Fetching the paper…
Reading the bibliography…
We propose a novel and flexible attention based U-Net architecture referred to as "Voxels-Intersecting Along Orthogonal Levels Attention U-Net" (viola-Unet), for intracranial hemorrhage (ICH) segmentation task in the INSTANCE 2022 Data Challenge on non-contrast computed tomography (CT).
“Volume of intracerebral hemorrhage. a powerful and easy-to-use predictor of 30-day mortality.,”
Joseph P Broderick, Thomas G Brott, John E Duldner, Thomas Tomsick, and Gertrude Huster, · 1993
Earlier work this paper cites.
“The ABCs of measuring intracerebral hemorrhage volumes,”
R. U. Kothari, T. Brott, J. P. Broderick, W. G. Barsan, L. R. Sauerbeck, M. Zuccarello, and J. Khoury, · 1996
Earlier work this paper cites.
“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
Earlier work this paper cites.
“U-Net: Convolutional networks for biomedical image segmentation,”
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, · 2015
Earlier work this paper cites.
“V-net: Fully convolutional neural networks for volumetric medical image segmentation,”
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi, · 2016
Earlier work this paper cites.
“Epidemiology, risk factors, and clinical features of intracerebral hemorrhage: an update,”
Sang Joon An, Tae Jung Kim, and Byung-Woo Yoon, · 2017
Earlier work this paper cites.
“Deeply-supervised cnn for prostate segmentation,”
Qikui Zhu, Bo Du, Baris Turkbey, Peter L Choyke, and Pingkun Yan, · 2017
Earlier work this paper cites.
“SGDR: Stochastic gradient descent with warm restarts,”
Ilya Loshchilov and Frank Hutter, · 2017
Earlier work this paper cites.
“Focal loss for dense object detection,”
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár, · 2017
Cited alongside, same era.
“Squeeze-and-excitation networks,”
Jie Hu, Li Shen, and Gang Sun, · 2018
Cited alongside, same era.
“Group normalization,”
Yuxin Wu and Kaiming He, · 2018
Cited alongside, same era.
“A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT,”
Ali Arab, Betty Chinda, George Medvedev, William Siu, Hui Guo, Tao Gu, Sylvain Moreno, Ghassan Hamarneh, Martin Ester, and Xiaowei Song, · 2020
Cited alongside, same era.
“Intracranial hemorrhage segmentation using a deep convolutional model,”
Murtadha D Hssayeni, Muayad S Croock, Aymen D Salman, Hassan Falah Al-khafaji, Zakaria A Yahya, and Behnaz Ghoraani, · 2020
Cited alongside, same era.
“Dense Dilated Convolutions’ Merging Network for Land Cover Classification,”
“Optimized U-Net for Brain Tumor Segmentation,”
Michał Futrega, Alexandre Milesi, Michal Marcinkiewicz, and Pablo Ribalta, · 2021
Later among the works it cites.
“Extending nn-UNet for brain tumor segmentation,”
Huan Minh Luu and Sung-Hong Park, · 2021
Later among the works it cites.
“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
Later among the works it cites.
“Hematoma expansion context guided intracranial hemorrhage segmentation and uncertainty estimation,”
Xiangyu Li, Gongning Luo, Wei Wang, Kuanquan Wang, Yue Gao, and Shuo Li, · 2021
Later among the works it cites.
“A Robust Deep Learning Segmentation Method for Hematoma Volumetric Detection in Intracerebral Hemorrhage,”
N. Yu, H. Yu, H. Li, N. Ma, C. Hu, and J. Wang, · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Q. Liu, M. Kampffmeyer, R. Jenssen, and A. B. Salberg, · 2020
Cited alongside, same era.
“3D deep neural network segmentation of intracerebral hemorrhage: Development and validation for clinical trials,”
Matthew F Sharrock, W Andrew Mould, Hasan Ali, Meghan Hildreth, Issam A Awad, Daniel F Hanley, and John Muschelli, · 2021
Cited alongside, same era.
Closest in time.
“The 2022 Intracranial Hemorrhage Segmentation Challenge on Non-Contrast head CT (NCCT),” Mar. 2022
Xiangyu Li, Kuanquan Wang, Jinbo Liu, Hongyu Wang, Mingwang Xu, and Xinjie Liang, · 2022
Closest in time.
Massih-Reza Amini, Vasilii Feofanov, Loic Pauletto, Emilie Devijver, and Yury Maximov, · 2022
Closest in time.