Fetching the paper…
Reading the bibliography…
An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection.
3d image reconstruction for comparison of algorithm database: A patient specific anatomical and medical image database
L Soler, A Hostettler, V Agnus, A Charnoz, J Fasquel, J Moreau, A Osswald, M Bouhadjar, and J Marescaux · 2010
Earlier work this paper cites.
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
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.
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
Earlier work this paper cites.
Entity embeddings of categorical variables
Cheng Guo and Felix Berkhahn · 2016
Earlier work this paper cites.
Multi-atlas labeling beyond the cranial vault-workshop and challenge
Bennett Landman, Zhoubing Xu, Juan Eugenio Igelsias, Martin Styner, Thomas Robin Langerak, and Arno Klein · 2017
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Earlier work this paper cites.
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
Earlier work this paper cites.
Attention u-net: Learning where to look for the pancreas
Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla, Bernhard Kainz, et al · 2018
Earlier work this paper cites.
Multi-modal learning from unpaired images: Application to multi-organ segmentation in ct and mri
Vanya V Valindria, Nick Pawlowski, Martin Rajchl, Ioannis Lavdas, Eric O Aboagye, Andrea G Rockall, Daniel Rueckert, and Ben Glocker · 2018
Earlier work this paper cites.
Deeplesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning
Ke Yan, Xiaosong Wang, Le Lu, and Ronald M Summers · 2018
Earlier work this paper 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
Earlier work this paper cites.
An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis
Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, Yun Liu, Shiro Kadowaki, Kunal Nagpal, Timo Kohlberger, Jeffrey Dean, Greg S Corrado, Jason D Hipp, et al · 2019
Earlier work this paper cites.
Med3d: Transfer learning for 3d medical image analysis
Sihong Chen, Kai Ma, and Yefeng Zheng · 2019
Earlier work this paper cites.
Transfer learning for 3d medical image analysis
S Chen, K Ma, and Y Zheng · 2019
Earlier work this paper cites.
Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample · 2019
Earlier work this paper cites.
Nicholas Heller, Niranjan Sathianathen, Arveen Kalapara, Edward Walczak, Keenan Moore, Heather Kaluzniak, Joel Rosenberg, Paul Blake, Zachary Rengel, Makinna Oestreich, et al · 2019
Earlier work this paper cites.
Scalable neural architecture search for 3d medical image segmentation
Sungwoong Kim, Ildoo Kim, Sungbin Lim, Woonhyuk Baek, Chiheon Kim, Hyungjoo Cho, Boogeon Yoon, and Taesup Kim · 2019
Earlier work this paper cites.
Partial order pruning: for best speed/accuracy trade-off in neural architecture search
Xin Li, Yiming Zhou, Zheng Pan, and Jiashi Feng · 2019
Earlier work this paper cites.
Multi-domain adaptation in brain mri through paired consistency and adversarial learning
Mauricio Orbes-Arteaga, Thomas Varsavsky, Carole H Sudre, Zach Eaton-Rosen, Lewis J Haddow, Lauge Sørensen, Mads Nielsen, Akshay Pai, Sébastien Ourselin, Marc Modat, et al · 2019
Earlier work this paper cites.
Mulan: multitask universal lesion analysis network for joint lesion detection, tagging, and segmentation
Ke Yan, Youbao Tang, Yifan Peng, Veit Sandfort, Mohammadhadi Bagheri, Zhiyong Lu, and Ronald M Summers · 2019
Earlier work this paper cites.
Prior-aware neural network for partially-supervised multi-organ segmentation
Yuyin Zhou, Zhe Li, Song Bai, Chong Wang, Xinlei Chen, Mei Han, Elliot Fishman, and Alan L Yuille · 2019
Earlier work this paper cites.
Unet++: Redesigning skip connections to exploit multiscale features in image segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang · 2019
Earlier work this paper cites.
Models genesis: Generic autodidactic models for 3d medical image analysis
Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B Gotway, and Jianming Liang · 2019
Earlier work this paper cites.
Universal lesion detector: Deep learning for analysing medical scans
Martin Zlocha, Ben Glocker, and Jonathan Passerat-Palmbach · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Multi-organ segmentation over partially labeled datasets with multi-scale feature abstraction
Xi Fang and Pingkun Yan · 2020
Earlier work this paper cites.
An international challenge to use artificial intelligence to define the state-of-the-art in kidney and kidney tumor segmentation in ct imaging., 2020
Nicholas Heller, Sean McSweeney, Matthew Thomas Peterson, Sarah Peterson, Jack Rickman, Bethany Stai, Resha Tejpaul, Makinna Oestreich, Paul Blake, Joel Rosenberg, et al · 2020
Earlier work this paper cites.
Multi-organ segmentation via co-training weight-averaged models from few-organ datasets
Rui Huang, Yuanjie Zheng, Zhiqiang Hu, Shaoting Zhang, and Hongsheng Li · 2020
Earlier work this paper cites.
