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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map
Peter Naylor, Marick Laé, Fabien Reyal, et al.
IEEE Transactions on Medical Imaging (2018) Vol. 38, Iss. 2, pp. 448-459
Closed Access | Times Cited: 533

Showing 1-25 of 533 citing articles:

Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
Simon Graham, Quoc Dang Vu, Shan E Ahmed Raza, et al.
Medical Image Analysis (2019) Vol. 58, pp. 101563-101563
Open Access | Times Cited: 937
Deep learning in histopathology: the path to the clinic
Jeroen van der Laak, Geert Litjens, Francesco Ciompi
Nature Medicine (2021) Vol. 27, Iss. 5, pp. 775-784
Open Access | Times Cited: 615
Deep neural network models for computational histopathology: A survey
Chetan L. Srinidhi, Ozan Ciga, Anne L. Martel
Medical Image Analysis (2020) Vol. 67, pp. 101813-101813
Open Access | Times Cited: 564
A Multi-Organ Nucleus Segmentation Challenge
Neeraj Kumar, Ruchika Verma, Deepak Anand, et al.
IEEE Transactions on Medical Imaging (2019) Vol. 39, Iss. 5, pp. 1380-1391
Open Access | Times Cited: 396
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis
Richard J. Chen, Ming Y. Lu, Jingwen Wang, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 41, Iss. 4, pp. 757-770
Open Access | Times Cited: 388
Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images
Faisal Mahmood, Daniel Borders, Richard J. Chen, et al.
IEEE Transactions on Medical Imaging (2019) Vol. 39, Iss. 11, pp. 3257-3267
Open Access | Times Cited: 298
The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Massimo Salvi, U. Rajendra Acharya, Filippo Molinari, et al.
Computers in Biology and Medicine (2020) Vol. 128, pp. 104129-104129
Open Access | Times Cited: 256
Self supervised contrastive learning for digital histopathology
Ozan Ciga, Tony Xu, Anne L. Martel
Machine Learning with Applications (2021) Vol. 7, pp. 100198-100198
Open Access | Times Cited: 198
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Jun Li, Junyu Chen, Yucheng Tang, et al.
Medical Image Analysis (2023) Vol. 85, pp. 102762-102762
Open Access | Times Cited: 191
Test-time augmentation for deep learning-based cell segmentation on microscopy images
Nikita Moshkov, Botond Mathe, Attila Kertész‐Farkas, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 169
Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
Aleksandar Vakanski, Min Xian, Phoebe E. Freer
Ultrasound in Medicine & Biology (2020) Vol. 46, Iss. 10, pp. 2819-2833
Open Access | Times Cited: 159
Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images
Hui Qu, Pengxiang Wu, Qiaoying Huang, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 39, Iss. 11, pp. 3655-3666
Open Access | Times Cited: 155
X-Net: a dual encoding–decoding method in medical image segmentation
Yuanyuan Li, Ziyu Wang, Li Yin, et al.
The Visual Computer (2021) Vol. 39, Iss. 6, pp. 2223-2233
Closed Access | Times Cited: 129
A survey on applications of deep learning in microscopy image analysis
Zhichao Liu, Luhong Jin, Jincheng Chen, et al.
Computers in Biology and Medicine (2021) Vol. 134, pp. 104523-104523
Closed Access | Times Cited: 124
Artificial intelligence for digital and computational pathology
Andrew H. Song, Guillaume Jaume, Drew F. K. Williamson, et al.
Nature Reviews Bioengineering (2023) Vol. 1, Iss. 12, pp. 930-949
Closed Access | Times Cited: 89
CellViT: Vision Transformers for precise cell segmentation and classification
Fabian Hörst, Moritz Rempe, Lukas Heine, et al.
Medical Image Analysis (2024) Vol. 94, pp. 103143-103143
Open Access | Times Cited: 61
Recent progress in transformer-based medical image analysis
Zhaoshan Liu, Qiujie Lv, Ziduo Yang, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 107268-107268
Open Access | Times Cited: 59
A review of uncertainty estimation and its application in medical imaging
Ke Zou, Zhihao Chen, Xuedong Yuan, et al.
Meta-Radiology (2023) Vol. 1, Iss. 1, pp. 100003-100003
Open Access | Times Cited: 58
Computational Pathology: A Survey Review and The Way Forward
Mahdi S. Hosseini, Babak Ehteshami Bejnordi, Vincent Quoc‐Huy Trinh, et al.
Journal of Pathology Informatics (2024), pp. 100357-100357
Open Access | Times Cited: 34
TSCA-Net: Transformer based spatial-channel attention segmentation network for medical images
Yinghua Fu, Junfeng Liu, Jun Shi
Computers in Biology and Medicine (2024) Vol. 170, pp. 107938-107938
Closed Access | Times Cited: 30
Nuclei segmentation using attention aware and adversarial networks
Evgin Göçeri
Neurocomputing (2024) Vol. 579, pp. 127445-127445
Closed Access | Times Cited: 27
Advantages of transformer and its application for medical image segmentation: a survey
Qiumei Pu, Zuoxin Xi, Shuai Yin, et al.
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 24
NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images
Shyam Lal, Devikalyan Das, Kumar Alabhya, et al.
Computers in Biology and Medicine (2020) Vol. 128, pp. 104075-104075
Closed Access | Times Cited: 130
PanNuke Dataset Extension, Insights and Baselines
Jevgenij Gamper, Navid Alemi Koohbanani, Simon Graham, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 121
Deep learning in digital pathology image analysis: a survey
Shujian Deng, Xin Zhang, Yan Wen, et al.
Frontiers of Medicine (2020) Vol. 14, Iss. 4, pp. 470-487
Closed Access | Times Cited: 120
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