IEEE Transactions on Image Processing, 27(5): 2433-2446, 2018.
Wiley EEEE Book Chapter doi.org/10.1002/047134608X.W8315
A. Rashno, D. D. Koozekanani, P. M. Drayna, B. Nazari, S. Sadri, H. Rabbani, K. K. Parhi, "Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms," IEEE Transactions on Biomedical Engineering, vol. 65, no. 5, pp. 989-1001, May 2018. A. Rashno, B. Nazari, D. D. Koozekanani, P. M. Drayna, S. Sadri, H. Rabbani, K. K. Parhi, "Fully-automated segmentation of fluid regions in exudative age-related macular degeneration subjects: Kernel graph cut in neutrosophic domain," PLoS ONE 12(10): e0186949. M. Esmaeili, A. Mehri, H. Rabbani, F. Hajizadeh, “Three-dimensional segmentation of retinal cysts from spectral-domain optical coherence tomography images by the use of three-dimensional curvelet based k-SVD ,” Journal of Medical Signals & Sensors, vol. 6, no. 3, pp. 166–171, 2016.
The datasets (24 768*768*x FA videos and late FA images in DME eyes) and manual and automated markings used in the following paper can be downloaded from HERE.
This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons.
This folder contains bone marrow microscopic images. These images are categorized into two groups: Normal Plasma Cells and Myeloma Cells.
We have collected retinal image of 70 patients of different diabetic retinopathy stages including 30 normal data and 40 abnormal data in different stages.
45 24-bit 3264*2448 microscopic images taken from bone marrow samples including leshman bodies.
This dataset contains 260 CT and 202 MR images in DICOM format.
Publicly available database of both fundus fluorescein fngiogram photographs and corresponding color fundus images of 30 healthy persons and 30 patients with diabetic retinopathy.
A set of 2D .mat corneal OCT images of 15 subjects. For example subject#1 includes 41 240×748 B-scans taken from Heidelberg OCT imaging device.
This folder includes 25 colour fundus images of healthy persons and 35 colour fundus images of patients with diabetic retinopathy used for automatic curvelet-based detection of Foveal Avascular Zone (FAZ).
A set of eye images consisting of 22 pairs of images (17 macular and 5 prepapillary), from random patients, each pair acquired from eyes with a variety of retinal diseases. Each image pair includes a colour fundus image and one OCT image acquired with Topcon 3D OCT-1000 instrument. OCT images contain images of 650 different slices with a size of 650 × 512 × 128 voxels and a voxel resolution of 3.125 µm × 3.125 µm × 7 µm.
A dataset for Glomeruli detection was collected with the contribution of MISP Research Center and Department of Pathology at IUMS
This dataset is acquired at Noor Eye Hospital in Tehran and is consisting of 50 normal, 48 dry AMD, and 50 DME OCTs.
7 healthy and 7 glaucoma data captured by Heidelberg Spectralis used to demonstrate the efficacy of a new imaging biomarker namely Volumetric Cup-to-Disc Ratio (VCDR) for diagnosis of ocular diseases such as Glaucoma.