Mouloud Adel

928 total citations
45 papers, 626 citations indexed

About

Mouloud Adel is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Mouloud Adel has authored 45 papers receiving a total of 626 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 21 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Artificial Intelligence. Recurrent topics in Mouloud Adel's work include Medical Image Segmentation Techniques (14 papers), Brain Tumor Detection and Classification (10 papers) and Image Retrieval and Classification Techniques (8 papers). Mouloud Adel is often cited by papers focused on Medical Image Segmentation Techniques (14 papers), Brain Tumor Detection and Classification (10 papers) and Image Retrieval and Classification Techniques (8 papers). Mouloud Adel collaborates with scholars based in France, Vietnam and Türkiye. Mouloud Adel's co-authors include Salah Bourennane, Yi Yin, Éric Guedj, Xiaoxi Pan, Caroline Fossati, M. Rasigni, Julien Wojak, J. Conrath, Zhiyong Xiao and Stanislav Zvánovec and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and Pattern Recognition.

In The Last Decade

Mouloud Adel

43 papers receiving 605 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mouloud Adel France 14 320 295 195 129 111 45 626
Donghuan Lu China 11 329 1.0× 262 0.9× 116 0.6× 163 1.3× 216 1.9× 29 686
Murat Seçkin Ayhan Germany 7 204 0.6× 124 0.4× 49 0.3× 78 0.6× 272 2.5× 12 534
Mohammad Eslami Iran 9 130 0.4× 82 0.3× 57 0.3× 38 0.3× 88 0.8× 41 365
Zaka Ur Rehman Malaysia 8 197 0.6× 265 0.9× 90 0.5× 179 1.4× 117 1.1× 22 488
Hossam El-Din Moustafa Egypt 12 159 0.5× 110 0.4× 19 0.1× 223 1.7× 220 2.0× 56 536
G. Kavitha India 11 124 0.4× 133 0.5× 25 0.1× 58 0.4× 62 0.6× 73 354
Inas A. Yassine Egypt 9 150 0.5× 77 0.3× 19 0.1× 50 0.4× 63 0.6× 33 394
Roberto Rosas-Romero Mexico 10 96 0.3× 78 0.3× 37 0.2× 35 0.3× 84 0.8× 33 466
Nawrès Khlifa Tunisia 12 262 0.8× 112 0.4× 28 0.1× 28 0.2× 120 1.1× 60 524

Countries citing papers authored by Mouloud Adel

Since Specialization
Citations

This map shows the geographic impact of Mouloud Adel'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 Mouloud Adel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mouloud Adel more than expected).

Fields of papers citing papers by Mouloud Adel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mouloud Adel. 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 Mouloud Adel. The network helps show where Mouloud Adel may publish in the future.

Co-authorship network of co-authors of Mouloud Adel

This figure shows the co-authorship network connecting the top 25 collaborators of Mouloud Adel. A scholar is included among the top collaborators of Mouloud Adel 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 Mouloud Adel. Mouloud Adel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Acarman, Tankut, et al.. (2025). Quantification of Overlapping and Network Complexity in News: Assessment of Top2Vec and Fuzzy Topic Models. Applied Sciences. 15(17). 9627–9627.
2.
Adel, Mouloud, et al.. (2025). FDG-PET-based brain network analysis: a brief review of metabolic connectivity. PubMed. 9(1). 4–4. 3 indexed citations
3.
Adel, Mouloud, et al.. (2025). Comparative evaluation of graph construction methods for individual brain metabolic network from FDG-PET images: an ADNI study in healthy subjects. European Journal of Nuclear Medicine and Molecular Imaging. 53(2). 1139–1154.
4.
Thanh, Le Trung, Nguyen Linh Trung, Karim Abed‐Meraim, et al.. (2024). Tensor Kernel Learning for Classification of Alzheimer’s Conditions using Multimodal Data. SERVAL (Université de Lausanne). 12. 1–6. 1 indexed citations
5.
Adel, Mouloud, et al.. (2024). Noise Resilience in Dermoscopic Image Segmentation: Comparing Deep Learning Architectures for Enhanced Accuracy. Electronics. 13(17). 3414–3414. 1 indexed citations
6.
Fau, Pierre, et al.. (2023). Synthetic computed tomography generation for abdominal adaptive radiotherapy using low-field magnetic resonance imaging. Physics and Imaging in Radiation Oncology. 25. 100425–100425. 6 indexed citations
7.
Adel, Mouloud, et al.. (2022). C-Atlas: A Brain Mapping based on FDG-PET Images for Alzheimer's Disease Diagnosis. 150–155. 3 indexed citations
8.
Pan, Xiaoxi, et al.. (2020). Multi-View Separable Pyramid Network for AD Prediction at MCI Stage by 18F-FDG Brain PET Imaging. IEEE Transactions on Medical Imaging. 40(1). 81–92. 75 indexed citations
9.
Settouti, Nesma, et al.. (2019). Influence of normalization and color features on super-pixel classification: application to cytological image segmentation. Australasian Physical & Engineering Sciences in Medicine. 42(2). 427–441. 5 indexed citations
10.
Pan, Xiaoxi, et al.. (2019). Multiscale spatial gradient features for 18F-FDG PET image-guided diagnosis of Alzheimer’s disease. Computer Methods and Programs in Biomedicine. 180. 105027–105027. 17 indexed citations
11.
Pan, Xiaoxi, et al.. (2018). Multilevel Feature Representation of FDG-PET Brain Images for Diagnosing Alzheimer's Disease. IEEE Journal of Biomedical and Health Informatics. 23(4). 1499–1506. 26 indexed citations
12.
Adel, Mouloud, et al.. (2018). Histogram-Based Features Selection and Volume of Interest Ranking for Brain PET Image Classification. IEEE Journal of Translational Engineering in Health and Medicine. 6. 1–12. 33 indexed citations
13.
Xiao, Zhiyong, Mouloud Adel, & Salah Bourennane. (2013). Bayesian Method with Spatial Constraint for Retinal Vessel Segmentation. Computational and Mathematical Methods in Medicine. 2013. 1–9. 25 indexed citations
14.
Adel, Mouloud, et al.. (2012). Texture analysis of multi-spectral prostate tissue using Generalised Grey Level Difference Method. International Journal of Signal and Imaging Systems Engineering. 5(2). 78–78. 1 indexed citations
15.
Yin, Yi, Mouloud Adel, & Salah Bourennane. (2011). Retinal vessel segmentation using a probabilistic tracking method. Pattern Recognition. 45(4). 1235–1244. 117 indexed citations
16.
Adel, Mouloud, et al.. (2009). Detection of the foveal avascular zone on retinal angiograms using Markov random fields. Digital Signal Processing. 20(1). 149–154. 33 indexed citations
17.
Adel, Mouloud, M. Rasigni, Salah Bourennane, & V. Juhan. (2007). Statistical Segmentation of Regions of Interest on a Mammographic Image. EURASIP Journal on Advances in Signal Processing. 2007(1). 11 indexed citations
18.
Rabhi, Abdelhamid, et al.. (2006). Segmentation d'images ultrasonores par les régions actives géodésiques. 27(1). 8–18. 2 indexed citations
19.
Barthes, Angéla, et al.. (2001). Mathematical morphology in computerized analysis of angiograms in age‐related macular degeneration. Medical Physics. 28(12). 2410–2419. 11 indexed citations
20.
Adel, Mouloud, et al.. (1997). Fast algorithm for texture discrimination by use of a separable orthonormal decomposition of the co-occurrence matrix. Applied Optics. 36(32). 8313–8313. 21 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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