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:

A survey on recent trends in deep learning for nucleus segmentation from histopathology images
Anusua Basu, Pradip Senapati, Mainak Deb, et al.
Evolving Systems (2023) Vol. 15, Iss. 1, pp. 203-248
Open Access | Times Cited: 38

Showing 26-50 of 38 citing articles:

Review of cervical cell segmentation
Qian Huang, Wei Zhang, Yulin Chen, et al.
Multimedia Tools and Applications (2024)
Closed Access

A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
Chai Ling Teoh, Xiao Jian Tan, Khairul Shakir Ab Rahman, et al.
Diagnostics (2024) Vol. 14, Iss. 18, pp. 2045-2045
Open Access

White blood cell segmentation using U-Net and its variants to improve leukemia diagnosis
Vivek C. Joshi, Mayuri A. Mehta, Ketan Kotecha
Neural Computing and Applications (2024) Vol. 37, Iss. 5, pp. 3265-3286
Closed Access

Bionic model of blood cell segmentation based on impulse image transformation
Roman Yu. Bukhtiiarov, Anatoliy V. Tarasov, Andriy V. Rabotiahov, et al.
Polish Journal of Medical Physics And Engineering (2024) Vol. 30, Iss. 4
Open Access

Bladder Segmentation in MRI for High Dose Rate Brachytherapy Using Deep Network
Suresh Chandra Das, Prakash Sanki, Subhayan Mondal, et al.
Lecture notes in networks and systems (2024), pp. 55-67
Closed Access

Federated Learning for Enhanced Cell Nuclei Segmentation in Histopathological Images
Marco Virgilio Usai, Andrea Loddo, Lorenzo Putzu, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 4507-4516
Closed Access

For the Nuclei Segmentation of Liver Cancer Histopathology Images, A Deep Learning Detection Approach is Used
Arifullah, Aziza Chakir, Dorsaf Sebai, et al.
Synthesis lectures on engineering, science, and technology (2024), pp. 263-274
Closed Access

Advancing lung cancer diagnosis with bio-inspired algorithms: a comprehensive assessment
Jyoti Kumari, Sapna Sinha, Laxman Singh
Multimedia Tools and Applications (2024)
Closed Access

Advancing histopathology in Health 4.0: Enhanced cell nuclei detection using deep learning and analytic classifiers
Sergi Pons, Esther Dura, Juan Domingo, et al.
Computer Standards & Interfaces (2024) Vol. 91, pp. 103889-103889
Open Access

Revolutionizing Cancer Diagnosis Through Hybrid Self-supervised Deep Learning: EfficientNet with Denoising Autoencoder for Semantic Segmentation of Histopathological Images
Mostafa A. Hammouda, Marwan Khaled, Hesham Ali, et al.
Lecture notes in computer science (2023), pp. 197-214
Closed Access

Self-Supervised Scribble-based Segmentation of Single Cells in Biofilms
Vidya Bommanapally, Mahadevan Subramaniam, Suvarna Talluri, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023) Vol. 1, pp. 4488-4493
Closed Access

Segmentation of Nuclei in H&E-Stained Histological Images using Deep Learning Framework: A Perspective on Ensemble Approach and Nuclei Count
Madhavi Aghera, Krishna V. Singh, Kishankumar Vaishnani, et al.
(2023), pp. 462-467
Closed Access

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