Dr. Florian Schwarzhans

AI Researcher at MIAAI at Danube Private University



Florian Schwarzhans holds an MSc degree in Medical Informatics from the Medical University of Vienna.

He has a background in informatics with a focus on programming using C, C++, MatLab and Python, as well as a background in electronics specializing in biomedical engineering.


His research interests include medical image processing with a special focus on automatic graph-based segmentation algorithms, deep learning methods for both image classification and segmentation, as well as development and implementation of parallel algorithms for medical image processing and analysis using CUDA.


He has developed real-time retinal tracking software for a prototype PS-OCT system and software for fast parallel reconstruction of OCT volumes from raw data via the GPU, which is actively being used in multiple OCT systems.



Key publications


Automatic retinal nerve fiber bundle tracing based on large field of view polarization sensitive OCT data.

Schwarzhans F, Desissaire S, Steiner S, Pircher M, Hitzenberger CK, Resch H, Vass C, Fischer G.

Biomedical Optics Express. 2022 Jan 1;13(1):65-81.


Temporal phase evolution OCT for measurement of tissue deformation in the human retina in-vivo.

Desissaire S, Schwarzhans F, Steiner S, Vass C, Fischer G, Pircher M, Hitzenberger CK.

Biomedical Optics Express. 2021 Nov 1;12(11):7092-112.


Generating large field of view en-face projection images from intra-acquisition motion compensated volumetric optical coherence tomography data.

Schwarzhans F, Desissaire S, Steiner S, Pircher M, Hitzenberger CK, Resch H, Vass C, Fischer G. Biomedical Optics Express. 2020 Dec 1;11(12):6881-904.


Analysis of longitudinal sections of retinal vessels using doppler oct.

Desissaire S, Schwarzhans F, Salas M, Wartak A, Fischer G, Vass C, Pircher M, Hitzenberger CK.

Biomedical Optics Express. 2020 Apr 1;11(4):1772-89.


Compensation of retinal nerve fibre layer thickness as assessed using optical coherence tomography based on anatomical confounders.

Chua J, Schwarzhans F, Nguyen DQ, Tham YC, Sia JT, Lim C, Mathijia S, Cheung C, Tin A, Fischer G, Cheng CY.

British Journal of Ophthalmology. 2020 Feb 1;104(2):282-90.

Distinguishing keratoconic eyes and healthy eyes using ultrahigh-resolution optical coherence tomography–based corneal epithelium thickness mapping.

Pircher N, Schwarzhans F, Holzer S, Lammer J, Schmidl D, Bata AM, Werkmeister RM, Seidel G, Garhöfer G, Gschließer A, Schmetterer L.

American journal of ophthalmology. 2018 May 1;189:47-54.