Rostom Kachouri

999 total citations
26 papers, 533 citations indexed

About

Rostom Kachouri is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Ophthalmology. According to data from OpenAlex, Rostom Kachouri has authored 26 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 11 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Ophthalmology. Recurrent topics in Rostom Kachouri's work include Retinal Imaging and Analysis (11 papers), Retinal Diseases and Treatments (6 papers) and Image Retrieval and Classification Techniques (6 papers). Rostom Kachouri is often cited by papers focused on Retinal Imaging and Analysis (11 papers), Retinal Diseases and Treatments (6 papers) and Image Retrieval and Classification Techniques (6 papers). Rostom Kachouri collaborates with scholars based in France, Tunisia and Algeria. Rostom Kachouri's co-authors include Mohamed Akil, Rachida Saouli, Mostefa Ben Naceur, Asma Ben Abdallah, Yaroub Elloumi, Mohamed Hédi Bedoui, H. Mâaref, Najia Es-Sbai, Ahmed Ben Atitallah and Hassène Mnif and has published in prestigious journals such as Pattern Recognition, Medical Image Analysis and Computer Methods and Programs in Biomedicine.

In The Last Decade

Rostom Kachouri

22 papers receiving 505 citations

Peers

Rostom Kachouri

CVPR

NEURO

RNMI

OPHTH

Shafiullah Soomro South Korea

Nancy M. Salem Egypt

Sarmad Maqsood Lithuania

Zaka Ur Rehman Malaysia

Pierre-Henri Conze France

N. Veeranjaneyulu India

Saleha Masood Pakistan

Zhaoqiang Yun China

Ahmed Atwan Egypt

Baisen Cong China

Shafiullah Soomro South Korea

Rostom Kachouri

348 ×1.0

CVPR

158 ×0.7

NEURO

268 ×1.2

RNMI

124 ×1.2

112 ×1.1

OPHTH

Citations per year, relative to Rostom Kachouri Rostom Kachouri (= 1×) peers Shafiullah Soomro

Countries citing papers authored by Rostom Kachouri

Since Specialization

Citations

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

Fields of papers citing papers by Rostom Kachouri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rostom Kachouri

This figure shows the co-authorship network connecting the top 25 collaborators of Rostom Kachouri. A scholar is included among the top collaborators of Rostom Kachouri 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 Rostom Kachouri. Rostom Kachouri 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

Kachouri, Rostom, et al.. (2025). Mobile-based deep learning system for early detection of diabetic retinopathy. Intelligence-Based Medicine. 12. 100259–100259. 1 indexed citations

Elloumi, Yaroub & Rostom Kachouri. (2025). Ensemble learning–based method for multiple sclerosis screening from retinal OCT images. Medical & Biological Engineering & Computing. 63(12). 3735–3748.

Kachouri, Rostom, et al.. (2024). Enhancing Myocardial Disease Prediction with DOC-NET+ Architecture: A Custom Data Analysis Approach for the EMIDEC Challenge. Procedia Computer Science. 235. 3217–3225.

Elloumi, Yaroub, et al.. (2024). Ensemble learning based method for severity detection of Age-Related Macular Degeneration. 1–6. 1 indexed citations

Elloumi, Yaroub, et al.. (2024). High Performance and Low Complexity Retinal Vessel Segmentation Method Based on Extended DCNN. SPIRE - Sciences Po Institutional REpository. 1–6. 1 indexed citations

Kachouri, Rostom, et al.. (2024). 3D-HEVC Fast Partitioning Algorithm Based on MD-CNN. 1–6. 1 indexed citations

Elloumi, Yaroub, et al.. (2023). Deep Learning Architecture with an Optimized Convolutional Processing for the Segmentation of Retinal Blood Vessels. SPIRE - Sciences Po Institutional REpository. 2451–2456.

Kachouri, Rostom, et al.. (2023). Early glaucoma screening Decision Tree using in-depth clinical analysis of the optic nerve head. SPIRE - Sciences Po Institutional REpository. 82. 1–6. 1 indexed citations

Elloumi, Yaroub, et al.. (2023). Retinal blood vessel segmentation from high resolution fundus image using deep learning architecture. SPIRE - Sciences Po Institutional REpository. 471–476. 2 indexed citations

10.

Elloumi, Yaroub, et al.. (2022). Automated method for real-time AMD screening of fundus images dedicated for mobile devices. Medical & Biological Engineering & Computing. 60(5). 1449–1479. 13 indexed citations

11.

Elloumi, Yaroub, et al.. (2021). Fast and efficient retinal blood vessel segmentation method based on deep learning network. Computerized Medical Imaging and Graphics. 90. 101902–101902. 67 indexed citations

12.

Naceur, Mostefa Ben, Mohamed Akil, Rachida Saouli, & Rostom Kachouri. (2020). Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy. Medical Image Analysis. 63. 101692–101692. 136 indexed citations

13.

Kachouri, Rostom, et al.. (2019). Fully automated method for glaucoma screening using robust optic nerve head detection and unsupervised segmentation based cup-to-disc ratio computation in retinal fundus images. Computerized Medical Imaging and Graphics. 77. 101643–101643. 50 indexed citations

14.

Naceur, Mostefa Ben, Rachida Saouli, Mohamed Akil, & Rostom Kachouri. (2018). Fully Automatic Brain Tumor Segmentation using End-To-End Incremental Deep Neural Networks in MRI images. Computer Methods and Programs in Biomedicine. 166. 39–49. 167 indexed citations

15.

Kachouri, Rostom & Mohamed Akil. (2015). Hardware design to accelerate PNG encoder for binary mask compression on FPGA. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9400. 940003–940003. 1 indexed citations

16.

Kachouri, Rostom, et al.. (2015). Gamma correction acceleration for real-time text extraction from complex colored images. HAL (Le Centre pour la Communication Scientifique Directe). 16. 527–531. 2 indexed citations

17.

Kachouri, Rostom, et al.. (2014). GPU parallel implementation of the new hybrid binarization based on Kmeans method (HBK). Journal of Real-Time Image Processing. 14(2). 363–377. 11 indexed citations

18.

Kachouri, Rostom, et al.. (2011). Multiple kernel weighting based SVM for heterogeneous image recognition system. International Journal of Signal and Imaging Systems Engineering. 4(2). 60–60. 1 indexed citations

19.

Kachouri, Rostom, et al.. (2010). Multi-model classification method in heterogeneous image databases. Pattern Recognition. 43(12). 4077–4088. 4 indexed citations

20.

Kachouri, Rostom, et al.. (2008). HETEROGENEOUS IMAGE RETRIEVAL SYSTEM BASED ON FEATURES EXTRACTION AND SVM CLASSIFIER. 137–142. 1 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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