M. Emre Celebi's Academic Web Page

M. Emre Celebi's Fall 2016 Photo

M. Emre Celebi

Professor and Chair
Department of Computer Science and Engineering
University of Central Arkansas

Email: ecelebi@uca.edu
Phone: 501-852-0931
Office: MCS 303
Address: 201 Donaghey Ave., Conway, AR 72035

Brief Biography

M. Emre Celebi received his B.Sc. degree in Computer Engineering from the Middle East Technical University (Ankara, Turkey) in 2002. He received his M.Sc. and Ph.D. degrees in Computer Science and Engineering from the University of Texas at Arlington (Arlington, TX, USA) in 2003 and 2006, respectively. He is currently a Professor and the Chair of the Department of Computer Science and Engineering at the University of Central Arkansas.

Dr. Celebi has actively pursued research in image processing/analysis and data mining with an emphasis on medical image analysis, color image processing, and partitional clustering. He has worked on several projects funded by the US National Science Foundation and the US National Institutes of Health and published over 160 articles in reputable journals and conference proceedings. As of March 2023, his work has received nearly 14,000 citations with an h-index of 56 (Google Scholar). According to a recent study from the Stanford University, based on the composite citation index (an indicator of career-long citation impact), Dr. Celebi ranked 1,191 out of 215,114 researchers in the field of Artificial Intelligence and Image Processing, placing him in the top 0.55% of his field.

Dr. Celebi is an editorial board member of eight international peer-reviewed journals (including the Expert Systems with Applications, Computers in Biology and Medicine, Journal of Electronic Imaging), reviews for over 120 international journals, and served on the program committee of more than 130 international conferences. He has been invited as a speaker to several colloquia, workshops, and conferences, is the organizer of several workshops, and the editor of several journal special issues, books, and book series. He is a senior member of the IEEE (since 2011) and a fellow of the SPIE (since 2021).

Teaching

CSCI 4372/5372/6397 Data Clustering

Representative Publications (Curriculum Vitae)

CSAuthors
DBLP
Google Scholar
ORCID
Publons
Research
Research Gate
Semantic Scholar

