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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:

A bird’s-eye view of deep learning in bioimage analysis
Erik Meijering
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 2312-2325
Open Access | Times Cited: 116

Showing 1-25 of 116 citing articles:

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
Bas H. M. van der Velden, Hugo J. Kuijf, Kenneth G. A. Gilhuijs, et al.
Medical Image Analysis (2022) Vol. 79, pp. 102470-102470
Open Access | Times Cited: 626
DeepImageJ: A user-friendly environment to run deep learning models in ImageJ
Estibaliz Gómez‐de‐Mariscal, Carlos García-López-de-Haro, Wei Ouyang, et al.
Nature Methods (2021) Vol. 18, Iss. 10, pp. 1192-1195
Open Access | Times Cited: 191
Medical image data augmentation: techniques, comparisons and interpretations
Evgin Göçeri
Artificial Intelligence Review (2023) Vol. 56, Iss. 11, pp. 12561-12605
Open Access | Times Cited: 164
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: 117
The Cell Tracking Challenge: 10 years of objective benchmarking
Martin Maška, Vladimír Ulman, Pablo Delgado-Rodriguez, et al.
Nature Methods (2023) Vol. 20, Iss. 7, pp. 1010-1020
Open Access | Times Cited: 87
AI‐organoid integrated systems for biomedical studies and applications
Sudhiksha Maramraju, Andrew Kowalczewski, Anirudh Kaza, et al.
Bioengineering & Translational Medicine (2024) Vol. 9, Iss. 2
Open Access | Times Cited: 15
Denoising diffusion probabilistic models for generation of realistic fully-annotated microscopy image datasets
Dennis Eschweiler, Rüveyda Yilmaz, Matisse Baumann, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 2, pp. e1011890-e1011890
Open Access | Times Cited: 15
Advanced imaging and labelling methods to decipher brain cell organization and function
Daniel Choquet, Matthieu Sainlos, Jean‐Baptiste Sibarita
Nature reviews. Neuroscience (2021) Vol. 22, Iss. 4, pp. 237-255
Closed Access | Times Cited: 91
VoxelEmbed: 3D Instance Segmentation and Tracking with Voxel Embedding based Deep Learning
Mengyang Zhao, Quan Liu, Aadarsh Jha, et al.
Lecture notes in computer science (2021), pp. 437-446
Open Access | Times Cited: 84
Open-source deep-learning software for bioimage segmentation
Alice Lucas, Pearl V. Ryder, Bin Li, et al.
Molecular Biology of the Cell (2021) Vol. 32, Iss. 9, pp. 823-829
Open Access | Times Cited: 62
Beauty Is in the AI of the Beholder: Are We Ready for the Clinical Integration of Artificial Intelligence in Radiography? An Exploratory Analysis of Perceived AI Knowledge, Skills, Confidence, and Education Perspectives of UK Radiographers
Clare Rainey, Tracy O’Regan, Jacqueline Matthew, et al.
Frontiers in Digital Health (2021) Vol. 3
Open Access | Times Cited: 55
Unravelling cell migration: defining movement from the cell surface
Francisco Merino-Casallo, María José Gómez‐Benito, Silvia Hervás-Raluy, et al.
Cell Adhesion & Migration (2022) Vol. 16, Iss. 1, pp. 25-64
Open Access | Times Cited: 49
The use of artificial intelligence for automating or semi-automating biomedical literature analyses: A scoping review
Álisson Oliveira dos Santos, Eduardo Sérgio da Silva, Letícia Machado Couto, et al.
Journal of Biomedical Informatics (2023) Vol. 142, pp. 104389-104389
Closed Access | Times Cited: 23
Harnessing artificial intelligence to reduce phototoxicity in live imaging
Estibaliz Gómez‐de‐Mariscal, Mario Del Rosario, Joanna W. Pylvänäinen, et al.
Journal of Cell Science (2024) Vol. 137, Iss. 3
Open Access | Times Cited: 7
Deep learning for bioimage analysis in developmental biology
Adrien Hallou, Hannah Yevick, Bianca Dumitrascu, et al.
Development (2021) Vol. 148, Iss. 18
Open Access | Times Cited: 51
Live cell microscopy: From image to insight
Andreas P. Cuny, Fabian P. Schlottmann, Jennifer C. Ewald, et al.
Biophysics Reviews (2022) Vol. 3, Iss. 2
Open Access | Times Cited: 32
Robust 3d Cell Segmentation: Extending The View Of Cellpose
Dennis Eschweiler, Richard S. Smith, Johannes Stegmaier
2022 IEEE International Conference on Image Processing (ICIP) (2022), pp. 191-195
Open Access | Times Cited: 27
Splinedist: Automated Cell Segmentation With Spline Curves
Soham Mandal, Virginie Uhlmann
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (2021), pp. 1082-1086
Open Access | Times Cited: 32
Deep Learning in Diverse Intelligent Sensor Based Systems
Yanming Zhu, Min Wang, Xuefei Yin, et al.
Sensors (2022) Vol. 23, Iss. 1, pp. 62-62
Open Access | Times Cited: 26
Deep learning-enabled segmentation of ambiguous bioimages with deepflash2
Matthias Griebel, Dennis Segebarth, Nikolai Stein, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 14
Made to measure: An introduction to quantifying microscopy data in the life sciences
S J Culley, Alicia Cuber Caballero, Jemima J. Burden, et al.
Journal of Microscopy (2023) Vol. 295, Iss. 1, pp. 61-82
Open Access | Times Cited: 13
From pixels to insights: Machine learning and deep learning for bioimage analysis
M Jan, Allie Spangaro, M. Lenartowicz, et al.
BioEssays (2023) Vol. 46, Iss. 2
Open Access | Times Cited: 12
Explainable prediction model for the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma using CNN on CT images
Annarita Fanizzi, Maria Colomba Comes, Samantha Bove, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Machine learning-enabled prediction of prolonged length of stay in hospital after surgery for tuberculosis spondylitis patients with unbalanced data: a novel approach using explainable artificial intelligence (XAI)
Parhat Yasin, Yasen Yimit, Xiaoyu Cai, et al.
European journal of medical research (2024) Vol. 29, Iss. 1
Open Access | Times Cited: 4
Fully Interpretable Deep Learning Model Using IR Thermal Images for Possible Breast Cancer Cases
Yerken Mirasbekov, Nurduman Aidossov, Aigerim Mashekova, et al.
Biomimetics (2024) Vol. 9, Iss. 10, pp. 609-609
Open Access | Times Cited: 4
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