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Metrics optimized in complex machine learning tasks are often selected in an ad-hoc manner.
On the theory of contingency and its relation to association and normal correlation , volume 1
Karl Pearson · 1904
Earlier work this paper cites.
The distribution of the flora in the alpine zone. 1
Paul Jaccard · 1912
Earlier work this paper cites.
On the generalized distance in statistics
Prasanta Chandra Mahalanobis · 1936
Earlier work this paper cites.
Measures of the amount of ecologic association between species
Lee R Dice · 1945
Earlier work this paper cites.
A coefficient of agreement for nominal scales
Jacob Cohen · 1960
Earlier work this paper cites.
Objective criteria for the evaluation of clustering methods
William M Rand · 1971
Earlier work this paper cites.
Intraclass correlations: uses in assessing rater reliability
Patrick E Shrout and Joseph L Fleiss · 1979
Earlier work this paper cites.
Comparing partitions
Lawrence Hubert and Phipps Arabie · 1985
Earlier work this paper cites.
Comparing images using the hausdorff distance
Daniel P Huttenlocher, Gregory A. Klanderman, and William J Rucklidge · 1993
Earlier work this paper cites.
Elements of information theory
Thomas M Cover · 1999
Earlier work this paper cites.
Valmet: A new validation tool for assessing and improving 3d object segmentation
Guido Gerig, Matthieu Jomier, and Miranda Chakos · 2001
Earlier work this paper cites.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik · 2001
Earlier work this paper cites.
Comparing clusterings by the variation of information
Marina Meilă · 2003
Earlier work this paper cites.
Cortical algorithms for perceptual grouping
Pieter R Roelfsema · 2006
Earlier work this paper cites.
FactoMineR: A package for multivariate analysis
Sébastien Lê, Julie Josse, and François Husson · 2008
Earlier work this paper cites.
A multidimensional segmentation evaluation for medical image data
Rubén Cárdenes, Rodrigo de Luis-Garcia, and Meritxell Bach-Cuadra · 2009
Earlier work this paper cites.
Label fusion in atlas-based segmentation using a selective and iterative method for performance level estimation (simple)
Thomas Robin Langerak, Uulke A van der Heide, Alexis NTJ Kotte, Max A Viergever, Marco Van Vulpen, and Josien PW Pluim · 2010
Earlier work this paper cites.
Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group
Patrick Y Wen, David R Macdonald, David A Reardon, Timothy F Cloughesy, A Gregory Sorensen, Evanthia Galanis, John DeGroot, Wolfgang Wick, Mark R Gilbert, Andrew B Lassman, et al · 2010
Earlier work this paper cites.
Points of view: Color blindness
Bang Wong · 2011
Earlier work this paper cites.
Freesurfer
Bruce Fischl · 2012
Earlier work this paper cites.
Evaluating segmentation error without ground truth
Timo Kohlberger, Vivek Singh, Chris Alvino, Claus Bahlmann, and Leo Grady · 2012
Earlier work this paper cites.
A century of gestalt psychology in visual perception: I. perceptual grouping and figure–ground organization
Johan Wagemans, James H Elder, Michael Kubovy, Stephen E Palmer, Mary A Peterson, Manish Singh, and Rüdiger von der Heydt · 2012
Earlier work this paper cites.
Metrics based on average distance between sets
Osamu Fujita · 2013
Cited alongside, same era.
Automatic ultrasound–mri registration for neurosurgery using the 2d and 3d lc2 metric
Bernhard Fuerst, Wolfgang Wein, Markus Müller, and Nassir Navab · 2014
Cited alongside, same era.
The multimodal brain tumor image segmentation benchmark (brats)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
Cited alongside, same era.
Eano guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma
Michael Weller, Martin Van Den Bent, Kirsten Hopkins, Jörg C Tonn, Roger Stupp, Andrea Falini, Elizabeth Cohen-Jonathan-Moyal, Didier Frappaz, Roger Henriksson, Carmen Balana, et al · 2014
Cited alongside, same era.
Fitting linear mixed-effects models using lme4
Douglas Bates, Martin Mächler, Ben Bolker, and Steve Walker · 2015
Cited alongside, same era.
Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch, Ruheena Mendes, Michelle Livne, Jeffrey De Fauw, Yojan Patel, Clemens Meyer, Harry Askham, Bernardino Romera-Paredes, et al · 2018
Later among the works it cites.