M. E. Celebi, “Forty Years of Color Quantization: A Modern, Algorithmic Survey,” Artificial Intelligence Review, to appear, 2023 [Publisher]
M. E. Celebi, C. Barata, A. Halpern, P. Tschandl, M. Combalia, and Y. Liu, “Guest Editorial: Skin Image Analysis in the Age of Deep Learning,” IEEE Journal of Biomedical and Health Informatics, vol. 27, no. 1, pp. 143–144, 2023 [Publisher]
S. Wang, Z. Dong, Z. Zhang, Y. Huo, M. E. Celebi, and C. Shan, “Guest Editorial: Emerging Challenges for Deep Learning,” IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 11, pp. 5287–5288, 2022 [Publisher]
A. D. Abernathy and M. E. Celebi, “The Incremental Online K-Means Clustering Algorithm and Its Application to Color Quantization,” Expert Systems with Applications, vol. 207, 117927, 2022. [Publisher][Source Code]
M. E. Celebi, C. Barata, A. Halpern, P. Tschandl, M. Combalia, and Y. Liu, “Guest Editorial: Image Analysis in Dermatology,” Medical Image Analysis, vol. 79, 102468, 2022. [Publisher]
R. Daneshjou, C. Barata, B. Betz-Stablein, M. E. Celebi, N. Codella, M. Combalia, P. Guitera, D. Gutman, A. Halpern, B. Helba, H. Kittler, K. Kose, K. Liopyris, J. Malvehy, H. S. Seog, H. P. Soyer, E. R. Tkaczyk, P. Tschandl, and V. Rotemberg, “Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines from the International Skin Imaging Collaboration Artificial Intelligence Working Group,” JAMA Dermatology, vol. 158, no. 1, pp. 90–96, 2022. [Publisher]
R. Jiang, P. Chazot, N. Pavese, D. Crookes, A. Bouridane, and M. E. Celebi, “Private Facial Prediagnosis as an Edge Service for Parkinson’s DBS Treatment Valuation,” IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 6, pp. 2703–2713, 2022 [Publisher]
P. Shamsolmoali, S. Garcia, H. Zhou, and M. E. Celebi, “Advances in Domain Adaptation for Computer Vision,” Image and Vision Computing, vol. 114, 104268, 2021. [Publisher]
S. Wang, M. E. Celebi, Y. D. Zhang, X. Yu, S. Lu, X. Yao, Q. Zhou, M. Martinez-Garcia, Y. Tian, J. M. Gorriz, and I. Tyukin, “Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects,” Information Fusion, vol. 76, pp. 376–421, 2021. [Publisher]
R. Rastghalam, H. Danyali, M. S. Helfroush, M. E. Celebi, and M. Mokhtari, “Skin Melanoma Detection in Microscopic Images Using HMM-Based Asymmetric Analysis and Expectation Maximization,” IEEE Journal of Biomedical and Health Informatics, vol. 25, no. 9, pp. 3486–3497, 2021. [Publisher]
P. Shamsolmoali, M. Zareapoor, E. Granger, H. Zhou, R.Wang, M. E. Celebi, and J. Yang, “Image Synthesis with Adversarial Networks: A Comprehensive Survey and Case Studies,” Information Fusion, vol. 72, pp. 126–146, 2021. [Publisher]
C. Barata, M. E. Celebi, and J. S. Marques, “Explainable Skin Lesion Diagnosis Using Taxonomies,” Pattern Recognition, vol. 110, 107413, 2021. [Publisher]
P. Shamsolmoali, M. E. Celebi, and R. Wang, “Advances in Deep Learning for Real-Time Image and Video Reconstruction and Processing,” Journal of Real-Time Image Processing, vol. 17, no. 6, pp. 1883–1884, 2020. [Publisher]
P. Shamsolmoali, M. E. Celebi, and R. Wang, “Deep Learning Approaches for Real-Time Image Super-Resolution,” Neural Computing and Applications, vol. 32, pp. 14519–14520, 2020. [Publisher]
S. Zhang, H. Zhou, D. Xu, M. E. Celebi, and T. Bouwmans, “Introduction to the Special Issue on Multimodal Machine Learning for Human Behavior Analysis,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 16, no. 1s, Article 19, 2020. [Publisher]
A. R. Sadri, M. E. Celebi, N. Rahnavard, and S. E. Viswanath, “Sparse Wavelet Networks,” IEEE Signal Processing Letters, vol. 27, pp. 111–115, 2020. [Publisher]
