WEB OF SCIENCE
SCOPUS
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 문인규 | - |
| dc.contributor.author | Hyunbin An | - |
| dc.date.accessioned | 2025-02-28T21:01:42Z | - |
| dc.date.available | 2025-02-28T21:01:42Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.11750/58017 | - |
| dc.identifier.uri | http://dgist.dcollection.net/common/orgView/200000828659 | - |
| dc.description | Red blood cells, Digital Holography, Deep Learning, Diffusion Model, Self-Supervised learning | - |
| dc.description.tableofcontents | 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 |
- |
| dc.format.extent | 32 | - |
| dc.language | eng | - |
| dc.publisher | DGIST | - |
| dc.title | Optimized Red Blood Cell Segmentation in Holographic Imaging through Integration of Self-Supervised Learning and Diffusion Models | - |
| dc.type | Thesis | - |
| dc.identifier.doi | 10.22677/THESIS.200000828659 | - |
| dc.description.degree | Master | - |
| dc.contributor.department | Department of Robotics and Mechatronics Engineering | - |
| dc.identifier.bibliographicCitation | 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 | - |
| dc.contributor.coadvisor | Youhyun Kim | - |
| dc.date.awarded | 2025-02-01 | - |
| dc.publisher.location | Daegu | - |
| dc.description.database | dCollection | - |
| dc.citation | XT.RM 안94 202502 | - |
| dc.date.accepted | 2025-01-20 | - |
| dc.contributor.alternativeDepartment | 로봇및기계전자공학과 | - |
| dc.subject.keyword | Red blood cells, Digital Holography, Deep Learning, Diffusion Model, Self-Supervised learning | - |
| dc.contributor.affiliatedAuthor | Hyunbin An | - |
| dc.contributor.affiliatedAuthor | Inkyu Moon | - |
| dc.contributor.affiliatedAuthor | Youhyun Kim | - |
| dc.contributor.alternativeName | 안현빈 | - |
| dc.contributor.alternativeName | Inkyu Moon | - |
| dc.contributor.alternativeName | 김유현 | - |
| dc.rights.embargoReleaseDate | 2030-02-28 | - |