Checklist for artificial intelligence in medical imaging (claim): A guide for authors and reviewers
John Mongan, Linda Moy, and Charles E. Kahn · 2020
Earlier work this paper cites.
Minimum information about clinical artificial intelligence modeling: the mi-claim checklist
Beau Norgeot, Giorgio Quer, Brett K Beaulieu-Jones, Ali Torkamani, Raquel Dias, Milena Gianfrancesco, Rima Arnaout, Isaac S Kohane, Suchi Saria, Eric Topol, et al · 2020
Earlier work this paper cites.
Ct-org, a new dataset for multiple organ segmentation in computed tomography
Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, and Daniel L Rubin · 2020
Earlier work this paper cites.
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation
Nima Tajbakhsh, Laura Jeyaseelan, Qian Li, Jeffrey N Chiang, Zhihao Wu, and Xiaowei Ding · 2020
Earlier work this paper cites.
Conditional convolutions for instance segmentation
Zhi Tian, Chunhua Shen, and Hao Chen · 2020
Earlier work this paper cites.
Universal lesion detection by learning from multiple heterogeneously labeled datasets
Ke Yan, Jinzheng Cai, Adam P Harrison, Dakai Jin, Jing Xiao, and Le Lu · 2020
Earlier work this paper cites.
Learning from multiple datasets with heterogeneous and partial labels for universal lesion detection in ct
Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P Harrison, Dakai Jin, You-bao Tang, Yu-Xing Tang, Lingyun Huang, Jing Xiao, and Le Lu · 2020
Cited alongside, same era.
Mri manufacturer shift and adaptation: increasing the generalizability of deep learning segmentation for mr images acquired with different scanners
Wenjun Yan, Lu Huang, Liming Xia, Shengjia Gu, Fuhua Yan, Yuanyuan Wang, and Qian Tao · 2020
Cited alongside, same era.
C2fnas: Coarse-to-fine neural architecture search for 3d medical image segmentation
Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan L Yuille, and Daguang Xu · 2020
Cited alongside, same era.
The medical segmentation decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Bennett A Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M Summers, Bram van Ginneken, et al · 2021
Cited alongside, same era.
Transunet: Transformers make strong encoders for medical image segmentation
Universal segmentation of 33 anatomies
Pengbo Liu, Yang Deng, Ce Wang, Yuan Hui, Qian Li, Jun Li, Shiwei Luo, Mengke Sun, Quan Quan, Shuxin Yang, et al · 2022
Later among the works it cites.
Improving ct-image universal lesion detection with comprehensive data and feature enhancements
Zhe Liu, Kai Han, Kaifeng Xue, Yuqing Song, Lu Liu, Yangyang Tang, and Yan Zhu · 2022
Later among the works it cites.
Image segmentation using text and image prompts
Timo Lüddecke and Alexander Ecker · 2022
Later among the works it cites.
Universal lesion detection in ct scans using neural network ensembles
Tarun Mattikalli, Tejas Sudharshan Mathai, and Ronald M Summers · 2022
Later among the works it cites.
Universal lesion detection and classification using limited data and weakly-supervised self-training
Varun Naga, Tejas Sudharshan Mathai, Angshuman Paul, and Ronald M Summers · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L Yuille, and Yuyin Zhou · 2021
Cited alongside, same era.
A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy
Xuming Chen, Shanlin Sun, Narisu Bai, Kun Han, Qianqian Liu, Shengyu Yao, Hao Tang, Chupeng Zhang, Zhipeng Lu, Qian Huang, et al · 2021
Cited alongside, same era.
Sedigheh Eslami, Gerard de Melo, and Christoph Meinel · 2021
Cited alongside, same era.
Deep learning-enabled medical computer vision
Andre Esteva, Katherine Chou, Serena Yeung, Nikhil Naik, Ali Madani, Ali Mottaghi, Yun Liu, Eric Topol, Jeff Dean, and Richard Socher · 2021
Cited alongside, same era.
Multi-institutional collaborations for improving deep learning-based magnetic resonance image reconstruction using federated learning
Pengfei Guo, Puyang Wang, Jinyuan Zhou, Shanshan Jiang, and Vishal M Patel · 2021
Cited alongside, same era.
Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B Gotway, and Jianming Liang · 2021
Cited alongside, same era.
Dints: Differentiable neural network topology search for 3d medical image segmentation
Yufan He, Dong Yang, Holger Roth, Can Zhao, and Daguang Xu · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Per-clip video object segmentation
Kwanyong Park, Sanghyun Woo, Seoung Wug Oh, In So Kweon, and Joon-Young Lee · 2022
Later among the works it cites.
Medical image understanding with pretrained vision language models: A comprehensive study
Ziyuan Qin, Huahui Yi, Qicheng Lao, and Kang Li · 2022
Later among the works it cites.
Denseclip: Language-guided dense prediction with context-aware prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen, Yansong Tang, Zheng Zhu, Guan Huang, Jie Zhou, and Jiwen Lu · 2022
Later among the works it cites.
Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al · 2022
Later among the works it cites.
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.
Cris: Clip-driven referring image segmentation
Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, and Tongliang Liu · 2022
Later among the works it cites.
Medclip: Contrastive learning from unpaired medical images and text
Zifeng Wang, Zhenbang Wu, Dinesh Agarwal, and Jimeng Sun · 2022
Later among the works it cites.
Totalsegmentator: robust segmentation of 104 anatomical structures in ct images
Jakob Wasserthal, Manfred Meyer, Hanns-Christian Breit, Joshy Cyriac, Shan Yang, and Martin Segeroth · 2022
Later among the works it cites.
Unimiss: Universal medical self-supervised learning via breaking dimensionality barrier
Yutong Xie, Jianpeng Zhang, Yong Xia, and Qi Wu · 2022
Later among the works it cites.
Linkbert: Pretraining language models with document links
Michihiro Yasunaga, Jure Leskovec, and Percy Liang · 2022
Later among the works it cites.
Xin Yu, Qi Yang, Yinchi Zhou, Leon Y Cai, Riqiang Gao, Ho Hin Lee, Thomas Li, Shunxing Bao, Zhoubing Xu, Thomas A Lasko, et al · 2022
Later among the works it cites.
Merging nucleus datasets by correlation-based cross-training
Wenhua Zhang, Jun Zhang, Xiyue Wang, Sen Yang, Junzhou Huang, Wei Yang, Wenping Wang, and Xiao Han · 2022
Later among the works it cites.
Learning to prompt for vision-language models
Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu · 2022
Later among the works it cites.
Interpreting medical images
Zongwei Zhou, Michael B Gotway, and Jianming Liang · 2022
Later among the works it cites.
Assembling and exploiting large-scale existing labels of common thorax diseases for improved covid-19 classification using chest radiographs
Zengle Zhu, Mintong Kang, Alan Yuille, and Zongwei Zhou · 2022
Later among the works it cites.
Universeg: Universal medical image segmentation
Victor Ion Butoi, Jose Javier Gonzalez Ortiz, Tianyu Ma, Mert R Sabuncu, John Guttag, and Adrian V Dalca · 2023
Closest in time.
Jieneng Chen, Yingda Xia, Jiawen Yao, Ke Yan, Jianpeng Zhang, Le Lu, Fakai Wang, Bo Zhou, Mingyan Qiu, Qihang Yu, et al · 2023
Closest in time.
Training like a medical resident: Universal medical image segmentation via context prior learning
Yunhe Gao, Zhuowei Li, Di Liu, Mu Zhou, Shaoting Zhang, and Dimitris N Meta · 2023
Closest in time.
Label-free liver tumor segmentation
Qixin Hu, Yixiong Chen, Junfei Xiao, Shuwen Sun, Jieneng Chen, Alan L Yuille, and Zongwei Zhou · 2023
Closest in time.
Ziyan Huang, Haoyu Wang, Zhongying Deng, Jin Ye, Yanzhou Su, Hui Sun, Junjun He, Yun Gu, Lixu Gu, Shaoting Zhang, et al · 2023
Closest in time.
Label-assemble: Leveraging multiple datasets with partial labels
Mintong Kang, Bowen Li, Zengle Zhu, Yongyi Lu, Elliot K Fishman, Alan L Yuille, and Zongwei Zhou · 2023
Closest in time.
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
Closest in time.
Foundation models for generalist medical artificial intelligence
Michael Moor, Oishi Banerjee, Zahra Shakeri Hossein Abad, Harlan M Krumholz, Jure Leskovec, Eric J Topol, and Pranav Rajpurkar · 2023
Closest in time.
Annotating 8,000 abdominal ct volumes for multi-organ segmentation in three weeks
Chongyu Qu, Tiezheng Zhang, Hualin Qiao, Jie Liu, Yucheng Tang, Alan Yuille, and Zongwei Zhou · 2023
Closest in time.
Multitalent: A multi-dataset approach to medical image segmentation
Constantin Ulrich, Fabian Isensee, Tassilo Wald, Maximilian Zenk, Michael Baumgartner, and Klaus H Maier-Hein · 2023
Closest in time.
Guotai Wang, Jianghao Wu, Xiangde Luo, Xinglong Liu, Kang Li, and Shaoting Zhang · 2023
Closest in time.
Uniseg: A prompt-driven universal segmentation model as well as a strong representation learner
Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, and Yong Xia · 2023
Closest in time.
Towards general purpose medical ai: Continual learning medical foundation model
Huahui Yi, Ziyuan Qin, Qicheng Lao, Wei Xu, Zekun Jiang, Dequan Wang, Shaoting Zhang, and Kang Li · 2023
Closest in time.
Continual learning for abdominal multi-organ and tumor segmentation
Yixiao Zhang, Xinyi Li, Huimiao Chen, Alan Yuille, Yaoyao Liu, and Zongwei Zhou · 2023
Closest in time.