FAIR data and methods

We embrace the Open Science movement and therefore aim to make as much of our data and method freely available. However, as most of our data contain potentially identifying information, they cannot be made publicly available. These data can, however, be shared with scientists after signing of a data transfer agreement to ensure the subject’s privacy. Please contact our data access committee for more information.

Reuse our methods

• Correction Method for Optical Scaling of Fundoscopy Images: Development, Validation, and First Implementation.
  Investigative Opthalmology & Visual Science (2024), doi: 10.1167/iovs.65.1.43 
  Open methods: The methodology for calibrating fundus photographs is made available on GitHub.
• Patient‐specific mapping of fundus photographs to three‐dimensional ocular imaging.
  Medical Physics (2024), doi: 10.1002/mp.17576 
  Open methods: The full methodology to map fundus images to ocular MR-images has been made available through the ZOSpy repository.
• ZOSPy: optical ray tracing in Python through OpticStudio.
  Journal of Open Source Software (2024), doi: 10.21105/joss.05756 
  Open methods: We published ZOSPy open-source on GitHub, so you cannot only use it, but also contribute to it.
• Automatic Three-Dimensional Magnetic Resonance-based measurements of tumour prominence and basal diameter for treatment planning of uveal melanoma.
  Physics and Imaging in Radiation Oncology (2022), doi: 10.1016/j.phro.2022.11.001 
  Open methods: The Python code to calculate the tumour prominence and basal diameter can be found in Appendix C.
  Open data: The MRI and ultrasound measurements of all individual patients are available in Appendix D.
• The Value of Static Perimetry in the Diagnosis and Follow-up of Negative Dysphotopsia.
  Optometry and Vision Science (2022), doi: 10.1097/opx.0000000000001918 
  Open methods: The Python code to digitize the visual field data is shared through GitHub.
• T2 relaxation‐time mapping in healthy and diseased skeletal muscle using extended phase graph algorithms.
  Magnetic Resonance in Medicine (2020), doi: 10.1002/mrm.28290 
  Open methods: The multi-component EPG fitting algorithm is provided for Mathematica, Matlab and Python.
• MRI of Uveal Melanoma.
  Cancers (2019), doi: 10.3390/cancers11030377 
  Open methods: An extensive description of the MRI protocol for intra-ocular pathology can be found here.

Reuse our data

• Diagnosing myasthenia gravis using orthoptic measurements: assessing extraocular muscle fatiguability.
  Journal of Neurology, Neurosurgery & Psychiatry (2023), doi: 10.1136/jnnp-2022-329859 
  Open data: The orthoptic measurements of all patients are made available for reuse.
• Eye Muscle MRI in Myasthenia Gravis and Other Neuromuscular Disorders.
  Journal of Neuromuscular Diseases (2023), doi: 10.3233/jnd-230023 
  Open data: The quantitative MRI data of the extra-ocular muscles are provided as supplementary materials.
• MR-based follow-up after brachytherapy and proton beam therapy in uveal melanoma.
  Neuroradiology (2023), doi: 10.1007/s00234-023-03166-1 
  Open data: Both the MRI and ultrasound measurements of all individual patients are made available.
• Automatic Three-Dimensional Magnetic Resonance-based measurements of tumour prominence and basal diameter for treatment planning of uveal melanoma.
  Physics and Imaging in Radiation Oncology (2022), doi: 10.1016/j.phro.2022.11.001 
  Open methods: The Python code to calculate the tumour prominence and basal diameter can be found in Appendix C.
  Open data: The MRI and ultrasound measurements of all individual patients are available in Appendix D.
• Effect of anatomical differences and intraocular lens design on negative dysphotopsia.
  Journal of Cataract & Refractive Surgery (2022), doi: 10.1097/j.jcrs.0000000000001054 
  Open data: The resulting ND and control eye model, both with a biconvex IOL, are made available through ZOSPy.
• Eye-specific quantitative dynamic contrast-enhanced MRI analysis for patients with intraocular masses.
  Magnetic Resonance Materials in Physics, Biology and Medicine (2022), doi: 10.1007/s10334-021-00961-w 
  Open data: The perfusion metrics and T1 values of individual patients are made available as supplementary materials.
• Magnetic resonance imaging reveals possible cause of diplopia after Baerveldt glaucoma implantation.
  PLoS ONE (2022), doi: 10.1371/journal.pone.0276527 
  Open data: The MRI metrics (eg. bleb volume) and ophthalmic data (eg. ocular motility restrictions) of all patient can be found in the supplementary materials.