheffler, Rahil Shahzad, Lenhard Pennig

Journal of Magnetic Resonance Imaging 2021 54 5
Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis

Burak B. Ozkara, Melissa M. Chen, Christian Federau, Mert Karabacak, Tina M. Briere, Jing Li, Max Wintermark

Cancers 2023 15 2
Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study

Josef A. Buchner, Florian Kofler, Lucas Etzel, Michael Mayinger, Sebastian M. Christ, Thomas B. Brunner, Andrea Wittig, Björn Menze, Claus Zimmer, Bernhard Meyer, Matthias Guckenberger, Nicolaus Andratschke, Rami A. El Shafie, Jürgen Debus, Susanne Rogers, Oliver Riesterer, Katrin Schulze, Horst J. Feldmann, Oliver Blanck, Constantinos Zamboglou, Konstantinos Ferentinos, Robert Wolff, Kerstin A. Eitz, Stephanie E. Combs, Denise Bernhardt, Benedikt Wiestler, Jan C. Peeken

Radiotherapy and Oncology 2023 178
Recent Outcomes and Challenges of Artificial Intelligence, Machine Learning, and Deep Learning in Neurosurgery

Wireko Andrew Awuah, Favour Tope Adebusoye, Jack Wellington, Lian David, Abdus Salam, Amanda Leong Weng Yee, Edouard Lansiaux, Rohan Yarlagadda, Tulika Garg, Toufik Abdul-Rahman, Jacob Kalmanovich, Goshen David Miteu, Mrinmoy Kundu, Nikitina Iryna Mykolaivna

World Neurosurgery: X 2024 23
2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data

Jon André Ottesen, Darvin Yi, Elizabeth Tong, Michael Iv, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Atle Bjørnerud, Greg Zaharchuk, Endre Grøvik

Frontiers in Neuroinformatics 2023 16
Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks

Irada Pflüger, Tassilo Wald, Fabian Isensee, Marianne Schell, Hagen Meredig, Kai Schlamp, Denise Bernhardt, Gianluca Brugnara, Claus Peter Heußel, Juergen Debus, Wolfgang Wick, Martin Bendszus, Klaus H Maier-Hein, Philipp Vollmuth

Neuro-Oncology Advances 2022 4 1
Brain metastasis tumor segmentation and detection using deep learning algorithms: A systematic review and meta-analysis

Ting-Wei Wang, Ming-Sheng Hsu, Wei-Kai Lee, Hung-Chuan Pan, Huai-Che Yang, Cheng-Chia Lee, Yu-Te Wu

Radiotherapy and Oncology 2024 190
Automated Detection of Brain Metastases on T1‐Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy

Gabriel Chartrand, Ramón D. Emiliani, Sophie A. Pawlowski, Daniel A. Markel, Houda Bahig, Alexandre Cengarle‐Samak, Selvan Rajakesari, Jeremi Lavoie, Simon Ducharme, David Roberge

Journal of Magnetic Resonance Imaging 2022 56 6
Detection of Intracranial Aneurysms Using Multiphase CT Angiography with a Deep Learning Model

Jinglu Wang, Jie Sun, Jingxu Xu, Shiyu Lu, Hao Wang, Chencui Huang, Fandong Zhang, Yizhou Yu, Xiang Gao, Ming Wang, Yu Wang, Xinzhong Ruan, Yuning Pan

Academic Radiology 2023 30 11

Adult Brain

Diagnostic Neuroradiology of Monoclonal Antibodies
Segmentation of Brain Metastases with BLAST
NCCT vs. MRI for Brain Atrophy in Acute Stroke

Show more Adult Brain

Functional

Glutaric Aciduria Type 1: DK vs. Conventional MRI
Kurtosis and Epileptogenic Tubers: A Pilot Study
Predicting Outcomes in Tuberous Sclerosis Epilepsy

Show more Functional

Main menu

User menu

Search

American Journal of Neuroradiology

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

Plain text

Vertical Tabs

Jump to comment:

In this issue

Citation Manager Formats

Related Articles

Cited By...

More in this TOC Section

Adult Brain

Functional

Similar Articles

Indexed Content

Cases

Special Collections

Resources

Multimedia

About Us

American Society of Neuroradiology