D
Duygu Sarikaya
Researcher at Gazi University
Publications - 21
Citations - 4430
Duygu Sarikaya is an academic researcher from Gazi University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 9, co-authored 16 publications receiving 3179 citations. Previous affiliations of Duygu Sarikaya include University at Buffalo & TOBB University of Economics and Technology.
Papers
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Journal ArticleDOI
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
Bjoern H. Menze,Andras Jakab,Stefan Bauer,Jayashree Kalpathy-Cramer,Keyvan Farahani,Justin Kirby,Yuliya Burren,N Porz,Johannes Slotboom,Roland Wiest,Levente Lanczi,Elizabeth R. Gerstner,Marc-André Weber,Tal Arbel,Brian B. Avants,Nicholas Ayache,Patricia Buendia,D. Louis Collins,Nicolas Cordier,Jason J. Corso,Antonio Criminisi,Tilak Das,Hervé Delingette,Çağatay Demiralp,Christopher R. Durst,Michel Dojat,Senan Doyle,Joana Festa,Florence Forbes,Ezequiel Geremia,Ben Glocker,Polina Golland,Xiaotao Guo,Andac Hamamci,Khan M. Iftekharuddin,Raj Jena,Nigel M. John,Ender Konukoglu,Danial Lashkari,José Mariz,Raphael Meier,Sérgio Pereira,Doina Precup,Stephen J. Price,Tammy Riklin Raviv,Syed M. S. Reza,Michael Ryan,Duygu Sarikaya,Lawrence H. Schwartz,Hoo-Chang Shin,Jamie Shotton,Carlos A. Silva,Nuno Sousa,Nagesh K. Subbanna,Gábor Székely,Thomas J. Taylor,Owen M. Thomas,Nicholas J. Tustison,Gozde Unal,Flor Vasseur,Max Wintermark,Dong Hye Ye,Liang Zhao,Binsheng Zhao,Darko Zikic,Marcel Prastawa,Mauricio Reyes,Koen Van Leemput +67 more
TL;DR: The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) as mentioned in this paper was organized in conjunction with the MICCAI 2012 and 2013 conferences, and twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low and high grade glioma patients.
Journal ArticleDOI
MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans
Adriënne M. Mendrik,Koen L. Vincken,Hugo J. Kuijf,Marcel Breeuwer,Willem H. Bouvy,Jeroen de Bresser,Amir Alansary,Marleen de Bruijne,Aaron Carass,Ayman El-Baz,Amod Jog,Ranveer Katyal,Ali R. Khan,Fedde van der Lijn,Qaiser Mahmood,Ryan Mukherjee,Annegreet van Opbroek,Sahil Paneri,Sérgio Pereira,Mikael Persson,Martin Rajchl,Duygu Sarikaya,Örjan Smedby,Carlos A. Silva,Henri A. Vrooman,Saurabh Vyas,Chunliang Wang,Liang Zhao,Geert Jan Biessels,Max A. Viergever +29 more
TL;DR: The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand.
Journal ArticleDOI
Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection
TL;DR: This approach will be the first to incorporate deep neural networks for tool detection and localization in RAS videos, and applies a region proposal network (RPN) and a multimodal two stream convolutional network for object detection to jointly predict objectness and localization on a fusion of image and temporal motion cues.
Journal ArticleDOI
Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection
TL;DR: In this paper, a multi-modal convolutional neural network (CNN) was proposed for tool detection and localization in robot-assisted surgery (RAS) videos using a strictly computer vision approach and the recent advances of deep learning.
Journal ArticleDOI
Surgical Data Science - from Concepts toward Clinical Translation
Lena Maier-Hein,Lena Maier-Hein,Lena Maier-Hein,Matthias Eisenmann,Duygu Sarikaya,Duygu Sarikaya,Keno März,Toby Collins,Anand Malpani,Johannes Fallert,Hubertus Feussner,Stamatia Giannarou,Pietro Mascagni,Hirenkumar Nakawala,Adrian Park,Carla M. Pugh,Danail Stoyanov,Swaroop Vedula,Kevin Cleary,Gabor Fichtinger,Germain Forestier,Germain Forestier,Bernard Gibaud,Teodor P. Grantcharov,Teodor P. Grantcharov,Makoto Hashizume,Doreen Heckmann-Nötzel,Hannes Kenngott,Ron Kikinis,Lars Mündermann,Nassir Navab,Nassir Navab,Sinan Onogur,Tobias Roß,Tobias Roß,Raphael Sznitman,Russell H. Taylor,Minu D. Tizabi,Martin Wagner,Gregory D. Hager,Thomas Neumuth,Nicolas Padoy,Justin W. Collins,Ines Gockel,Jan Goedeke,Daniel A. Hashimoto,Daniel A. Hashimoto,Luc Joyeux,Kyle Lam,Daniel R. Leff,Amin Madani,Hani J. Marcus,Ozanan R. Meireles,Alexander Seitel,Dogu Teber,Frank Ückert,Beat P. Müller-Stich,Pierre Jannin,Stefanie Speidel +58 more
TL;DR: Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data as mentioned in this paper.