Fetching the paper…
Reading the bibliography…
Segmentation in medical imaging is a critical component for the diagnosis, monitoring, and treatment of various diseases and medical conditions.
Noel C. F. Codella, Veronica Rotemberg, Philipp Tschandl, M. Emre Celebi, Stephen W. Dusza, David A. Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael A. Marchetti, Harald Kittler, and Allan Halpern · 1902
Earlier work this paper cites.
Current methods in medical image segmentation
Dzung L Pham, Chenyang Xu, and Jerry L Prince · 2000
Earlier work this paper cites.
Automated medical image segmentation techniques
Neeraj Sharma and Lalit M Aggarwal · 2010
Earlier work this paper cites.
Automatic tuberculosis screening using chest radiographs
Stefan Jaeger, Alexandros Karargyris, Sema Candemir, Les R. Folio, Jenifer Siegelman, Fiona M. Callaghan, Zhiyun Xue, Kannappan Palaniappan, Rahul K. Singh, Sameer K. Antani, George R. Thoma, Yi-Xiang J. Wang, Pu-Xuan Lu, and Clement J. McDonald · 2013
Earlier work this paper cites.
Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration
Sema Candemir, Stefan Jaeger, Kannappan Palaniappan, Jonathan P. Musco, Rahul K. Singh, Zhiyun Xue, Alexandros Karargyris, Sameer K. Antani, George R. Thoma, and Clement J. McDonald · 2013
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.
WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians
Jorge Bernal, Francisco Javier Sánchez, Gloria Fernández-Esparrach, Debora Gil, Cristina Rodríguez de Miguel, and Fernando Vilariño · 2015
Earlier work this paper cites.
Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation
Shuo Wang, Mu Zhou, Zaiyi Liu, Zhenyu Liu, Dongsheng Gu, Yali Zang, Di Dong, Olivier Gevaert, and Jie Tian · 2017
Earlier work this paper cites.
A survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen Awm Van Der Laak, Bram Van Ginneken, and Clara I Sánchez · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
Earlier work this paper cites.
Review on 2d and 3d mri image segmentation techniques
S Shirly and K Ramesh · 2019
Cited alongside, same era.
Dataset of breast ultrasound images
Walid Al-Dhabyani, Mohammed Gomaa, Hussien Khaled, and Aly Fahmy · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Segmentation and feature extraction in medical imaging: a systematic review
Chiranji Lal Chowdhary and D Prasanna Acharjya · 2020
Cited alongside, same era.
Human–computer collaboration for skin cancer recognition
Philipp Tschandl, Christoph Rinner, Zoe Apalla, Giuseppe Argenziano, Noel Codella, Allan Halpern, Monika Janda, Aimilios Lallas, Caterina Longo, Josep Malvehy, John Paoli, Susana Puig, Cliff Rosendahl, H. Peter Soyer, Iris Zalaudek, and Harald Kittler · 2020
Cited alongside, same era.
Automatic lung segmentation on chest x-rays using self-attention deep neural network
Minki Kim and Byoung-Dai Lee · 2021
Later among the works it cites.
Vision transformers in medical imaging: A review
Emerald U. Henry, Onyeka Emebob, and Conrad Asotie Omonhinmin · 2022
Later among the works it cites.
Calip: Zero-shot enhancement of clip with parameter-free attention
Ziyu Guo, Renrui Zhang, Longtian Qiu, Xianzheng Ma, Xupeng Miao, Xuming He, and Bin Cui · 2022
Later among the works it cites.
Jongseong Jang, Daeun Kyung, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae, and Edward Choi · 2022
Later among the works it cites.
Medclip: Contrastive learning from unpaired medical images and text
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Training on polar image transformations improves biomedical image segmentation
Marin Bencevic, Irena Galic, Marija Habijan, and Danilo Babin · 2021
Cited alongside, same era.
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
Cited alongside, same era.
Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
Cited alongside, same era.
Combined scaling for zero-shot transfer learning
Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu, Minh-Thang Luong, Mingxing Tan, and Quoc V Le · 2021
Cited alongside, same era.
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
Cited alongside, same era.
X-ray images of the hip joints, 2021
Daniel Gut · 2021
Cited alongside, same era.
Rese-net: Enhanced unet architecture for lung segmentation in chest radiography images
Tarun Agrawal and Prakash Choudhary
Cited in the paper.
Zifeng Wang, Zhenbang Wu, Dinesh Agarwal, and Jimeng Sun · 2022
Later among the works it cites.
Zero-shot and few-shot learning for lung cancer multi-label classification using vision transformer
Fu-Ming Guo and Yingfang Fan · 2022
Later among the works it cites.
Alessandro Sebastian Podda, Riccardo Balia, Silvio Barra, Salvatore Carta, Gianni Fenu, and Leonardo Piano · 2022
Later among the works it cites.
Clip-driven universal model for organ segmentation and tumor detection
Jie Liu, Yixiao Zhang, Jieneng Chen, Junfei Xiao, Yongyi Lu, Bennett A. Landman, Yixuan Yuan, Alan L. Yuille, Yucheng Tang, and Zongwei Zhou · 2023
Closest in time.
Rema-net: An efficient multi-attention convolutional neural network for rapid skin lesion segmentation
Litao Yang, Chao Fan, Hao Lin, and Yingying Qiu · 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.
Fsa-net: Rethinking the attention mechanisms in medical image segmentation from releasing global suppressed information
Bangcheng Zhan, Enmin Song, and Hong Liu · 2023
Closest in time.