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Precise image segmentation provides clinical study with instructive information.
Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
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Comparison and evaluation of methods for liver segmentation from ct datasets
Tobias Heimann, Bram Van Ginneken, Martin A Styner, Yulia Arzhaeva, Volker Aurich, Christian Bauer, Andreas Beck, Christoph Becker, Reinhard Beichel, György Bekes, et al · 2009
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Pet-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques
Habib Zaidi and Issam El Naqa · 2010
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3d image reconstruction for comparison of algorithm database
Luc Soler, Alexandre Hostettler, Vincent Agnus, Arnaud Charnoz, Jean-Baptiste Fasquel, Johan Moreau, Anne-Blandine Osswald, Mourad Bouhadjar, and Jacques Marescaux · 2010
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Laparoscopic partial nephrectomy with segmental renal artery clamping: technique and clinical outcomes
Pengfei Shao, Chao Qin, Changjun Yin, Xiaoxin Meng, Xiaobing Ju, Jie Li, Qiang Lv, Wei Zhang, and Zhengquan Xu · 2011
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Value of multidetector computed tomography image segmentation for preoperative planning in general surgery
Vincenzo Ferrari, Marina Carbone, Carla Cappelli, Luigi Boni, Franca Melfi, Mauro Ferrari, Franco Mosca, and Andrea Pietrabissa · 2012
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Precise segmental renal artery clamping under the guidance of dual-source computed tomography angiography during laparoscopic partial nephrectomy
Pengfei Shao, Lijun Tang, Pu Li, Yi Xu, Chao Qin, Qiang Cao, Xiaobing Ju, Xiaoxin Meng, Qiang Lv, Jie Li, et al · 2012
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The cancer imaging archive (tcia): maintaining and operating a public information repository
Kenneth Clark, Bruce Vendt, Kirk Smith, John Freymann, Justin Kirby, Paul Koppel, Stephen Moore, Stanley Phillips, David Maffitt, Michael Pringle, et al · 2013
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Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
Bennett Landman, Zhoubing Xu, J Igelsias, Martin Styner, T Langerak, and Arno Klein · 2015
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Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation
Holger R Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B Turkbey, and Ronald M Summers · 2015
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Data from pancreas-ct. the cancer imaging archive
Holger R Roth, Amal Farag, E Turkbey, Le Lu, Jiamin Liu, and Ronald M Summers · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Patrick Ferdinand Christ, Florian Ettlinger, Felix Grün, Mohamed Ezzeldin A Elshaera, Jana Lipkova, Sebastian Schlecht, Freba Ahmaddy, Sunil Tatavarty, Marc Bickel, Patrick Bilic, et al · 2017
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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
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Unet++: A nested u-net architecture for medical image segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang · 2018
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Mdu-net: Multi-scale densely connected u-net for biomedical image segmentation
Jiawei Zhang, Yuzhen Jin, Jilan Xu, Xiaowei Xu, and Yanchun Zhang · 2018
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Ct organ segmentation using gpu data augmentation, unsupervised labels and iou loss
Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, and Daniel L Rubin · 2018
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Brain tumor detection and segmentation in mr images using deep learning
Sidra Sajid, Saddam Hussain, and Amna Sarwar · 2019
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Ce-net: Context encoder network for 2d medical image segmentation
Zaiwang Gu, Jun Cheng, Huazhu Fu, Kang Zhou, Huaying Hao, Yitian Zhao, Tianyang Zhang, Shenghua Gao, and Jiang Liu · 2019
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Ct-org: Ct volumes with multiple organ segmentations [dataset]
Blaine Rister, Kaushik Shivakumar, Tomomi Nobashi, and Daniel L Rubin · 2019
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Chaos - combined (ct-mr) healthy abdominal organ segmentation challenge data
Ali Emre Kavur, M. Alper Selver, Oğuz Dicle, Mustafa Barış, and N. Sinem Gezer · 2019
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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
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Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
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Segthor: Segmentation of thoracic organs at risk in ct images, 2019
Z. Lambert, C. Petitjean, B. Dubray, and S. Ruan · 2019
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Deep learning for cardiac image segmentation: a review
Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni, Jinming Duan, Wenjia Bai, and Daniel Rueckert · 2020
Cited alongside, same era.
Doubleu-net: A deep convolutional neural network for medical image segmentation
Debesh Jha, Michael A Riegler, Dag Johansen, Pål Halvorsen, and Håvard D Johansen · 2020
Cited alongside, same era.
Dense-inception u-net for medical image segmentation
Ziang Zhang, Chengdong Wu, Sonya Coleman, and Dermot Kerr · 2020
Cited alongside, same era.
A comprehensive review of deep learning in colon cancer
Ishak Pacal, Dervis Karaboga, Alper Basturk, Bahriye Akay, and Ufuk Nalbantoglu · 2020
Cited alongside, same era.
A survey of recent interactive image segmentation methods
Hiba Ramadan, Chaymae Lachqar, and Hamid Tairi · 2020
Cited alongside, same era.
Linguistic structure guided context modeling for referring image segmentation
U-net-based medical image segmentation
Xiao-Xia Yin, Le Sun, Yuhan Fu, Ruiliang Lu, Yanchun Zhang, et al · 2022
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R2u++: a multiscale recurrent residual u-net with dense skip connections for medical image segmentation
Mehreen Mubashar, Hazrat Ali, Christer Grönlund, and Shoaib Azmat · 2022
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Unetr: Transformers for 3d medical image segmentation
Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger R Roth, and Daguang Xu · 2022
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nnformer: Interleaved transformer for volumetric segmentation, 2022
Hong-Yu Zhou, Jiansen Guo, Yinghao Zhang, Lequan Yu, Liansheng Wang, and Yizhou Yu · 2022
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Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images, 2022
Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger Roth, and Daguang Xu · 2022
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Tianrui Hui, Si Liu, Shaofei Huang, Guanbin Li, Sansi Yu, Faxi Zhang, and Jizhong Han · 2020
Cited alongside, same era.
