Gharsallah Saoussen

Handled MRI/CT data analysis
Applied advanced preprocessing
Generated synthetic CT from MRI data
Developed 2D/3D deep learning models

Radiotherapy and Medical Imaging: Development of a Deep Learning Approach for Generating Synthetic CT scans from MRI:
• Handled MRI/CT data analysis
• Applied advanced preprocessing
• Generated synthetic CT from MRI data
• Developed 2D/3D deep learning models

Estimation of a Tennis Player's Service Motion from 2D Smartphone Footage

Leveraged advanced preprocessing methodologies on 3D MRI scans for SLA patient analysis, encompassing registration, filtering, and image enhancement
Employed Python-based automation for precise segmentation and quantification of WMHs lesions through cutting-edge Deep Learning techniques

• Leveraged advanced preprocessing methodologies on 3D MRI scans for SLA patient analysis, encompassing registration, filtering, and
image enhancement.
• Employed Python-based automation for precise segmentation and quantification of WMHs lesions through cutting-edge Deep Learning
techniques.

Executed advanced preprocessing of MR brain images to optimize data for model integration
Engineered and refined CNN models for the precise automatic segmentation of white lesions
Expertly performed parameter tuning to enhance model performance, focusing on regularization, data augmentation, and initialization techniques
Leveraged Python and TensorFlow for robust application development in a cutting-edge research environment

• Executed advanced preprocessing of MR brain images to optimize data for model integration.
• Engineered and refined CNN models for the precise automatic segmentation of white lesions.
• Expertly performed parameter tuning to enhance model performance, focusing on regularization, data augmentation, and initialization
techniques.
• Leveraged Python and TensorFlow for robust application development in a cutting-edge research environmen

Executed advanced segmentation of vascular white matter hyperintensities in MR brain images utilizing state-of-the-art 3D preprocessing methods such as bias correction, contrast enhancement, and registration
Developed an innovative automatic segmentation model leveraging the Unet architecture to enhance diagnostic accuracy
Proficient in programming with Python and MATLAB to create robust applications for medical image analysis

• Executed advanced segmentation of vascular white matter hyperintensities in MR brain images utilizing state-of-the-art 3D
preprocessing methods such as bias correction, contrast enhancement, and registration.
• Developed an innovative automatic segmentation model leveraging the Unet architecture to enhance diagnostic accuracy.
• Proficient in programming with Python and MATLAB to create robust applications for medical image analysis.

Engineered an innovative circular-based micro-mixer for efficient molecular grafting, leveraging advanced COMSOL Multiphysics simulations
Spearheaded investigative research into the dynamics of vibrational-acoustic interactions within droplet systems

• Engineered an innovative circular-based micro-mixer for efficient molecular grafting, leveraging advanced COMSOL Multiphysics
simulations.
• Spearheaded investigative research into the dynamics of vibrational-acoustic interactions within droplet systems.