Highly Performing Automatic Detection of Structural Chromosomal Abnormalities Using Siamese Architecture

Autor: Bechar, Mohammed El Amine, Guyader, Jean-Marie, El Bouz, Marwa, Douet-Guilbert, Nathalie, Al Falou, Ayman, Troadec, Marie-Bérengère

Publikováno v: In Journal of Molecular Biology 15 April 2023 435(8)

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Autor: Settouti Nesma, Douibi Khalida, Bechar Mohammed El Amine, Daho Mostafa El Habib, Saidi Meryem

Publikováno v: Open Computer Science, Vol 9, Iss 1, Pp 226-242 (2019)

Over the last few years, Multi-label classification has received significant attention from researchers to solve many issues in many fields. The manual annotation of available datasets is time-consuming and need a huge effort from the expert, especia

Externí odkaz: https://doaj.org/article/621945e32bb44038bfd5a7d9b6cf8634

Automatic detection of a structural chromosomal abnormality: the del(5q) deletion

Autor: Alam, Mohammad S., Asari, Vijayan K., Bechar, Mohammed El Amine, Guyader, Jean-Marie, El Bouz, Marwa, Douet-Guilbert, Nathalie, Al Falou, Ayman, Troadec, Marie-Bérengère

Publikováno v: Proceedings of SPIE; June 2023, Vol. 12527 Issue: 1 p125270O-125270O-5, 1127436p

Medical Images Classification Based on Deep Features Extraction Exploiting Transfer Learning

Autor: Briki, Mohamed Elamine, Nesma Settouti, Bechar, Mohammed El Amine

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::832a9a12febb6a75f554b676f09abc95

An optimised pixel-based classification approach for automatic white blood cells segmentation

Autor: Settouti, Nesma, Bechar, Mohammed El Amine, Daho, Mostafa El Habib, Chikh, Mohammed Amine

Publikováno v: International Journal of Biomedical Engineering and Technology (IJBET)
International Journal of Biomedical Engineering and Technology (IJBET), Inderscience, 2020, 32 (2), pp.144. ⟨10.1504/IJBET.2020.105651⟩
International Journal of Biomedical Engineering and Technology (IJBET), 2020, 32 (2), pp.144. ⟨10.1504/IJBET.2020.105651⟩

International audience; The pixel-based classification is an automatic approach for classifying all pixels in the image but does not take into account the spatial information for the region of interest. On the other hand, region-growing methods take

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3380488af272ceb9f6af2206db23bb44
https://doi.org/10.1504/ijbet.2020.105651