Refining COVID‐19 Lesion Segmentation in Lung CT Scans Using Swarm Intelligence and Evolutionary Algorithms

The findings demonstrate the effectiveness of swarm and evolutionary algorithms in segmenting COVID-19 lesions, contributing to enhanced diagnostic accuracy and treatment efficiency.

Authors

Anis Sakly (ORCID: https://orcid.org/0000-0002-3608-0386)
Marwa Fradi
Wafa Gtifa
Mohsen Machhout (ORCID: https://orcid.org/0000-0002-5629-0508)

Institutions

University of Monastir (TN)

Publication Details

Journal: International Journal of Medical Robotics and Computer Assisted Surgery
Published: 2025-02-01
DOI: https://doi.org/10.1002/rcs.70044
Primary Topic: COVID-19 diagnosis using AI
Type: article
Field-Weighted Citation Impact: 0.00

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article

Refining COVID‐19 Lesion Segmentation in Lung CT Scans Using Swarm Intelligence and Evolutionary Algorithms

Anis Sakly, Marwa Fradi, Wafa Gtifa, Mohsen Machhout

Feb 1, 2025

International Journal of Medical Robotics and Computer Assisted Surgery

COVID-19 diagnosis using AI

article

Refining COVID‐19 Lesion Segmentation in Lung CT Scans Using Swarm Intelligence and Evolutionary Algorithms

Anis Sakly, Marwa Fradi, Wafa Gtifa, Mohsen Machhout

February 1, 2025article en

Abstract

The findings demonstrate the effectiveness of swarm and evolutionary algorithms in segmenting COVID-19 lesions, contributing to enhanced diagnostic accuracy and treatment efficiency.

International Journal of Medical Robotics and Computer Assisted SurgeryVol. 21(1)

University of Monastir (TN)

Good health and well-being

Openalex Percentile: Top 97%

COVID-19 diagnosis using AI

DOI Source OpenAlex

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Refining COVID‐19 Lesion Segmentation in Lung CT Scans Using Swarm Intelligence and Evolutionary Algorithms — Anis Sakly, Marwa Fradi, et al. · International Journal of Medical Robotics and Computer Assisted Surgery (2025) | TGRS Research Map | TGRS