Dmitry B. Goldgof

13.9k total citations · 2 hit papers
275 papers, 9.5k citations indexed

About

Dmitry B. Goldgof is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Dmitry B. Goldgof has authored 275 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 136 papers in Computer Vision and Pattern Recognition, 74 papers in Artificial Intelligence and 63 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Dmitry B. Goldgof's work include Radiomics and Machine Learning in Medical Imaging (50 papers), Medical Image Segmentation Techniques (49 papers) and Advanced Vision and Imaging (41 papers). Dmitry B. Goldgof is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (50 papers), Medical Image Segmentation Techniques (49 papers) and Advanced Vision and Imaging (41 papers). Dmitry B. Goldgof collaborates with scholars based in United States, China and United Kingdom. Dmitry B. Goldgof's co-authors include Lawrence Hall, Robert J. Gillies, Robert A. Gatenby, Yoganand Balagurunathan, Matthew B. Schabath, Steven A. Eschrich, Virendra Kumar, Kevin W. Bowyer, Yuhua Gu and Sudeep Sarkar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Dmitry B. Goldgof

261 papers receiving 9.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Radiomics: the process and the challenges

2012 1.7k citations Matthew B. Schabath, Dmitry B. Goldgof et al. profile →
An experimental comparison of range image segmentation algorithms

1996 554 citations Dmitry B. Goldgof et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dmitry B. Goldgof United States	46	4.1k	3.3k	2.4k	1.6k	1.4k	275	9.5k
Tom Vercauteren United Kingdom	42	4.3k 1.0×	4.0k 1.2×	1.8k 0.7×	924 0.6×	2.2k 1.6×	251	11.2k
Frederik Maes Belgium	50	5.3k 1.3×	5.1k 1.5×	1.1k 0.5×	1.1k 0.7×	2.1k 1.6×	307	13.5k
Josien P. W. Pluim Netherlands	40	6.1k 1.5×	5.9k 1.8×	2.4k 1.0×	1.3k 0.8×	2.2k 1.6×	180	12.5k
Nikos Paragios France	46	3.1k 0.8×	6.2k 1.9×	1.4k 0.6×	906 0.6×	1.3k 1.0×	198	10.5k
Jianhua Yao United States	50	4.5k 1.1×	2.6k 0.8×	3.3k 1.4×	1.5k 0.9×	2.1k 1.6×	377	12.7k
Jayaram K. Udupa United States	59	3.8k 0.9×	5.7k 1.7×	1.2k 0.5×	1.2k 0.7×	1.8k 1.4×	428	12.1k
Karthikeyan Shanmugam United States	17	3.3k 0.8×	6.2k 1.9×	3.8k 1.6×	875 0.5×	1.3k 1.0×	72	18.5k
I. Dinstein Israel	21	3.3k 0.8×	6.7k 2.0×	3.7k 1.5×	879 0.5×	1.4k 1.0×	86	17.6k
Paul Suetens Belgium	63	7.0k 1.7×	6.2k 1.9×	1.1k 0.5×	889 0.5×	4.2k 3.1×	429	17.4k
Ben Glocker United Kingdom	40	3.4k 0.8×	5.0k 1.5×	2.2k 0.9×	572 0.4×	1.5k 1.1×	151	10.1k

Countries citing papers authored by Dmitry B. Goldgof

Since Specialization

Citations

This map shows the geographic impact of Dmitry B. Goldgof's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dmitry B. Goldgof with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitry B. Goldgof more than expected).

Fields of papers citing papers by Dmitry B. Goldgof

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dmitry B. Goldgof. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dmitry B. Goldgof. The network helps show where Dmitry B. Goldgof may publish in the future.

