Hyunbin An. (2025). Optimized Red Blood Cell Segmentation in Holographic Imaging through Integration of Self-Supervised Learning and Diffusion Models. doi: 10.22677/THESIS.200000828659
Type
Thesis
Description
Red blood cells, Digital Holography, Deep Learning, Diffusion Model, Self-Supervised learning
Table Of Contents
I. INTRODUCTION 1 II. METHODOLOGY 6 2.1 Data Acquisition 6 2.2 Digital Holographic Microscopy 7 2.3 Synthetic RBC Image Generation Using Diffusion Model 9 2.4 Self-Supervised Learning for Pretrained Model 13 2.5 Watershed Algorithm 16 2.6 Evaluation Metrics 17 III. EXPERIMENTAL SETUPS 18 3.1 Datasets 18 3.2 Implementation Setups 18 IV. RESULTS 20 4.1 Generated Synthetic RBC Data 20 4.2 Semantic Segmentation 21 4.3 Effectiveness of Losses in Self-Supervised Learning 24 4.4 Experiments on the Effect of SSCRL in Limited Training Data 25 4.5 Phenotypical Assessment of Red Blood Cells 26 V. CONCLUSION 27
