Zakia Khatun

Zakia Khatun

Data Scientist | AI-Driven Radiology & Digital Health | PhD, Marie Skłodowska-Curie Actions Fellow (ITN)

Early Stage Researcher, EU H2020-MSCA-ITN-EJD Program

Biography

Zakia Khatun is an AI researcher working at the intersection of radiology, machine learning, and computer vision. She holds a double PhD from the prestigious EU H2020-MSCA-ITN European Joint Doctorate program (P4FIT) in Information Engineering and Biomedical Engineering. Her recent work focuses on developing AI-powered algorithms that enhance diagnostic accuracy, support clinical decision-making, and mitigate human bias. Fueled by a deep passion for machine learning and computer vision, she is dedicated to translating cutting-edge research into practical healthcare solutions with tangible real-world impact.

Interests

  • Artificial Intelligence
  • Radiology & Computer-Aided Diagnosis
  • Predictive Modeling
  • Data Science & Analytics
  • Healthcare Innovation & Project Collaboration

Education

  • PhD in Biomedical Engineering & PhD in Information Engineering, EU H2020-MSCA-ITN-EJD (P4FIT Project)

    Reykjavík University, Iceland & Università degli Studi di Salerno, Italy

  • Erasmus Mundus Joint Master Degree in Medical Imaging and Applications

    University of Burgundy, France; University of Cassino, Italy; University of Girona, Spain

  • BSc in Electrical & Electronic Engineering

    American International University-Bangladesh, Bangladesh

Publications

Zakia Khatun, Sara Kristinsdóttir, Arndís Thóra Thórisdóttir, Linda Björk Halldórsdóttir, Francesco Tortorella, Paolo Gargiulo, Thordur Helgason (2025). Assessing Neuromuscular System via Patellar Tendon Reflex Analysis using EMG in Healthy Individuals.

DOI

Zakia Khatun, Halldór Jónsson Jr, Paolo Gargiulo, Francesco Tortorella (2025). Graph Echo State Network for MRI-based Tendon Pathology Classification.

Zakia Khatun, Halldór Jónsson Jr, Mariella Tsirilaki, Nicola Maffulli, Francesco Oliva, Pauline Daval, Francesco Tortorella, Paolo Gargiulo (2024). Beyond pixel Superpixel-based MRI Segmentation through Traditional Machine Learning and Graph Convolutional Network.

DOI

Zakia Khatun, Mariella Tsirilaki, Alessia Lindemann, Francesco Tortorella, Nicola Maffulli, Halldor Jonsson Jr, Paolo Gargiulo (2022). The Role of Muscle and Tendon in Predicting Cartilage Degeneration and Tendinopathy.

DOI

Projects

Advancing Human Soft Tissue Pathology Assessment Using Artificial Intelligence in Medical Imaging

This thesis presents my original research on assessing human soft tissue pathologies through the application of artificial intelligence (AI) to medical imaging. The significance of this work lies in the development of automated systems that enhance the understanding of human soft tissue-related pathologies. These systems aim to support more reliable clinical decision-making and enable earlier interventions by minimizing human error and variability, ultimately improving patient outcomes.
Zakia Khatun, Halldór Jónsson Jr, Francesco Tortorella, Paolo Gargiulo
Advancing Human Soft Tissue Pathology Assessment Using Artificial Intelligence in Medical Imaging

Survival Time Prediction of Metastatic Melanoma Patients by Computed Tomography using Convolutional Neural Networks

This study aims to predict the 1-year survival time of patients with metastatic melanoma using a binary classification approach. The dataset consists of CT scans from 71 patients diagnosed with metastatic melanoma, all studied at Université Clermont Auvergne Hospital, France. The number of lesions per patient ranges from 1 to 11. The survival time is predicted by feeding the CT scan data into a 3D Convolutional Neural Network (CNN), which serves as the model to anticipate the survival outcome based on the available imaging data.
Zakia Khatun, Adrien Bartoli
Survival Time Prediction of Metastatic Melanoma Patients by Computed Tomography using Convolutional Neural Networks

To Design, Analyze, and Implement Approaches for Brain Tissue Segmentation

The main goal of this project was to develop tissue (WM, GM, and CSF) segmentation methods in brain MRI images. The dataset used is IBSR18, which contains 18 skull-stripped and bias field-corrected T1-w images with different spatial resolutions (pixel spacing), and there is a heterogeneity in image intensities that hinders segmentation. System architecture used - Data → Pre-processing → Segmentation (3D patch-wise segmentation using 3D U-Net).
Zakia Khatun
To Design, Analyze, and Implement Approaches for Brain Tissue Segmentation

