Dr. Tiziano Ronchetti
Dr. Tiziano Ronchetti Dozent
School of Engineering and Computer Science
Abt MNG Allgemeinbildung
BsC in Microtechnology: Analyse 1&2
BSc in Electrical Engineering and Information Technology: Analyse 2
BsC in Informatics: Discrete Mathematics 1&2, Analysis and Linear Algebra
My research work focuses on developing an automatic algorithms to detect subtle changes in the area of the human choroid. This is relevant because choroidal thickness changes could be among the first signs of, for example, myopia or glaucoma and must therefore be monitored.
Segmenting the choroid is often challenging because of low contrast, loss of signal and the presence of artifacts. In particular, in-vivo imaging of the choroid-sclera interface (CSI), the border separating the choroid from the sclera, is often prone to such image degradations. My research work focuses on new approaches (based on image registration and/or deep learning) which allow to overcome the difficulties mentioned above.
Since a ground truth for comparison with the in-vivo situation is lacking, my research work also focuses on developing appropriate statistical validation procedures to accurately evaluate the detection-performance of algorithms.
- since 2007: Lectures in Mathematics, Bern University of Applied Sciences (BUAS) in Biel, Bern and Burgdorf
- since 2003: Teaching in Mathematics, Berufsmaturitätsschule BMS/GIBB, Bern
- 1998-2003: Lectures in Mathematics, Ingenieurschule ISBE-HTA, Bern
- 1993-1998: High school teaching in Mathematics, Gymnasium Langenthal, Neufeld Gymnasium and Freies Gymnasium Bern
- 2015-2020: PhD (Dr. sc. med) in Biomedical Engineering, CIAN/DBE, Medical Faculty, University of Basel
- 1997-2001: High school teacher diploma in Mathematics and Chemistry, Höheres Lehramt, University of Bern
- 1992-1997: Master of Science (Lic. phil.-nat.) in Mathematics (major) and Chemistry (minor), University of Bern
- 1989-1992: Matura (type B), Literaturgymnasium, Liceo Lugano 1, Lugano
- Specialization in image processing with MATLAB, Mathworks (2014)
PhD Research Project: SNSF Project 320030-146021 “Characterisation of choroidal changes in chil- dren and its temporal response to optical defocus”, an international cooperation between the University of Applied Sciences of Biel (project center), the Depart- ment of Biomedical Engineering of the University of Basel (academic supervision), Department of Ophthalmology (clinical support), Guangzhou and Hong Kong (clini- cal partners). The persons responsible are Prof. Christoph Meier (head of the HuCE-OptoLab of the Bern University of Applied Sciences in Biel) and the principal investigator Dr. Boris Považay.
Tiziano Ronchetti, "Detecting Early Choroidal Changes Using Piecewise Rigid Image Registration and Eye-Shape Adherent Regularization", Doctoral Thesis, University of Basel, 2020.
PhD committee: Prof. Dr. Selim Orgül (Primary Advisor), Prof. Dr. Philippe C. Cattin (Secondary Advisor), Prof. Dr. Dr. Daniel Barthelmes (External Expert), Dr. Christoph Jud, Dr. Boris Považay and Dr. Peter Maloca (Further Experts).
T. Ronchetti, P. Maloca, E. R. de Carvalho, T. F. Heeren, K. Balaskas, A. Tufail, C. Egan, M. Okada, S. Orgül, C. Jud, and P. C. Cattin, “Feasibility study of subfoveal choroidal thickness changes in spectral-domain optical coherence tomography measurements of macular telangiectasia type 2,” in Computational Pathology and Ophthalmic Medical Image Analysis. Springer, 2018, pp. 303–309.
T. Ronchetti, P. Maloca, C. Jud, C. Meier, S. Orgül, H. P. Scholl, B. Považay, and P. C. Cattin, “Detecting early choroidal changes using piecewise rigid image registration and eye-shape adherent regularization,” in Fetal, Infant and Ophthalmic Medical Image Analysis. Springer, 2017, pp. 92–100.
T. Ronchetti, P. Maloca, C. Meier, S. Orgül,C.Jud, P. Hasler, B. Považay,and P.C. Cattin, “Intensity-based choroidal registration using regularized block matching,” in Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop (OMIA), 2016, pp. 33–40.
Ali Sahandabadi A web application for manual expert segmentation of retinal and choroidal layers 2019
Emeline Lieberherr and Rayner Oswaldo Daeppen A deep learning framework to generate synthetic ground truth for evaluation of automated detection of intraretinal thickness changes 2021
Fabian Jegerlehner A pattern recognition C++ algorithm for retinal and/or choroidal thickness changes detection 2021
Jonathan Hector An appropriate graphic user interface for ophthalmic medical image analysis 2021