Science-advisor
REGISTER info/FAQ
Login
username
password
     
forgot password?
register here
 
Research articles
  search articles
  reviews guidelines
  reviews
  articles index
My Pages
my alerts
  my messages
  my reviews
  my favorites
 
 
Stat
Members: 3643
Articles: 2'488'730
Articles rated: 2609

29 March 2024
 
  » arxiv » 1811.2629

 Article overview


Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas ; Mauricio Reyes ; Andras Jakab ; Stefan Bauer ; Markus Rempfler ; Alessandro Crimi ; Russell Takeshi Shinohara ; Christoph Berger ; Sung Min Ha ; Martin Rozycki ; Marcel Prastawa ; Esther Alberts ; Jana Lipkova ; John Freymann ; Justin Kirby ; Michel Bilello ; Hassan Fathallah-Shaykh ; Roland Wiest ; Jan Kirschke ; Benedikt Wiestler ; Rivka Colen ; Aikaterini Kotrotsou ; Pamela Lamontagne ; Daniel Marcus ; Mikhail Milchenko ; Arash Nazeri ; Marc-Andre Weber ; Abhishek Mahajan ; Ujjwal Baid ; Dongjin Kwon ; Manu Agarwal ; Mahbubul Alam ; Alberto Albiol ; Antonio Albiol ; Varghese Alex ; Tuan Anh Tran ; Tal Arbel ; Aaron Avery ; Pranjal B. ; Subhashis Banerjee ; Thomas Batchelder ; Kayhan Batmanghelich ; Enzo Battistella ; Martin Bendszus ; Eze Benson ; Jose Bernal ; George Biros ; Mariano Cabezas ; Siddhartha Chandra ; Yi-Ju Chang ; Joseph Chazalon ; Shengcong Chen ; Wei Chen ; Jefferson Chen ; Kun Cheng ; Meinel Christoph ; Roger Chylla ; Albert Clérigues ; Anthony Costa ; Xiaomeng Cui ; Zhenzhen Dai ; Lutao Dai ; Eric Deutsch ; Changxing Ding ; Chao Dong ; Wojciech Dudzik ; Théo Estienne ; Hyung Eun Shin ; Richard Everson ; Jonathan Fabrizio ; Longwei Fang ; Xue Feng ; Lucas Fidon ; Naomi Fridman ; Huan Fu ; David Fuentes ; David G Gering ; Yaozong Gao ; Evan Gates ; Amir Gholami ; Mingming Gong ; Sandra González-Villá ; J. Gregory Pauloski ; Yuanfang Guan ; Sheng Guo ; Sudeep Gupta ; Meenakshi H Thakur ; Klaus H. Maier-Hein ; Woo-Sup Han ; Huiguang He ; Aura Hernández-Sabaté ; Evelyn Herrmann ; Naveen Himthani ; Winston Hsu ; Cheyu Hsu ; Xiaojun Hu ; Xiaobin Hu ; Yan Hu ; Yifan Hu ; Rui Hua ; Teng-Yi Huang ; Weilin Huang ; Quan Huo ; Vivek HV ; Fabian Isensee ; Mobarakol Islam ; Francisco J. Albiol ; Chiatse J. Wang ; Sachin Jambawalikar ; V Jeya Maria Jose ; Weijian Jian ; Peter Jin ; Alain Jungo ; Nicholas K Nuechterlein ; Po-Yu Kao ; Adel Kermi ; Kurt Keutzer ; Mahendra Khened ; Philipp Kickingereder ; Nik King ; Haley Knapp ; Urspeter Knecht ; Lisa Kohli ; Deren Kong ; Xiangmao Kong ; Simon Koppers ; Avinash Kori ; Ganapathy Krishnamurthi ; Piyush Kumar ; Kaisar Kushibar ; Dmitrii Lachinov ; Joon Lee ; Chengen Lee ; Yuehchou Lee ; Szidonia Lefkovits ; Laszlo Lefkovits ; Tengfei Li ; Hongwei Li ; Wenqi Li ; Hongyang Li ; Xiaochuan Li ; Zheng-Shen Lin ; Fengming Lin ; Chang Liu ; Boqiang Liu ; Xiang Liu ; Mingyuan Liu ; Ju Liu ; Xavier Lladó ; Lin Luo ; Khan M. Iftekharuddin ; Yuhsiang M. Tsai ; Jun Ma ; Kai Ma ; Thomas