Ahmed Lotfi Alqnatri


As a PhD student at FIIT STU, I am researching innovative methods for using computer vision in medical settings, specifically focusing on the analysis of histological data.I am eager to investigate advanced technologies such as Vision Transformer to expand the limits of our knowledge on this subject. When I’m not consumed by research, I enjoy experimenting with new technologies as a hobby.


In my research, I am investigating the benefits of integrating Vision Transformer (ViT) and the LORA approach to improve histopathology data comprehension. By combining ViT’s visual processing capabilities with LORA’s benefits of fine-tuning large general models to do a specific task.  I aim to develop a robust system capable of extracting precise cellular data essential for accurate illness diagnosis. This combination of advanced methods has the potential to revolutionize our medical interventions, possibly leading to more efficient treatments based on a better understanding of cellular disease.


DP: Interpretability and explainability of deep learning systems in the domain of medical image data processing.

Abstract: Early breast cancer detection and treatment is one of the most crucial aspects of patient health, 
particularly in developing nations. Due to the unequal distribution of resources, some fields of medical
research receive more focus than others; therefore, in recent years, there has been a significant increase
in the use of computer vision to assist with such tasks due to the results it produces. We decided to do
our research in this area with the goal of designing a custom method to perform cancer. Performing
classification and segmentation tasks on breast ultrasound images. Implementing modern artificial
intelligence techniques—particularly deep neural networks and placing a strong emphasis on interpreting
the model outputs were key to achieving that. To help improve the design and increase the robustness of the
models themselves, we used visualization methods and a comprehensive evaluation protocol.


  • Intelligent Data Analysis (IAU): Teaching Assistant
  • Object-Oriented Programming (OOP): Teaching Assistant