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Large foundation models, known for their strong zero-shot generalization, have excelled in visual and language applications.
Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response
AD Hoover, Valentina Kouznetsova, and Michael Goldbaum · 2000
Earlier work this paper cites.
Evaluation framework for algorithms segmenting short axis cardiac mri
Perry Radau, Yingli Lu, Kim Connelly, Gideon Paul, Alexander J Dick, and Graham A Wright · 2009
Earlier work this paper cites.
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Maria Kuklisova-Murgasova, Paul Aljabar, Latha Srinivasan, Serena J Counsell, Valentina Doria, Ahmed Serag, Ioannis S Gousias, James P Boardman, Mary A Rutherford, A David Edwards, et al · 2011
Earlier work this paper cites.
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Randy L Gollub, Jody M Shoemaker, Margaret D King, Tonya White, Stefan Ehrlich, Scott R Sponheim, Vincent P Clark, Jessica A Turner, Bryon A Mueller, Vince Magnotta, et al · 2013
Earlier work this paper cites.
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Geert Litjens, Robert Toth, Wendy Van De Ven, Caroline Hoeks, Sjoerd Kerkstra, Bram Van Ginneken, Graham Vincent, Gwenael Guillard, Neil Birbeck, Jindang Zhang, et al · 2014
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
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Earlier work this paper cites.
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Guillaume Lemaître, Robert Martí, Jordi Freixenet, Joan C Vilanova, Paul M Walker, and Fabrice Meriaudeau · 2015
Earlier work this paper cites.
Data from pancreas-ct. the cancer imaging archive
Holger R Roth, Amal Farag, E Turkbey, Le Lu, Jiamin Liu, and Ronald M Summers · 2016
Earlier work this paper cites.
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the luna16 challenge
Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas De Bel, Moira SN Berens, Cas Van Den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, et al · 2017
Earlier work this paper cites.
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Xin Zheng, Yong Wang, Guoyou Wang, and Jianguo Liu · 2018
Earlier work this paper cites.
Standardized assessment of automatic segmentation of white matter hyperintensities and results of the wmh segmentation challenge
Hugo J Kuijf, J Matthijs Biesbroek, Jeroen De Bresser, Rutger Heinen, Simon Andermatt, Mariana Bento, Matt Berseth, Mikhail Belyaev, M Jorge Cardoso, Adria Casamitjana, et al · 2019
Earlier work this paper cites.
Amber L Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello, Keyvan Farahani, Bram Van Ginneken, Annette Kopp-Schneider, Bennett A Landman, Geert Litjens, Bjoern Menze, et al · 2019
Earlier work this paper cites.
Panet: Few-shot image semantic segmentation with prototype alignment
Kaixin Wang, Jun Hao Liew, Yingtian Zou, Daquan Zhou, and Jiashi Feng · 2019
Earlier work this paper cites.
Data augmentation using learned transformations for one-shot medical image segmentation
Amy Zhao, Guha Balakrishnan, Fredo Durand, John V Guttag, and Adrian V Dalca · 2019
Earlier work this paper cites.
Segthor: Segmentation of thoracic organs at risk in ct images
Zoé Lambert, Caroline Petitjean, Bernard Dubray, and Su Kuan · 2020
Earlier work this paper cites.
Rose: a retinal oct-angiography vessel segmentation dataset and new model
Yuhui Ma, Huaying Hao, Jianyang Xie, Huazhu Fu, Jiong Zhang, Jianlong Yang, Zhen Wang, Jiang Liu, Yalin Zheng, and Yitian Zhao · 2020
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Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
José Ignacio Orlando, Huazhu Fu, João Barbosa Breda, Karel Van Keer, Deepti R Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, JoonHo Lee, et al · 2020
Cited alongside, same era.
Self-supervision with superpixels: Training few-shot medical image segmentation without annotation
Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart, Huaqi Qiu, and Daniel Rueckert · 2020
Cited alongside, same era.
‘squeeze & excite’guided few-shot segmentation of volumetric images
Abhijit Guha Roy, Shayan Siddiqui, Sebastian Pölsterl, Nassir Navab, and Christian Wachinger · 2020
Cited alongside, same era.
Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
Later among the works it cites.
Medsegdiff: Medical image segmentation with diffusion probabilistic model
Junde Wu, Huihui Fang, Yu Zhang, Yehui Yang, and Yanwu Xu · 2022
Later among the works it cites.
https://tdsc-abus2023.grand-challenge.org , 20203
Tumor detection, segmentation and classification challenge on automated 3d breast ultrasound (abus) 2023 · 2023
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The state of the art in kidney and kidney tumor segmentation in contrast-enhanced ct imaging: Results of the kits19 challenge
Nicholas Heller, Fabian Isensee, Klaus H Maier-Hein, Xiaoshuai Hou, Chunmei Xie, Fengyi Li, Yang Nan, Guangrui Mu, Zhiyong Lin, Miofei Han, et al · 2021
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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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Chaos challenge-combined (ct-mr) healthy abdominal organ segmentation
A Emre Kavur, N Sinem Gezer, Mustafa Barış, Sinem Aslan, Pierre-Henri Conze, Vladimir Groza, Duc Duy Pham, Soumick Chatterjee, Philipp Ernst, Savaş Özkan, et al · 2021
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Word: Revisiting organs segmentation in the whole abdominal region
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Abdomenct-1k: Is abdominal organ segmentation a solved problem?
Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, et al · 2021
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Deep learning saliency maps do not accurately highlight diagnostically relevant regions for medical image interpretation
Adriel Saporta, Xiaotong Gui, Ashwin Agrawal, Anuj Pareek, SQ Truong, CD Nguyen, Van-Doan Ngo, Jayne Seekins, Francis G Blankenberg, AY Ng, et al · 2021
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