7 papers:
SAC-2015-MottaMSMPC #3d #image #re-engineering- All-in-focus imaging technique used to improve 3D retinal fundus image reconstruction (DM, LdM, ACdS, RM, AP, LAVdC), pp. 26–31.
ICPR-2014-DingM #approach #detection #image- An Accurate Approach for Microaneurysm Detection in Digital Fundus Images (SD, WM), pp. 1846–1851.
- ICPR-2012-WongLTYLTCW #automation #detection #image
- Detecting the optic cup excavation in retinal fundus images by automatic detection of vessel kinking (DWKW, JL, NMT, FY, BHL, YCT, CYlC, TYW), pp. 73–76.
- ICPR-2012-XuLCYTWCTW #classification #image #locality #performance
- Efficient optic cup localization based on superpixel classification for glaucoma diagnosis in digital fundus images (YX, JL, JC, FY, NMT, DWKW, CYC, YCT, TYW), pp. 49–52.
- SAC-2010-WelferSM #approach #detection #image
- A morphologic three-stage approach for detecting exudates in color eye fundus images (DW, JS, DRM), pp. 964–968.
- ICPR-v1-2006-TangLFG #automation #image #segmentation
- Automatic Segmentation of the Papilla in a Fundus Image Based on the C-V Model and a Shape Restraint (YT, XL, AvF, GG), pp. 183–186.
- ICPR-v4-2000-DeguchiNH #3d #image #multi #re-engineering
- 3D Fundus Pattern Reconstruction and Display from Multiple Fundus Images (KD, JN, HH), pp. 4094–4097.