S. Thompson, M. E. Celebi, K. H. Buck, “Fast Color Quantization Using MacQueen’s K-Means Algorithm,” Journal of Real-Time Image Processing, vol. 17, no. 5, pp. 1609–1624, 2020. [Publisher][Source Code]
C. Barata, J. S. Marques, and M. E. Celebi, “Deep Attention Model for the Hierarchical Diagnosis of Skin Lesions,” in Proceedings of the 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019) Workshops, pp. 2757–2765, 2019. [Publisher]
C. Curiel-Lewandrowski, R. A. Novoa, E. Berry, M. E. Celebi, N. Codella, F. Giuste, D. Gutman, A. Halpern, S. Leachman, Y. Liu, Y. Liu, O. Reiter, and P. Tschandl, “Artificial Intelligence Approach in Melanoma,” in Melanoma (D. E. Fisher and B. C. Bastian, eds.), pp. 599–628, Springer, 2019. [Publisher]
Z. Jiang, P. Chazot, M. E. Celebi, D. Crookes, and R. Jiang, “Social Behavioral Phenotyping of Drosophila with a 2D-3D Hybrid CNN Framework,” IEEE Access, vol. 7, pp. 67972–67982, 2019. [Publisher]
Q. Abbas and M. E. Celebi, “Dermodeep - A Classification of Melanoma-Nevus Skin Lesions Using Multi-Feature Fusion of Visual Features and Deep Neural Network,” Multimedia Tools and Applications, vol. 78, no. 16, pp. 23559–23580, 2019. [Publisher]
M. E. Celebi, N. Codella, and A. Halpern, “Dermoscopy Image Analysis: Overview and Future Directions,” IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 2, pp. 474–478, 2019. [Publisher] (100+ citations as of June 2022)
M. E. Celebi, N. Codella, A. Halpern, and D. Shen, “Guest Editorial: Skin Lesion Image Analysis for Melanoma Detection,” IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 2, pp. 479–480, 2019. [Publisher]
C. Barata, M. E. Celebi, and J. S. Marques, “A Survey of Feature Extraction in Dermoscopy Image Analysis of Skin Cancer,” IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 3, pp. 1096–1109, 2019. [Publisher] (100+ citations as of June 2022)
M. Zareapoor, M. E. Celebi, and J. Yang, “Diverse Adversarial Network for Image Super-Resolution,” Signal Processing: Image Communication, vol. 74, pp. 191–200, 2019. [Publisher]
E. Ardizzone and M. E. Celebi, “Image and Video Analysis, Detection and Recognition,” Journal of Electronic Imaging, vol. 27, no. 5, p. 051201, 2018. [Publisher]
A. Katapadi, M. E. Celebi, S. Trotter, and M. Gurcan, “Evolving Strategies for the Development and Evaluation of a Computerized Melanoma Image Analysis System,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 6, no. 4, pp. 465–472, 2018. [Publisher]
N. C. F. Codella, D. Gutman, M. E. Celebi, B. Helba, M. A. Marchetti, S. W. Dusza, A. Kalloo, K. Liopyris, N. Mishra, H. Kittler, and A. Halpern, “Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC),” in Proceedings of the 2018 IEEE International Symposium on Biomedical Imaging (ISBI 2018), pp. 168–172, 2018. [Publisher] (1,000+ citations as of June 2022)
M. A. Marchetti, N. C. F. Codella, S. W. Dusza, D. A. Gutman, B. Helba, A. Kalloo, N. Mishra,C. Carrera, M. E. Celebi, J. L. DeFazio, N. Jaimes, A. A. Marghoob, E. Quigley, A. Scope,O. Yelamos, and A. C. Halpern, “Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging Challenge: Comparison of the Accuracy of Computer Algorithms to Dermatologists for the Diagnosis of Melanoma from Dermoscopic Images,” Journal of the American Academy of Dermatology, vol. 78, no. 2, pp. 270–277, 2018. [Publisher] (nearly 200 citations as of April 2022)
C. Barata, M. E. Celebi, and J. S. Marques, “Development of a Clinically Oriented System for Melanoma Diagnosis,” Pattern Recognition, vol. 69, pp. 270–285, 2017. [Publisher]