Mackie ; Issam Mahmoudi ; Michal Marcinkiewicz ; Richard McKinley ; Sachin Mehta ; Raghav Mehta ; Raphael Meier ; Dorit Merhof ; Craig Meyer ; Sushmita Mitra ; Aliasgar Moiyadi ; Grzegorz Mrukwa ; Miguel A.B. Monteiro ; Andriy Myronenko ; Eric N Carver ; Jakub Nalepa ; Thuyen Ngo ; Chen Niu ; Eric Oermann ; Arlindo Oliveira ; Arnau Oliver ; Sebastien Ourselin ; Andrew P. French ; Michael P. Pound ; Tony P. Pridmore ; Juan Pablo Serrano-Rubio ; Nikos Paragios ; Brad Paschke ; Linmim Pei ; Suting Peng ; Bao Pham ; Gemma Piella ; G.N. Pillai ; Marie Piraud ; Anmol Popli ; Vesna Prčkovska ; Santi Puch ; Élodie Puybareau ; Xu Qiao ; Yannick R Suter ; Matthew R. Scott ; Swapnil Rane ; Michael Rebsamen ; Hongliang Ren ; Xuhua Ren ; Mina Rezaei ; Pablo Ribalta Lorenzo ; Oliver Rippel ; Charlotte Robert ; Ahana Roy Choudhury ; Aaron S. Jackson ; B. S. Manjunath ; Mostafa Salem ; Joaquim Salvi ; Irina Sánchez ; Dawid Schellingerhout ; Zeina Shboul ; Haipeng Shen ; Dinggang Shen ; Varun Shenoy ; Feng Shi ; Hai Shu ; James Snyder ; Il Song Han ; Mehul Soni ; Jean Stawiaski ; Shashank Subramanian ; Li Sun ; Roger Sun ; Jiawei Sun ; Kay Sun ; Yu Sun ; Guoxia Sun ; Shuang Sun ; Moo Sung Park ; Laszlo Szilagyi ; Sanjay Talbar ; Dacheng Tao ; Dacheng Tao ; Mohamed Tarek Khadir ; Siddhesh Thakur ; Guillaume Tochon ; Tuan Tran ; Kuan-Lun Tseng ; Vadim Turlapov ; Nicholas Tustison ; B. Uma Shankar ; Maria Vakalopoulou ; Sergi Valverde ; Rami Vanguri ; Evgeny Vasiliev ; Tom Vercauteren ; Lasitha Vidyaratne ; Ajeet Vivekanandan ; Guotai Wang ; Qian Wang ; Weichung Wang ; Ning Wen ; Xin Wen ; Leon Weninger ; Wolfgang Wick ; Shaocheng Wu ; Qiang Wu ; Yong Xia ; Yanwu Xu ; Xiaowen Xu ; Peiyuan Xu ; Tsai-Ling Yang ; Xiaoping Yang ; Hao-Yu Yang ; Junlin Yang ; Haojin Yang ; Hongdou Yao ; Brett Young-Moxon ; Xiangyu Yue ; Songtao Zhang ; Angela Zhang ; Kun Zhang ; Xuejie Zhang ; Lichi Zhang ; Xiaoyue Zhang ; Sicheng Zhao ; Yu Zhao ; Yefeng Zheng ; Liming Zhong ; Chenhong Zhou ; Xiaobing Zhou ; Hongtu Zhu ; Weiwei Zong ; Jayashree Kalpathy-Cramer ; Keyvan Farahani ; Christos Davatzikos ; Koen van Leemput ; Bjoern Menze ;
Date 5 Nov 2018
AbstractGliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e. 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that undergone gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.
Source arXiv, 1811.2629
Services Forum | Review | PDF | Favorites   
 
Visitor rating: did you like this article? no 1   2   3   4   5   yes

No review found.
 Did you like this article?

This article or document is ...
important:
of broad interest:
readable:
new:
correct:
Global appreciation:

  Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.

browser claudebot






ScienXe.org
» my Online CV
» Free


News, job offers and information for researchers and scientists:
home  |  contact  |  terms of use  |  sitemap
Copyright © 2005-2024 - Scimetrica