Leuven-Haifa High-Resolution Fundus Image Dataset for Retinal Blood Vessel Segmentation and Glaucoma Diagnosis.
Jan Van EijgenJonathan FhimaMarie-Isaline Billen Moulin-RomséeJoachim A BeharEirini ChristinakiIngeborg StalmansPublished in: Scientific data (2024)
The Leuven-Haifa dataset contains 240 disc-centered fundus images of 224 unique patients (75 patients with normal tension glaucoma, 63 patients with high tension glaucoma, 30 patients with other eye diseases and 56 healthy controls) from the University Hospitals of Leuven. The arterioles and venules of these images were both annotated by master students in medicine and corrected by a senior annotator. All senior segmentation corrections are provided as well as the junior segmentations of the test set. An open-source toolbox for the parametrization of segmentations was developed. Diagnosis, age, sex, vascular parameters as well as a quality score are provided as metadata. Potential reuse is envisioned as the development or external validation of blood vessels segmentation algorithms or study of the vasculature in glaucoma and the development of glaucoma diagnosis algorithms. The dataset is available on the KU Leuven Research Data Repository (RDR).
Keyphrases
- deep learning
- convolutional neural network
- optic nerve
- optical coherence tomography
- machine learning
- artificial intelligence
- diabetic retinopathy
- high school
- high resolution
- cataract surgery
- end stage renal disease
- chronic kidney disease
- ejection fraction
- healthcare
- newly diagnosed
- prognostic factors
- wastewater treatment
- quality improvement