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The Segment Anything Model (SAM) and CLIP are remarkable vision foundation models (VFMs).
U-Net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
An open, multi-vendor, multi-field-strength brain mr dataset and analysis of publicly available skull stripping methods agreement
Roberto Souza, Oeslle Lucena, Julia Garrafa, David Gobbi, Marina Saluzzi, Simone Appenzeller, Letícia Rittner, Richard Frayne, and Roberto Lotufo · 2018
Earlier work this paper cites.
Automated measurement of fetal head circumference using 2D ultrasound images
Thomas L A van den Heuvel, Dagmar de Bruijn, Chris L de Korte, and Bram van Ginneken · 2018
Earlier work this paper cites.
Chest x-ray masks and labels
Nikhil Pandey · 2019
Earlier work this paper cites.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Earlier work this paper cites.
Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Image segmentation using text and image prompts
Timo Lüddecke and Alexander Ecker · 2022
Earlier work this paper cites.
Reclip: A strong zero-shot baseline for referring expression comprehension
Sanjay Subramanian, William Merrill, Trevor Darrell, Matt Gardner, Sameer Singh, and Anna Rohrbach · 2022
Earlier work this paper cites.
Medclip: Contrastive learning from unpaired medical images and text
Zifeng Wang, Zhenbang Wu, Dinesh Agarwal, and Jimeng Sun · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Polyp-sam++: Can a text guided sam perform better for polyp segmentation?
Risab Biswas · 2023
Cited alongside, same era.
Ruining Deng, Can Cui, Quan Liu, Tianyuan Yao, Lucas W Remedios, Shunxing Bao, Bennett A Landman, Lee E Wheless, Lori A Coburn, Keith T Wilson, et al · 2023
Cited alongside, same era.
What does clip know about a red circle? visual prompt engineering for vlms
Aleksandar Shtedritski, Christian Rupprecht, and Andrea Vedaldi · 2023
Later among the works it cites.
Medical sam adapter: Adapting segment anything model for medical image segmentation
Junde Wu, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel · 2023
Later among the works it cites.
CXR-CLIP: Toward large scale chest x-ray Language-Image pre-training
Kihyun You, Jawook Gu, Jiyeon Ham, Beomhee Park, Jiho Kim, Eun K Hong, Woonhyuk Baek, and Byungseok Roh · 2023
Later among the works it cites.
Customized segment anything model for medical image segmentation
Kaidong Zhang and Dong Liu · 2023
Later among the works it cites.
TPRO: Text-Prompting-Based weakly supervised histopathology tissue segmentation
Shaoteng Zhang, Jianpeng Zhang, Yutong Xie, and Yong Xia · 2023
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Chuanfei Hu and Xinde Li · 2023
Cited alongside, same era.
Ultralytics yolo, 2023
Glenn Jocher, Ayush Chaurasia, and Jing Qiu · 2023
Cited alongside, same era.
Segment anything
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
Cited alongside, same era.
Enhancing clip with gpt-4: Harnessing visual descriptions as prompts
Mayug Maniparambil, Chris Vorster, Derek Molloy, Noel Murphy, Kevin McGuinness, and Noel E O’Connor · 2023
Cited alongside, same era.
Exploring the zero-shot capabilities of the segment anything model (sam) in 2d medical imaging: A comprehensive evaluation and practical guideline
Christian Mattjie, Luis Vinicius de Moura, Rafaela Cappelari Ravazio, Lucas Silveira Kupssinskü, Otávio Parraga, Marcelo Mussi Delucis, and Rodrigo Coelho Barros · 2023
Cited alongside, same era.
Segment anything model for medical image analysis: an experimental study
Maciej A Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, and Yixin Zhang · 2023
Cited alongside, same era.
Brain extraction comparing segment anything model (sam) and fsl brain extraction tool
Sovesh Mohapatra, Advait Gosai, and Gottfried Schlaug · 2023
Cited alongside, same era.
Comprehensive multimodal segmentation in medical imaging: Combining yolov8 with sam and hq-sam models
Sumit Pandey, Kuan-Fu Chen, and Erik B Dam · 2023
Cited alongside, same era.
Later among the works it cites.
Continual learning for abdominal multi-organ and tumor segmentation
Yixiao Zhang, Xinyi Li, Huimiao Chen, Yaoyao Yuille, Alan Land Liu, and Zongwei Zhou · 2023
Later among the works it cites.
Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu, and Chen Gong · 2023
Later among the works it cites.
Segment anything model for medical images?
Yuhao Huang, Xin Yang, Lian Liu, Han Zhou, Ao Chang, Xinrui Zhou, Rusi Chen, Junxuan Yu, Jiongquan Chen, Chaoyu Chen, et al · 2024
Closest in time.
Segment anything in medical images
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, and Bo Wang · 2024
Closest in time.
Fine-grained visual prompting
Lingfeng Yang, Yueze Wang, Xiang Li, Xinlong Wang, and Jian Yang · 2024
Closest in time.
Cpt: Colorful prompt tuning for pre-trained vision-language models
Yuan Yao, Ao Zhang, Zhengyan Zhang, Zhiyuan Liu, Tat-Seng Chua, and Maosong Sun · 2024
Closest in time.