Developing Computer Aided Algorithm for the Diagnosis in Histopathological Images to Classify Benign vs Malignant Using Deep Learning Approach

The main objective of this project was to design a computer-aided diagnosis system to develop a deep learning algorithm for diagnosis in histological patches to classify benign vs malignant patches. System architecture used - Image → Normalization → Per instance standardization → Aggressive Data Augmentation → Classification.
Zakia Khatun, Nur Adhianti, khrystyna Faryna
Developing Computer Aided Algorithm for the Diagnosis in Histopathological Images to Classify Benign vs Malignant Using Deep Learning Approach

Developing Computer Aided Algorithm for the Diagnosis in Dermoscopic Images to Classify Melanoma vs All Other Types Using Deep Learning Approach

The main goal of this project was to design a computer-aided diagnosis system to classify dermoscopic images and determine whether any case belongs to Nevus or lesion. System architecture - Image → Normalization → Per instance standardization → Aggressive Data Augmentation → Classification.
khrystyna Faryna, Zakia Khatun, Nur Adhianti

Image Registration of Chest CT Volumes; 4DCT DIR-Lab Challenge

This project aims to register 3D CT lung images, which was tested on the first 4 cases available on 4DCT DIR-Lab Challenge. Where data is available with 300 landmark annotations. Evaluation is made using TRE 3D Euclidean distance between transformed landmarks.
Patricia Cabanillas Silva, Zakia Khatun, Ahmed Gouda
Image Registration of Chest CT Volumes; 4DCT DIR-Lab Challenge

Demonstration of Medical Robotics in Spine Surgery using Tx60 Staubli Robot

The goal of this project was to demonstrate pedicle screw placement for spine fusion. Steps - 1) Trajectory planning (Type of movement is Point to point), 2) Software simulation of robotic spine surgery (Stäubli Robotics Suite), and 3) Testing demo surgery using Tx60 Stabuli.
Zakia Khatun, Zohaib Salahuddin, Tewodros Arega
Demonstration of Medical Robotics in Spine Surgery using Tx60 Staubli Robot

Breast Mass Detection using Machine Learning Algorithms

The main aim of this project was to design a computer-aided diagnosis system that can detect mass/masses in mammograms to help the screening procedure. System architecture - Image → Candidate extraction → Feature extraction → Classification.
Isaac Llorente, Zakia Khatun, Pierpaollo Vendetelli
Breast Mass Detection using Machine Learning Algorithms

CT Reconstruction using Parallelization Strategy

This project proposes a discrete image reconstruction algorithm using parallel beam geometry where a set of X-ray beams are passed through the object of interest and intensity variations of the beams at input and output are measured. To reconstruct, filtered back projection is used, which uses a 1D filter on the projection data before back projecting (2D or 3D) the data onto the image space.
khrystyna Faryna, Nur Adhianti, Zakia Khatun
CT Reconstruction using Parallelization Strategy

Vision Application (VIZN)

The VIZN application provides an environment where users will be able to test some performance related to the eyesight, observing the evolution over time by means of innovative user controls. In this project, all the tests were prepared in a scientific way.
Isaac Llorente, Valeria Abramova, Zakia Khatun, Nur Adhianti
Vision Application (VIZN)

Designing an Inverse Kinematics Controller

The purpose of this project was to design an Inverse Kinematic controller for the Kinova Jaco2 robot to follow some given tasks. The control objectives include position only without exploiting the redundancy, given by both the position and the orientation, the end-effector orientation needs to be changed, and the redundancy needs to be exploited by maximizing the manipulability.
Zakia Khatun

Interest Points Detection on 3D Meshes Using Harris Operator

In this project, an adaptive technique was implemented to determine interest points or 3D objects based on the Harris operator, which is done by determining the neighborhood of a vertex over which the Harris response is calculated.
Roa’a Khaled, Zakia Khatun, Nur Adhianti
Interest Points Detection on 3D Meshes Using Harris Operator

Automatic MRI Cardiac Segmentation in Short Axis for Left Ventricular Endocardium

