FAIR Data and Reusable 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

• A Novel MRI-Based Approach to Peripheral Refraction and Prediction of Myopia Progression

  Kneepkens, Vught, Polling, Klaver, Tideman and Beenakker
  American Journal of Ophthalmology (2025), doi: 10.1016/j.ajo.2025.06.013 
  Methods: The methods to perform peripheral ray-tracing simulations have been made available through the ZOSpy repository.
• Patient‐specific mapping of fundus photographs to three‐dimensional ocular imaging

  Haasjes, Vu and Beenakker
  Medical Physics (2025), doi: 10.1002/mp.17576 
  Methods: The full methodology to map fundus images to ocular MR-images has been made available through the ZOSpy repository.
• Correction Method for Optical Scaling of Fundoscopy Images: Development, Validation, and First Implementation

  Pors, Haasjes, Vught, Hoes, Luyten, Rijn, Vu, Rasch, Horeweg and Beenakker
  Investigative Opthalmology & Visual Science (2024), doi: 10.1167/iovs.65.1.43 
  Methods: The methodology for calibrating fundus photographs is made available on GitHub.
• ZOSPy: optical ray tracing in Python through OpticStudio

  Vught, Haasjes and Beenakker
  Journal of Open Source Software (2024), doi: 10.21105/joss.05756 
  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

  Klaassen, Jaarsma-Coes, Verbist, Vu, Marinkovic, Rasch, Luyten and Beenakker
  Physics and Imaging in Radiation Oncology (2022), doi: 10.1016/j.phro.2022.11.001 
  Methods: The Python code to calculate the tumour prominence and basal diameter can be found in Appendix C.
• The Value of Static Perimetry in the Diagnosis and Follow-up of Negative Dysphotopsia

  Rozendal, Vught, Luyten and Beenakker
  Optometry and Vision Science (2022), doi: 10.1097/opx.0000000000001918 
  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

  Keene, Beenakker, Hooijmans, Naarding, Niks, Otto, Pol, Tannemaat, Kan and Froeling
  Magnetic Resonance in Medicine (2020), doi: 10.1002/mrm.28290 
  Methods: The multi-component EPG fitting algorithm is provided for Mathematica, Matlab and Python.
• MRI of Uveal Melanoma

  Ferreira, Fonk, Jaarsma-Coes, Haren, Marinkovic and Beenakker
  Cancers (2019), doi: 10.3390/cancers11030377 
  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

  Keene, Nie, Brink, Notting, Verschuuren, Kan, Beenakker and Tannemaat
  Journal of Neurology, Neurosurgery & Psychiatry (2023), doi: 10.1136/jnnp-2022-329859 
  Data: The orthoptic measurements of all patients are made available for reuse.
• Eye Muscle MRI in Myasthenia Gravis and Other Neuromuscular Disorders

  Keene, Notting, Verschuuren, Voermans, Keizer, Beenakker, Tannemaat and Kan
  Journal of Neuromuscular Diseases (2023), doi: 10.3233/jnd-230023 
  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

  Tang, Ferreira, Marinkovic, Jaarsma-Coes, Klaassen, Vu, Creutzberg, Rodrigues, Horeweg, Klaver, Rasch, Luyten and Beenakker
  Neuroradiology (2023), doi: 10.1007/s00234-023-03166-1 
  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

  Klaassen, Jaarsma-Coes, Verbist, Vu, Marinkovic, Rasch, Luyten and Beenakker
  Physics and Imaging in Radiation Oncology (2022), doi: 10.1016/j.phro.2022.11.001 
  Data: The MRI and ultrasound measurements of all individual patients are available in Appendix D.
  Methods: The Python code to calculate the tumour prominence and basal diameter can be found in Appendix C.
• Effect of anatomical differences and intraocular lens design on negative dysphotopsia

  Vught, Que, Luyten and Beenakker
  Journal of Cataract & Refractive Surgery (2022), doi: 10.1097/j.jcrs.0000000000001054 
  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

  Jaarsma-Coes, Ferreira, Houdt, Heide, Luyten and Beenakker
  Magnetic Resonance Materials in Physics, Biology and Medicine (2022), doi: 10.1007/s10334-021-00961-w 
  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

  Islamaj, Vught, Jordaan-Kuip, Vermeer, Ferreira, Waard, Lemij and Beenakker
  PLoS ONE (2022), doi: 10.1371/journal.pone.0276527 
  Data: The MRI metrics (eg. bleb volume) and ophthalmic data (eg. ocular motility restrictions) of all patient can be found in the supplementary materials.