Maryam Viqar: Advancing vein analysis and image reconstruction with SS-OCT and deep learning

In her doctoral dissertation, MSc (Tech.) Maryam Viqar who served as an Early-Stage Researcher in the Plenoptima – European Training Network, explores the integrated application of swept-source optical coherence tomography (SS-OCT) and deep learning (DL) to improve vein analysis and image reconstruction. The research employs advanced DL models to extract detailed vascular information through vein segmentation and wall-thickness estimation from SS-OCT data. Additionally, the work proposes novel methods for leveraging raw interferometric OCT signals, enabling faster and more efficient volumetric reconstruction for a wide range of biomedical applications. The methods developed throughout this thesis have shown high efficiency and performance, thereby advancing the state-of-the-art works in the realm of OCT.

The doctoral dissertation of MSc Maryam Viqar in the field of plenoptic imaging, titled “Deep Learning Models for Vascular Image Reconstruction and Analysis in Swept-Source Optical Coherence Tomography”, will be publicly examined at the Institute of Optical Materials and Technologies (IOMT), Bulgarian Academy of Sciences, on Friday 9 January at 10:30 o’clock (Europe/Helsinki). The venue is Conference room, on Acad. G. Bontchev Street, Sofia, Bulgaria.

The pre-examiners were Prof. Uma Maheswari Rajagopalan, Shibaura Institute of Technology, Japan and Assoc. Prof. Hsiang-Chieh Lee, National Taiwan University, Taiwan. The opponent will be Assoc. Prof. Ivan Panayotov Bodurov, University of Plovdiv "Paisii Hilendarski", Bulgaria. The president will be Prof. Vera Marinova, IOMT, Bulgaria.