Fetching the paper…
Reading the bibliography…
The semantic segmentation task in pathology plays an indispensable role in assisting physicians in determining the condition of tissue lesions.
“On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition,”
Andrei Nikolaevich Kolmogorov, · 1957
Earlier work this paper cites.
“Multilayer feedforward networks are universal approximators,”
Kurt Hornik, Maxwell Stinchcombe, and Halbert White, · 1989
Earlier work this paper cites.
“Deep architecture of kolmogorov-arnold representation,”
Guang-Bin Huang, Lei Zhao, and Yong Song, · 2014
Earlier work this paper cites.
“A survey on deep learning in medical image analysis,”
G. Litjens, T. Kooi, B.E. Bejnordi, A.A.A. Setio, F. Ciompi, M. Ghafoorian, J.A. Van Der Laak, B. Van Ginneken, and C.I. Sánchez, · 2017
Earlier work this paper cites.
“Gland segmentation in colon histology images: The glas challenge contest,”
Korsuk Sirinukunwattana, Josien PW Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J Matuszewski, Elia Bruni, Urko Sanchez, et al., · 2017
Earlier work this paper cites.
“Artificial intelligence and digital pathology: Challenges and opportunities,”
H.R. Tizhoosh and L. Pantanowitz, · 2018
Earlier work this paper cites.
“Machine learning methods for histopathological image analysis,”
D. Komura and S. Ishikawa, · 2018
Earlier work this paper cites.
“Decoupled weight decay regularization,”
Ilya Loshchilov and Frank Hutter, · 2018
Earlier work this paper cites.
“Digital pathology and artificial intelligence,”
M.K.K. Niazi, A.V. Parwani, and M.N. Gurcan, · 2019
Earlier work this paper cites.
“Mild-net: Minimal information loss dilated network for gland instance segmentation in colon histology images,”
S. Graham, H. Chen, J. Gamper, Q. Dou, P.A. Heng, D. Snead, Y.W. Tsang, and N. Rajpoot, · 2019
Earlier work this paper cites.
“Feature-driven local cell graph (flock): new computational pathology-based descriptors for prognosis of lung cancer and hpv status of oropharyngeal cancers,”
C. Lu, C. Koyuncu, G. Corredor, P. Prasanna, P. Leo, X. Wang, A. Janowczyk, K. Bera, J. Lewis Jr, V. Velcheti, et al., · 2021
Cited alongside, same era.
“Subtype-specific spatial descriptors of tumor-immune microenvironment are prognostic of survival in lung adenocarcinoma,”
S. Kapse, L. Torre-Healy, R.A. Moffitt, R. Gupta, and P. Prasanna, · 2022
Cited alongside, same era.
“Image analysis reveals molecularly distinct patterns of tils in nsclc associated with treatment outcome,”
R. Ding, P. Prasanna, G. Corredor, C. Barrera, P. Zens, C. Lu, P. Velu, P. Leo, N. Beig, H. Li, et al., · 2022
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
Cited alongside, same era.
“Sam-path: A segment anything model for semantic segmentation in digital pathology,”
Jingwei Zhang, Ke Ma, Saarthak Kapse, Joel Saltz, Maria Vakalopoulou, Prateek Prasanna, and Dimitris Samaras, · 2023
Later among the works it cites.
“Hiera: A hierarchical vision transformer without the bells-and-whistles,”
Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya, Chen Wei, Haoqi Fan, Po-Yao Huang, Vaibhav Aggarwal, Arkabandhu Chowdhury, Omid Poursaeed, Judy Hoffman, Jitendra Malik, Yanghao Li, and Christoph Feichtenhofer, · 2023
Later among the works it cites.
“Ebhi-seg: A novel enteroscope biopsy histopathological hematoxylin and eosin image dataset for image segmentation tasks,”
Liyu Shi, Xiaoyan Li, Weiming Hu, Haoyuan Chen, Jing Chen, Zizhen Fan, Minghe Gao, Yujie Jing, Guotao Lu, Deguo Ma, et al., · 2023
Later among the works it cites.
“Segment anything in medical images,”
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, and Bo Wang, · 2024
Closest in time.
“Sam 2: Segment anything in images and videos,”
Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu, Ronghang Hu, Chaitanya Ryali, Tengyu Ma, Haitham Khedr, Roman Rädle, Chloe Rolland, Laura Gustafson, Eric Mintun, Junting Pan, Kalyan Vasudev Alwala, Nicolas Carion, Chao-Yuan Wu, Ross Girshick, Piotr Dollár, and Christoph Feichtenhofer, · 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“Scaling vision transformers to gigapixel images via hierarchical self-supervised learning,”
R.J. Chen, C. Chen, Y. Li, T.Y. Chen, A.D. Trister, R.G. Krishnan, and F. Mahmood, · 2022
Cited alongside, same era.
“Precise location matching improves dense contrastive learning in digital pathology,”
J. Zhang, S. Kapse, K. Ma, P. Prasanna, M. Vakalopoulou, J. Saltz, and D. Samaras, · 2023
Cited alongside, same era.
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.
“Seggpt: Segmenting everything in context,”
Xinlong Wang, Xiaosong Zhang, Yue Cao, Wen Wang, Chunhua Shen, and Tiejun Huang, · 2023
Cited alongside, same era.
“Images speak in images: A generalist painter for in-context visual learning,”
Xinlong Wang, Wen Wang, Yue Cao, Chunhua Shen, and Tiejun Huang, · 2023
Cited alongside, same era.
Closest in time.
“Segment anything in medical images and videos: Benchmark and deployment,”
Jun Ma, Sumin Kim, Feifei Li, Mohammed Baharoon, Reza Asakereh, Hongwei Lyu, and Bo Wang, · 2024
Closest in time.
“Towards a general-purpose foundation model for computational pathology,”
Richard J Chen, Tong Ding, Ming Y Lu, Drew FK Williamson, Guillaume Jaume, Bowen Chen, Andrew Zhang, Daniel Shao, Andrew H Song, Muhammad Shaban, et al., · 2024
Closest in time.
“White-box transformers via sparse rate reduction,”
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin Haeffele, and Yi Ma, · 2024
Closest in time.
“Masked completion via structured diffusion with white-box transformers,”
Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, and Yi Ma, · 2024
Closest in time.