Ahmedou Moulaye IDRISS (Faculté de médecine de Nouakchott, Université de Nouakchott, Mauritania)
Fatimetou Mohamed-Saleck (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Moustapha Mohamed Saleck (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Mohamed Mahmoud Septy Mohamed bamba (Faculté de médecine de Nouakchott, Université de Nouakchott, Mauritania)
Mohamed Abdellahi Sidi Mohamed Blal (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
El Hacen Mohamed Soueilem (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Mohamedou (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Mohamed Boullah (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Aichetou Ndiaye Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Fatimetou Hademine (Faculté des Sciences et Techniques, Université de Nouakchott, Mauritania)
Project Description
The Mauritanian approach aims to make 3D Slicer accessible to a broader audience of users and researchers in the medical field. Various projects have been completed, initiated, or are currently under consideration, including:
The anatomical atlas created by professors Idriss and Yahya in 2018 enabled medical students to visualize and quickly assimilate human body parts through the use of 3D Slicer.
Other applications for generating 3D models of baby and expectant mother mannequins.
Implementation and integration of three breast cancer segmentation methods by one of our researchers: An adaptive fuzzy C-means algorithm, An adaptive k-means algorithm, and an adaptive Otsu thresholding. Integration is underway.
Processing and segmentation of medical images with 3D Slicer and Deep Learning in the context of an integrated approach for analyzing various medical data from Mauritania. This is the subject of an ongoing doctoral thesis.
Testing, correcting, and if necessary, completing the translation of 3D Slicer modules into Arabic.
Other upcoming applications are planned.
Objective
Facilitate access to 3D Slicer for medical students to enhance understanding and manipulation of the human body.
Generate 3D models of baby and expectant mother mannequins.
Contribute to enriching breast cancer segmentation methods by introducing and comparing user choices in 3D Slicer.
Aim to make 3D Slicer usable by a wider audience of Mauritanian and Arabic-speaking users (practitioners, students, and researchers).
Explore cutting-edge techniques in medical image processing and segmentation, especially those based on Deep Learning, implement them, and evaluate performance.
Anticipate additional upcoming applications.
Approach and Plan
Anatomical Atlas:
3D Model of Baby and Expectant Mother:
Introduction of 3 Segmentation Methods:
4 .Arabization of 3D Slicer:
Segmentation of Medical Images from Mauritania:
Other upcoming applications:
Progress and Next Steps
Progress of the anatomical atlas: ...
Progress in generating 3D models of the baby and expectant mother.
Progress in integrating the 3 segmentation methods.
Progress of the doctoral thesis: Segmentation of Medical Images from Mauritania.
Progress in contributing to the Arabic translation:
Draft Status
Ready - team will start page creating immediately
Category
Other
Presenter Location
In-person
Key Investigators
Project Description
The Mauritanian approach aims to make 3D Slicer accessible to a broader audience of users and researchers in the medical field. Various projects have been completed, initiated, or are currently under consideration, including:
Objective
Approach and Plan
Progress and Next Steps
Illustrations
No response
Background and References
No response