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6.9.5 Other (59)
Showing records 1 to 25
Display all abstracts in classification 6.9.5 Other
Search within classification 6.9.5 Other78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Fu H
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605
78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
An G
Journal of healthcare engineering 2018; 2018: 6874765
78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Duan XJ
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826
78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Devalla SK
Biomedical optics express 2018; 9: 3244-3265
78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Hagiwara Y
Computer Methods and Programs in Biomedicine 2018; 165: 1-12
78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Kipli K
Computational and mathematical methods in medicine 2018; 2018: 4019538
78268 Deep learning in ophthalmology: a review
Grewal PS
Canadian Journal of Ophthalmology 2018; 53: 309-313
78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Tanito M
Acta Ophthalmologica 2018; 0:
78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Cheng J
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605
78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Omodaka K
Journal of healthcare engineering 2018; 2018: 6874765
78268 Deep learning in ophthalmology: a review
Oloumi F
Canadian Journal of Ophthalmology 2018; 53: 309-313
78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Jefferys JL
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826
78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Nitta K
Acta Ophthalmologica 2018; 0:
78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Hoque ME
Computational and mathematical methods in medicine 2018; 2018: 4019538
78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Koh JEW
Computer Methods and Programs in Biomedicine 2018; 165: 1-12
78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Renukanand PK
Biomedical optics express 2018; 9: 3244-3265
78268 Deep learning in ophthalmology: a review
Rubin U
Canadian Journal of Ophthalmology 2018; 53: 309-313
78133 Validation of formula-predicted glaucomatous optic disc appearances: the Glaucoma Stereo Analysis Study
Katai M
Acta Ophthalmologica 2018; 0:
78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Lim LT
Computational and mathematical methods in medicine 2018; 2018: 4019538
78310 Computer-aided diagnosis of glaucoma using fundus images: A review
Tan JH
Computer Methods and Programs in Biomedicine 2018; 165: 1-12
78056 Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Xu Y
IEEE Transactions on Medical Imaging 2018; 37: 1597-1605
78080 DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images
Sreedhar BK
Biomedical optics express 2018; 9: 3244-3265
78125 Comparison of Machine-Learning Classification Models for Glaucoma Management
Tsuda S
Journal of healthcare engineering 2018; 2018: 6874765
78241 Evaluation of Automated Segmentation Algorithms for Optic Nerve Head Structures in Optical Coherence Tomography Images
Quigley HA
Investigative Ophthalmology and Visual Science 2018; 59: 3816-3826
78230 A Review on the Extraction of Quantitative Retinal Microvascular Image Feature
Mahmood MH
Computational and mathematical methods in medicine 2018; 2018: 4019538
