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Andrey Fedorov
PeerJ Author & Reviewer
325 Points

Contributions by role

Author 135
Preprint Author 175
Reviewer 15
Preprint Feedback 15
Answers 2

Contributions by subject area

Bioinformatics
Clinical Trials
Oncology
Radiology and Medical Imaging
Urology
Computational Science
Translational Medicine
Science and Medical Education

By Q&A topic

Bioinformatics
Radiology-and-medical-imaging
Translational-medicine
Science-and-medical-education
Computational-science

Andrey Fedorov

PeerJ Author & Reviewer

Summary

Andrey completed his undergraduate studies at the Ternopol Institute of Computer Information Technologies, Ukraine. He received his MS (2003) and PhD (2009) in computer science from The College of William and Mary. His research interests are at the intersection of imaging informatics, open source software, medical image computing, reproducible science, and cancer research.

Bioinformatics Radiology & Medical Imaging Translational Medicine

Editing Journals

Past or current institution affiliations

Harvard University

Work details

Assistant Professor

Brigham and Women's Hospital / Harvard Medical School
October 2009

Websites

  • Surgical Planning Lab
  • GitHub
  • QIICR
  • Google Scholar
  • MyNCBI
  • Personal web page

PeerJ Contributions

  • Articles 1
  • Preprints 2
  • Feedback 1
  • Questions 2
May 24, 2016
DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
Andriy Fedorov, David Clunie, Ethan Ulrich, Christian Bauer, Andreas Wahle, Bartley Brown, Michael Onken, Jörg Riesmeier, Steve Pieper, Ron Kikinis, John Buatti, Reinhard R. Beichel
https://doi.org/10.7717/peerj.2057 PubMed 27257542
May 20, 2019 - Version: 2
Standardized representation of the LIDC annotations using DICOM
Andrey Fedorov, Matthew Hancock, David Clunie, Mathias Brochhausen, Jonathan Bona, Justin Kirby, John Freymann, Steve Pieper, Hugo Aerts, Ron Kikinis, Fred Prior
https://doi.org/10.7287/peerj.preprints.27378v2
February 20, 2016 - Version: 3
DICOM for quantitative imaging biomarker development: A standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
Andriy Fedorov, David Clunie, Ethan Ulrich, Christian Bauer, Andreas Wahle, Bartley Brown, Michael Onken, Jörg Riesmeier, Steve Pieper, Ron Kikinis, John Buatti, Reinhard R. Beichel
https://doi.org/10.7287/peerj.preprints.1541v3

Provided feedback on

02 Jul 2015

DCEMRI.jl: A fast, validated, open source toolkit for dynamic contrast enhanced MRI analysis

I ran into this while looking at DCE@urLAB. Very nice work! One comment is that your list of publicly available packages for DCE MRI analysis does not include PK modeling tool d...

2 Questions

0
Updated instructions on visualization of the data using 3D Slicer software
about DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
0
DICOM Surface Segmentation support in MeVisLab
about Towards an easier creation of three-dimensional data for embedding into scholarly 3D PDF (Portable Document Format) files