A. R. Sadri, S. Azarianpour, M. Zekri, M. E. Celebi, and S. Sadri, “WN Based Approach to Melanoma Diagnosis from Dermoscopy Images,” IET Image Processing, vol. 11, no. 7, pp. 475–482, 2017. [Publisher]
O. Lezoray, C. Meurie, and M. E. Celebi, “Superpixels for Image Processing and Computer Vision,” Journal of Electronic Imaging, vol. 26, no. 6, 2017. [Publisher]
C. Barata, M. E. Celebi, J. S. Marques, and J. Rozeira, “Clinically Inspired Analysis of Dermoscopy Images Using a Generative Model,” Computer Vision and Image Understanding, vol. 151, pp. 124–137, 2016. [Publisher]
N. K. Mishra and M. E. Celebi, “An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning” arXiv:1601.07843v1 [cs.CV], 2016. (100+ citations as of January 2021)
M. E. Celebi, Q. Wen, and S. Hwang, “An Effective Real-Time Color Quantization Method Based on Divisive Hierarchical Clustering,” Journal of Real-Time Image Processing, vol. 10, no. 2, pp. 329–344, 2015. [Publisher][Source Code]
C. Barata, M. E. Celebi, and J. S. Marques, “Improving Dermoscopy Image Classification Using Color Constancy,” IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 3, pp. 1146–1152, 2015. [Publisher] (nearly 200 citations as of April 2022)
K. Shimizu, H. Iyatomi, M. E. Celebi, K. A. Norton, and M. Tanaka, “Four-Class Classification of Skin Lesions with Task Decomposition Strategy,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 1, pp. 274–283, 2015. [Publisher]
M. E. Celebi, Q. Wen, H. Iyatomi, K. Shimizu, H. Zhou, and G. Schaefer, “A State-of-the-Art Survey on Lesion Border Detection in Dermoscopy Images,” in Dermoscopy Image Analysis (M. E. Celebi, T. Mendonca, and J. S. Marques, eds.), pp. 97–129, CRC Press, 2015. (100+ citations as of January 2021)
M. E. Celebi and H. A. Kingravi, “Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm,” in Partitional Clustering Algorithms (M. E. Celebi, ed.), pp. 79–98, Springer, 2015.
M. E. Celebi, S. Hwang, and Q. Wen, “Color Quantization Using the Adaptive Distributing Units Algorithm,” Imaging Science Journal, vol. 62, no. 2, pp. 80–91, 2014. [Publisher]
M. E. Celebi and A. Zornberg, “Automated Quantification of Clinically Significant Colors in Dermoscopy Images and Its Application to Skin Lesion Classification,” IEEE Systems Journal, vol. 8, no. 3, pp. 980–984, 2014. [Publisher]
G. Schaefer, B. Krawczyk, M. E. Celebi, and H. Iyatomi, “An Ensemble Classification Approach for Melanoma Diagnosis,” Memetic Computing, vol. 6, no. 4, pp. 233–240, 2014. [Publisher] (100+ citations as of June 2022)
M. E. Celebi, Q. Wen, S. Hwang, H. Iyatomi, and G. Schaefer, “Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods,” Skin Research and Technology, vol. 19, no. 1, pp. e252–e258, 2013. [arXiv][Publisher] (nearly 200 citations as of April 2022)
M. E. Celebi, H. Kingravi, and P. A. Vela, “A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm,” Expert Systems with Applications, vol. 40, no. 1, pp. 200–210, 2013. [arXiv][Publisher] (1,100+ citations and 18th all-time most-cited ESWA article as of June 2022)
Q. Abbas, M. E. Celebi, C. Serrano, I. F. Garcia, and G. Ma, “Pattern Classification of Dermoscopy Images: A Perceptually Uniform Model,” Pattern Recognition, vol. 46, no. 1, pp. 86–97, 2013. [Publisher] (100+ citations as of January 2021)
H. Zhou, X. Li, G. Schaefer, M. E. Celebi, and P. Miller, “Mean Shift Based Gradient Vector Flow for Image Segmentation,” Computer Vision and Image Understanding, vol. 117, no. 9, pp. 1004–1016, 2013. [Publisher] (100+ citations as of January 2021)