The main aim of this project was to improve the accuracy of automatic Left ventricular (LV) segmentation in short-axis cardiac cine MR images.
Zakia Khatun, Nur Adhianti, Valeria Abramova
Automatic MRI Cardiac Segmentation in Short Axis for Left Ventricular Endocardium

Face Recognition using Principal Component Analysis

In this project, a simple face recognition system was designed based on a very small dataset of the training images. The two main steps of this project include data normalization and face recognition. After the normalization of the training data set, principle component analysis was incorporated. A simple Graphical User Interface was designed.
Zakia Khatun, Inder Pal
Face Recognition using Principal Component Analysis

Automated Inspection at Soft Drink Bottling Plant

The main goal of this project was to develop a visual inspection system. The following seven fault conditions were aimed to be detected - Bottle under filled, Bottle over filled, Bottle has label missing, Bottle has label but label printing failed, Bottle label is not straight, Bottle cap is missing, and Bottle is deformed in some way.
Nur Adhianti, Zakia Khatun, Roa’a Khaled
Automated Inspection at Soft Drink Bottling Plant

Gesture Controlled Pick & Place Robot

In this project, a gesture-controlled pick-and-place robot was proposed with a drive system. This design is wirelessly controllable using a hand module. The main purpose was to aid physically disabled people to manipulate an object as they wish. Moreover, it will be useful in industrial work as it has the option of mobility, a trait that conventional pick-and-place robots do not have.
Zakia Khatun, Islam Alif, Hasan Shimul, Hossain Md. Delower
Gesture Controlled Pick & Place Robot

Accomplish­ments

PhD Grant, EU H2020-MSCA-ITN-EJD Program

European Union Nov 2021
This PhD project is one of 15 positions within the P4-FIT project which was funded by the European Uni­on’s Ho­ri­zon 2020 research and innovation pro­gramme under the Marie Skłodowska-Curie grant agree­ment No 955685.

Erasmus Mundus Joint Master Degree Scholarship in Medical Imaging and Applications (MAIA)

European Union Sep 2018 – Sep 2020
This two-year master’s program in Medical Imaging and Applications, fully funded by the European Union, equips students with expertise in medical image analysis and the development of Computer-Aided Diagnosis (CAD) systems. The program addresses the growing need for professionals skilled in artificial intelligence, machine learning, image processing, and other key technologies that are transforming healthcare through more accurate and early diagnoses.

Dean’s Award for Undergraduate Final Year Project

American International University-Bangladesh (AIUB) Dec 2017
It was awarded for achieving 7th place out of 155 projects/theses during the 2017-2018 academic year.

Merit-Based Scholarship in Electrical & Electronic Engineering (EEE)

American International University-Bangladesh (AIUB) Jun 2014 – Feb 2018
This bachelor’s degree is a four-year program focused on the practical applications of electricity in all its forms, including those within the field of electronics. The scholarship was awarded in recognition of outstanding academic performance throughout the duration of the program.

Dean’s Honour

American International University-Bangladesh (AIUB) Jun 2014
This honor was awarded for maintaining academic excellence throughout each semester.

Co-curricular activities

 
 
 
 
 

Guest Speaker

IEEE AIUB Student Branch

Aug 2019 – Aug 2019 Dhaka, Bangladesh
Guest Speaker at the Seminar on “Road to Erasmus+ Scholarship”, organized by IEEE AIUB Student Branch at American Internation University-Bangladesh.
 
 
 
 
 

Member of Event Coordination Committee

IEEE Region-10 Student Professional Awareness Venture (SPAVe), supported by IEEE USA

Dec 2016 – Dec 2016 Dhaka
SPAVe stands for Student Professional Awareness Venture. SPAVe took place for the first time in the history of IEEE Bangladesh Section. This venture was supported by IEEE, IEEE USA, IEEE R10, IEEE Bangladesh Section.
 
 
 
 
 

Campus Ambassador

IEEE Bangladesh Section SYW Congress-2016

Oct 2016 – Nov 2016 Dhaka
The largest annual event of IEEE Bangladesh Section.
 
 
 
 
 

Volunteer

AIUB Engineering Jubilation-2016

Jun 2016 – Jul 2016 Dhaka
 
 
 
 
 

Vice Chairperson

IEEE AIUB Student Branch Women in Engineering Affinity Group (WIE)

Feb 2016 – Jun 2017 Dhaka

Contact