Comparison of semi-automatic and deep learning based automatic methods for liver segmentation in living liver transplant donors
A. Emre Kavur, Naciye Sinem Gezer, Mustafa Barış, Yusuf Şahin, Savaş Özkan, Bora Baydar, Ulaş Yüksel, Çağlar Kılıkçıer, Şahin Olut, Gözde Bozdağı Akar, Gözde Ünal, Oğuz Dicle, and M. Alper Selver · 2020
Cited alongside, same era.
Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation
Yuting He, Guanyu Yang, Jian Yang, Yang Chen, Youyong Kong, Jiasong Wu, Lijun Tang, Xiaomei Zhu, Jean-Louis Dillenseger, Pengfei Shao, et al · 2020
Cited alongside, same era.
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 · 2020
Cited alongside, same era.
A vertebral segmentation dataset with fracture grading
Maximilian T Löffler, Anjany Sekuboyina, Alina Jacob, Anna-Lena Grau, Andreas Scharr, Malek El Husseini, Mareike Kallweit, Claus Zimmer, Thomas Baum, and Jan S Kirschke · 2020
Cited alongside, same era.
Fourier features let networks learn high frequency functions in low dimensional domains, 2020
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2020
Cited alongside, same era.
Prognostic value of deep learning-mediated treatment monitoring in lung cancer patients receiving immunotherapy
Stefano Trebeschi, Zuhir Bodalal, Thierry N Boellaard, Teresa M Tareco Bucho, Silvia G Drago, Ieva Kurilova, Adriana M Calin-Vainak, Andrea Delli Pizzi, Mirte Muller, Karlijn Hummelink, et al · 2021
Cited alongside, same era.
Self-supervised pre-training of swin transformers for 3d medical image analysis
Yucheng Tang, Dong Yang, Wenqi Li, Holger R Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh · 2022
Later among the works it cites.
Deep learning techniques for tumor segmentation: a review
Huiyan Jiang, Zhaoshuo Diao, and Yu-Dong Yao · 2022
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Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation
Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, et al · 2022
Later among the works it cites.
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, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, and Xiaoping Yang · 2022
Later among the works it cites.
Totalsegmentator: Robust segmentation of 104 anatomical structures in ct images 2022
J Wasserthal, M Meyer, HC Breit, J Cyriac, S Yang, and M Segeroth · 2022
Later among the works it cites.
WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from ct image
Xiangde Luo, Wenjun Liao, Jianghong Xiao, Jieneng Chen, Tao Song, Xiaofan Zhang, Kang Li, Dimitris N. Metaxas, Guotai Wang, and Shaoting Zhang · 2022
Later among the works it cites.
Simmim: A simple framework for masked image modeling, 2022
Zhenda Xie, Zheng Zhang, Yue Cao, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai, and Han Hu · 2022
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3d ux-net: A large kernel volumetric convnet modernizing hierarchical transformer for medical image segmentation, 2023
Ho Hin Lee, Shunxing Bao, Yuankai Huo, and Bennett A. Landman · 2023
Closest in time.
The liver tumor segmentation benchmark (lits)
Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, et al · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Segment anything in medical images, 2023
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, and Bo Wang · 2023
Closest in time.
Junlong Cheng, Jin Ye, Zhongying Deng, Jianpin Chen, Tianbin Li, Haoyu Wang, Yanzhou Su, Ziyan Huang, Jilong Chen, Lei Jiang, et al · 2023
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Sam-med3d, 2023
Haoyu Wang, Sizheng Guo, Jin Ye, Zhongying Deng, Junlong Cheng, Tianbin Li, Jianpin Chen, Yanzhou Su, Ziyan Huang, Yiqing Shen, Bin Fu, Shaoting Zhang, Junjun He, and Yu Qiao · 2023
Closest in time.
Han-seg: The head and neck organ-at-risk ct and mr segmentation dataset
Gašper Podobnik, Primož Strojan, Primož Peterlin, Bulat Ibragimov, and Tomaž Vrtovec · 2023
Closest in time.
The kits21 challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase ct, 2023
Nicholas Heller, Fabian Isensee, Dasha Trofimova, Resha Tejpaul, Zhongchen Zhao, Huai Chen, Lisheng Wang, Alex Golts, et al · 2023
Closest in time.
https://qubiq21.grand-challenge.org/
Quantification of uncertainties in biomedical image quantification challenge 2021 · 2023
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Clip-driven universal model for organ segmentation and tumor detection, 2023
Jie Liu, Yixiao Zhang, Jie-Neng Chen, Junfei Xiao, Yongyi Lu, Bennett A. Landman, Yixuan Yuan, Alan Yuille, Yucheng Tang, and Zongwei Zhou · 2023
Closest in time.
Boosting weakly-supervised referring image segmentation via progressive comprehension, 2024
Zaiquan Yang, Yuhao Liu, Jiaying Lin, Gerhard Hancke, and Rynson W. H. Lau · 2024
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M3d: Advancing 3d medical image analysis with multi-modal large language models, 2024
Fan Bai, Yuxin Du, Tiejun Huang, Max Q. H. Meng, and Bo Zhao · 2024
Closest in time.