M. E. Celebi, H. Kingravi, and F. Celiker, “Comments on ’On Approximating Euclidean Metrics by Weighted t-Cost Distances in Arbitrary Dimension’,” Pattern Recognition Letters, vol. 33, no. 10, pp. 1422–1425, 2012. [arXiv][Publisher]
M. E. Celebi and H. Kingravi, “Deterministic Initialization of the K-Means Algorithm Using Hierarchical Clustering,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 26, no. 7, 2012. [arXiv][Publisher]
M. E. Celebi, F. Celiker, and H. Kingravi, “On Euclidean Norm Approximations,” Pattern Recognition, vol. 44, no. 2, pp. 278–283, 2011. [arXiv][Publisher][Source Code]
M. E. Celebi, “Improving the Performance of K-Means for Color Quantization,” Image and Vision Computing, vol. 29, no. 4, pp. 260–271, 2011. [arXiv][Publisher] (nearly 200 citations as of April 2022)
Q. Wen and M. E. Celebi, “Hard versus Fuzzy C-Means Clustering for Color Quantization,” EURASIP Journal on Advances in Signal Processing, vol. 2011, no. 1, pp. 118–129, 2011. [Publisher]
Q. Abbas, M. E. Celebi, and I. F. Garcia, “Hair Removal Methods: A Comparative Study for Dermoscopy Images,” Biomedical Signal Processing and Control, vol. 6, no. 4, pp. 395–404, 2011. [Publisher] (100+ citations as of January 2021)
R. Garnavi, M. Aldeen, and M. E. Celebi, “Weighted Performance Index for Objective Evaluation of Border Detection Methods in Dermoscopy Images,” Skin Research and Technology, vol. 17, no. 1, pp. 35–44, 2011. [Publisher]
R. Garnavi, M. Aldeen, M. E. Celebi, G. Varigos, and S. Finch, “Border Detection in Dermoscopy Images Using Hybrid Thresholding on Optimized Color Channels,” Computerized Medical Imaging and Graphics, vol. 35, no. 2, pp. 105–115, 2011. [Publisher] (100+ citations as of January 2021)
H. Iyatomi, M. E. Celebi, G. Schaefer, and M. Tanaka, “Automated Color Calibration Method for Dermoscopy Images,” Computerized Medical Imaging and Graphics, vol. 35, no. 2, pp. 89–98, 2011. [Publisher]
G. Schaefer, M. I. Rajab, M. E. Celebi, and H. Iyatomi, “Colour and Contrast Enhancement for Improved Skin Lesion Segmentation,” Computerized Medical Imaging and Graphics, vol. 35, no. 2, pp. 99–104, 2011. [Publisher] (100+ citations as of January 2021)
H. Zhou, G. Schaefer, M. E. Celebi, F. Lin, and T. Liu, “Gradient Vector Flow with Mean Shift for Skin Lesion Segmentation,” Computerized Medical Imaging and Graphics, vol. 35, no. 2, pp. 121–127, 2011. [Publisher] (100+ citations as of January 2021)
M. E. Celebi, H. Kingravi, and F. Celiker, “Fast Color Space Transformations Using Minimax Approximations,” IET Image Processing, vol. 4, no. 2, pp. 70–79, 2010. [Publisher]
M. E. Celebi, H. Iyatomi, G. Schaefer, and W. V. Stoecker, “Lesion Border Detection in Dermoscopy Images,” Computerized Medical Imaging and Graphics, vol. 33, no. 2, pp. 148–153, 2009. [arXiv][Publisher] (400+ citations and 8th all-time most-cited CMIG article as of January 2021)
M. E. Celebi, H. Iyatomi, G. Schaefer, and W. V. Stoecker, “Approximate Lesion Localization in Dermoscopy Images,” Skin Research and Technology, vol. 15, no. 3, pp. 314–322, 2009. [arXiv][Publisher]
M. E. Celebi, H. Kingravi, R. Lukac, and F. Celiker, “Cost-Effective Implementation of Order-Statistics Based Vector Filters Using Minimax Approximations,” Journal of the Optical Society of America A, vol. 26, no. 6, pp. 1518–1524, 2009. [arXiv][Publisher]
M. E. Celebi, “Distance Measures for Reduced Ordering Based Vector Filters,” IET Image Processing, vol. 3, no. 5, pp. 249–260, 2009. [arXiv][Publisher]
M. E. Celebi, G. Schaefer, H. Iyatomi, W. V. Stoecker, J. M. Malters, and J. M. Grichnik, “An Improved Objective Evaluation Measure for Border Detection in Dermoscopy Images,” Skin Research and Technology, vol. 15, no. 4, pp. 444–450, 2009. [Publisher]
