Fine-tuning of Advanced Vision Language Models for Peripheral Blood Cell Image Analysis

Abstract

This thesis investigates the application of vision-language models (VLMs) for automated morphological analysis of peripheral blood cells. While manual microscopic analysis remains the gold standard in hematological diagnosis, it is time-consuming and subject to inter-observer variability. This work aims to develop and evaluate fine-tuned VLMs capable of generating accurate morphological descriptions of blood cells from microscopic images.