Co-authorship network of co-authors of Dmitry B. Goldgof

This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry B. Goldgof. A scholar is included among the top collaborators of Dmitry B. Goldgof based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dmitry B. Goldgof. Dmitry B. Goldgof is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Weinheimer, Carla J., et al.. (2024). Synergizing Deep Learning-Enabled Preprocessing and Human–AI Integration for Efficient Automatic Ground Truth Generation. Bioengineering. 11(5). 434–434. 1 indexed citations

Mouton, Peter R., et al.. (2024). Active Prompting of Vision Language Models for Human-in-the-loop Classification and Explanation of Microscopy Images. 205–212. 1 indexed citations

Hall, Lawrence, et al.. (2024). Repeatability of Fine-Tuning Large Language Models Illustrated Using QLoRA. IEEE Access. 12. 153221–153231. 5 indexed citations

Goldgof, Dmitry B., Lawrence Hall, Joseph Johnson, et al.. (2023). Classifying Malignancy in Prostate Glandular Structures from Biopsy Scans with Deep Learning. Cancers. 15(8). 2335–2335. 2 indexed citations

Hossain, Md. Imran, et al.. (2023). Explainable AI for Medical Data: Current Methods, Limitations, and Future Directions. ACM Computing Surveys. 57(6). 1–46. 25 indexed citations

Goldgof, Dmitry B., et al.. (2022). A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 7458–7477. 6 indexed citations

Hall, Lawrence, et al.. (2022). Achieving Multisite Generalization for CNN-Based Disease Diagnosis Models by Mitigating Shortcut Learning. IEEE Access. 10. 78726–78738. 7 indexed citations

Goldgof, Dmitry B., et al.. (2021). An adaptive digital stain separation method for deep learning-based automatic cell profile counts. Journal of Neuroscience Methods. 354. 109102–109102. 5 indexed citations

Mouton, Peter R., Ghada Zamzmi, Dmitry B. Goldgof, et al.. (2021). Future roles of artificial intelligence in early pain management of newborns. SHILAP Revista de lepidopterología. 3(3). 134–145. 19 indexed citations

10.

Goldgof, Gregory M., et al.. (2021). Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification. IEEE Access. 9. 72970–72979. 26 indexed citations

11.

Zamzmi, Ghada, et al.. (2020). Multimodal spatio-temporal deep learning approach for neonatal postoperative pain assessment. Computers in Biology and Medicine. 129. 104150–104150. 51 indexed citations

12.

Goldgof, Dmitry B., et al.. (2020). Challenges for the Repeatability of Deep Learning Models. IEEE Access. 8. 211860–211868. 51 indexed citations

13.

Canavan, Shaun, et al.. (2020). Gaze-based classification of autism spectrum disorder. Pattern Recognition Letters. 135. 204–212. 13 indexed citations

14.

Cherezov, Dmitry, Dmitry B. Goldgof, Lawrence Hall, et al.. (2019). Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness. Scientific Reports. 9(1). 4500–4500. 34 indexed citations

15.

Phoulady, Hady Ahmady, Dmitry B. Goldgof, Lawrence Hall, Kevin Nash, & Peter R. Mouton. (2019). Automatic stereology of mean nuclear size of neurons using an active contour framework. Journal of Chemical Neuroanatomy. 96. 110–115. 3 indexed citations

16.

Zamzmi, Ghada, Rahul Paul, Dmitry B. Goldgof, et al.. (2019). Convolutional Neural Networks for Neonatal Pain Assessment. IEEE Transactions on Biometrics Behavior and Identity Science. 1(3). 192–200. 14 indexed citations

17.

Zhou, Mu, Jacob G. Scott, Baishali Chaudhury, et al.. (2017). Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches. American Journal of Neuroradiology. 39(2). 208–216. 272 indexed citations

18.

Fefilatyev, Sergiy, et al.. (2006). Horizon Detection Using Machine Learning Techniques. 17–21. 66 indexed citations

19.

Kramer, Kurt, Dmitry B. Goldgof, Lawrence Hall, et al.. (2005). Active Learning to Recognize Multiple Types of Plankton. Journal of Machine Learning Research. 6(20). 589–613. 129 indexed citations

20.

Kambhamettu, Chandra, Dmitry B. Goldgof, Demetri Terzopoulos, & Thomas S. Huang. (1994). Nonrigid motion analysis. 135(5). 405–430. 38 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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