M. E. Celebi, “Fast Color Quantization Using Weighted Sort-Means Clustering,” Journal of the Optical Society of America A, vol. 26, no. 11, pp. 2434–2443, 2009. [arXiv][Publisher]
H. Zhou, G. Schaefer, A. Sadka, and M. E. Celebi, “Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images,” IEEE Journal of Selected Topics in Signal Processing, vol. 3, no. 1, pp. 26–34, 2009. [Publisher] (200+ citations as of November 2021)
M. E. Celebi and A. Aslandogan, “Robust Switching Vector Median Filter for Impulsive Noise Removal,” Journal of Electronic Imaging, vol. 17, no. 4, 2008. [Publisher]
M. E. Celebi, H. Iyatomi, W. V. Stoecker, R. H. Moss, H. S. Rabinovitz, G. Argenziano, and H. P. Soyer, “Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images,” Computerized Medical Imaging and Graphics, vol. 32, no. 8, pp. 670–677, 2008. [Publisher] (100+ citations as of January 2021)
M. E. Celebi, H. Kingravi, H. Iyatomi, A. Aslandogan, W. V. Stoecker, and R. H. Moss, “Border Detection in Dermoscopy Images Using Statistical Region Merging,” Skin Research and Technology, vol. 14, no. 3, pp. 347–353, 2008. [Publisher] (400+ citations and 8th all-time most-cited SRT article as of July 2021)
H. Iyatomi, H. Oka, M. E. Celebi, K. Ogawa, G. Argenziano, H. Soyer, H. Koga, T. Saida, K. Ohara, and M. Tanaka, “Computer-Based Classification of Dermoscopy Images of Melanocytic Lesions on Acral Volar Skin,” Journal of Investigative Dermatology, vol. 128, no. 8, pp. 2049–2054, 2008. [Publisher]
H. Iyatomi, H. Oka, M. E. Celebi, M. Hashimoto, M. Hagiwara, M. Tanaka, and K. Ogawa, “An Improved Internet-Based Melanoma Screening System with Dermatologist-like Tumor Area Extraction Algorithm,” Computerized Medical Imaging and Graphics, vol. 32, no. 7, pp. 566–579, 2008. [Publisher] (200+ citations as of January 2021)
M. E. Celebi, A. Aslandogan, and W. V. Stoecker, “Unsupervised Border Detection in Dermoscopy Images,” Skin Research and Technology, vol. 13, no. 4, pp. 454–462, 2007. [Publisher] (200+ citations as of June 2022)
M. E. Celebi, H. Kingravi, B. Uddin, H. Iyatomi, A. Aslandogan, W. V. Stoecker, and R. H. Moss, “A Methodological Approach to the Classification of Dermoscopy Images,” Computerized Medical Imaging and Graphics, vol. 31, no. 6, pp. 362–373, 2007. [arXiv][Publisher] (600+ citations and 3rd all-time most-cited CMIG article as of July 2021)
M. E. Celebi, H. Kingravi, and A. Aslandogan, “Nonlinear Vector Filtering for Impulsive Noise Removal from Color Images,” Journal of Electronic Imaging, vol. 16, no. 3, 2007. [arXiv][Publisher] (100+ citations as of January 2021)
M. E. Celebi, H. Kingravi, and B. Uddin, “Fast Switching Filter for Impulsive Noise Removal from Color Images,” Journal of Imaging Science and Technology, vol. 51, no. 2, pp. 155–165, 2007. [arXiv][Publisher]

Announcements

Organizer, Eighth ISIC Workshop on Skin Image Analysis, 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023)
Program Committee Member, SPIE Conference on Real-Time Image Processing and Deep Learning 2023
Guest Editor, Image Analysis in Advanced Skin Imaging Technology, Computer Methods and Programs in Biomedicine [2020 Impact Factor = 5.428]
Guest Editor, Multi-Modal Computing for Biomedical Diagnosis and Analysis, Information Processing & Management [2020 Impact Factor = 6.222]
Trust Colead, EPSCoR Research Infrastructure grant from the National Science Foundation ($24,000,000; 7/20–6/25)
Series Editor, Signals and Communication Technology, Springer
Series Editor, Unsupervised and Semi-Supervised Learning, Springer

Software