About

PhD Candidate & Computer Engineer.

I am a PhD candiate in Medical Image Analysis and Federated Learning at the Biomedical Imaging Group Rotterdam, Erasmus MC, under the supervision of Prof. Dr. Stefan Klein and Dr. Esther Bron. My research focuses on the application of deep learning techniques to advance the field of radiology, with an emphasis on upholding fairness, data privacy, and security. I am currently working on establishing a real-world fedearated network across multiple memory clinics in the Netherlands, with the final aim of building a federated deep learning model for the differential diagnosis of Dementia leveraging multimodal data.
I am a graduate of the Erasmus Mundus Joint Master Degree in Medical Imaging and Applications coordinated by the university of Girona, Spain, with a grant from the European Union. I conducted my Master's thesis at the The Duke Center for Virtual Imaging Trials under the supervision of Dr. Joseph Lo, where I worked on geometric diffusion models for improving the shape modeling of the large intestine.

I hold a Bachelor's Degree in Computer Engineering from Eskisehir Technical University, Turkey. I graduated on June 2021 with First Class Honors after 5 years of undergraduatestudies as a "Turkiye Burslari" scholar. I worked as part-time candidate researcher at TUBITAK YTE for the period January 2020 - August 2021 after a successful summer internship at the same Institute.

Skills

Programming

Python, Java, C++, MatLab, R, JavaScript, PHP

AI and Computer Vision

PyTorch, MONAI, Simple ITK, Sci-kit Learn, OpenCV

Federated Learning

Nvidia-Flare, Vantage6

Database Management

PostgreSQL, SQL, XNAT

Resume

Find my complete CV here...

Summary

Kaouther MOUHEB

PhD Candidate, M.Sc. in medical imaging and applications.

  • Rotterdam, the Netherlands
  • k.mouheb@erasmusmc.nl

Education

PhD in Medical Image Analysis & Federated Learning

2023 - present

Dept. of Radiology & Nuclear Medicine, Erasmus MC

Master in Medical Imaging & Applications

2021 - 2023

University of Girona, University of Burgundy, University of Cassino and Southern Lazio

Erasmus Mundus Joint Master Degree
grade: 9.7/10

Bachelor of Computer Engineering

2016 - 2021

Eskisehir Technical University

Graduated as Valedictorian on June 2021
Grade: 3.99/4

Experience

Visiting Researcher

Jan-Jul 2023

CVIT, Duke University, NC, USA

  • Supervised by Dr. Joseph Lo
  • Worked on improving the 3D shape modeling of the large intesting using Geometric Diffusion Models.

Graduate Research Intern

Jul-Aug 2022

ViCOROB Lab, UdG, Girona

  • Supervised by Dr. Robert Marti
  • Worked with a team on Breast Density Estimation using Federated Learning.

Candidate Researcher

Jan-Aug 2021

TUBITAK Software Technologies Research Institute, Ankara, Turkey

  • Project: Expenses Management Systems of the Turkish Ministry of Treasury and Finance.
  • Participated as a Full-Stack developer in designing a software system based on the micro-service architecture following the domain driven design paradigm.

Undergraduate Research Intern

Sep 2020 - Jan 2021

ESTU Electrical and Electronics Engineering Department

  • Supervised by Dr. Cihan Topal.
  • Worked on developing an automatic system for face liveness detection during online meetings based on unisotropic diffusion and deep learning.

Software Development Intern

Jun-Aug 2020

TUBITAK Software Technologies Research Institute, Ankara, Turkey

  • Developed an event management system for the institute with a Spring Boot based backend, a React-based web front-end and a PostgreSQL database.

Projects

Skin Lesion Segmentation and Classification

We addressed the tasks of skin lesion segmentation and classification using two approaches, a classical pipeline using advanced image processing techniques and traditional machine learning, and a deep learning-based method. [Code]

Heart Axes Detection

Worked within a team during the third "Datacare AI Santé Datathon" on detecting the main axes of the heart from MRI images by combining deep learning-based segmentation and image processing techniques. Supervised by Sarah Leclerc and Alain Lalande.