How to exploit weaknesses in biomedical challenge design and organization
Annika Reinke, Matthias Eisenmann, Sinan Onogur, Marko Stankovic, Patrick Scholz, Peter M Full, Hrvoje Bogunovic, Bennett A Landman, Oskar Maier, Bjoern Menze, et al · 2018
Later among the works it cites.
The liver tumor segmentation benchmark (lits)
Patrick Bilic, Patrick Ferdinand Christ, Eugene Vorontsov, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, et al · 2019
Later among the works it cites.
Weakly-supervised white and grey matter segmentation in 3d brain ultrasound
Beatrice Demiray, Julia Rackerseder, Stevica Bozhinoski, and Nassir Navab · 2019
Later among the works it cites.
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Deep convolutional encoder networks for multiple sclerosis lesion segmentation. vol. 9556, 2015
Tom Brosch, Y Yoo, Lisa YW Tang, David KB Li, Anthony Traboulsee, and R Tam · 2015
Cited alongside, same era.
jspsych: A javascript library for creating behavioral experiments in a web browser
Joshua R De Leeuw · 2015
Cited alongside, same era.
Multi-scale 3d cnns for segmentation of brain lesions in multi-modal mri
Konstantinos Kamnitsas, Liang Chen, Christian Ledig, Daniel Rueckert, and Ben Glocker · 2015
Cited alongside, same era.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Cited alongside, same era.
Metrics for evaluating 3d medical image segmentation: analysis, selection, and tool
Abdel Aziz Taha and Allan Hanbury · 2015
Cited alongside, same era.
The importance of skip connections in biomedical image segmentation
Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand, Samuel Kadoury, and Chris Pal · 2016
Cited alongside, same era.
V-net: Fully convolutional neural networks for volumetric medical image segmentation
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016
Cited alongside, same era.
Brain tumor segmentation using an ensemble of 3d u-nets and overall survival prediction using radiomic features
Xue Feng, Nicholas Tustison, and Craig Meyer · 2019
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Reducing the hausdorff distance in medical image segmentation with convolutional neural networks
Davood Karimi and Septimiu E Salcudean · 2019
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Segmenting brain tumors from mri using cascaded multi-modal u-nets
Michaland et al Marcinkiewicz · 2019
Later among the works it cites.
Ensembles of densely-connected cnns with label-uncertainty for brain tumor segmentation
Richard McKinley, Raphael Meier, and Roland Wiest · 2019
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3d-espnet with pyramidal refinement for volumetric brain tumor image segmentation
Nicholas Nuechterlein and Sachin Mehta · 2019
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Segmentation of brain tumors and patient survival prediction: Methods for the brats 2018 challenge
Leon Weninger, Oliver Rippel, Simon Koppers, and Dorit Merhof · 2019
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Multi-view semi-supervised 3d whole brain segmentation with a self-ensemble network
Yuan-Xing Zhao, Yan-Ming Zhang, Ming Song, and Cheng-Lin Liu · 2019
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nnu-net for brain tumor segmentation
Fabian Isensee, Paul F Jäger, Peter M Full, Philipp Vollmuth, and Klaus H Maier-Hein · 2020
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Brats toolkit: translating brats brain tumor segmentation algorithms into clinical and scientific practice
Florian Kofler, Christoph Berger, Diana Waldmannstetter, Jana Lipkova, Ivan Ezhov, Giles Tetteh, Jan Kirschke, Claus Zimmer, Benedikt Wiestler, and Bjoern H Menze · 2020
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Evaluation: from precision, recall and f-measure to roc, informedness, markedness and correlation
David MW Powers · 2020
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Verse: a vertebrae labelling and segmentation benchmark
Anjany Sekuboyina, Amirhossein Bayat, Malek E Husseini, Maximilian Löffler, Markus Rempfler, Jan Kukačka, Giles Tetteh, Alexander Valentinitsch, Christian Payer, Martin Urschler, et al · 2020
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Classification assessment methods
Alaa Tharwat · 2020
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nnu-net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein · 2021
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pymia: A python package for data handling and evaluation in deep learning-based medical image analysis
Alain Jungo, Olivier Scheidegger, Mauricio Reyes, and Fabian Balsiger · 2021
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performance: An r package for assessment, comparison and testing of statistical models
Daniel Lüdecke, Mattan S Ben-Shachar, Indrajeet Patil, Philip Waggoner, and Dominique Makowski · 2021
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performance: An R package for assessment, comparison and testing of statistical models
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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, et al · 2022
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