PMID- 31600644
OWN - NLM
STAT- MEDLINE
DCOM- 20200505
LR  - 20200505
IS  - 1872-7565 (Electronic)
IS  - 0169-2607 (Linking)
VI  - 182
DP  - 2019 Dec
TI  - Geographic atrophy segmentation in SD-OCT images using synthesized fundus 
      autofluorescence imaging.
PG  - 105101
LID - S0169-2607(19)30905-8 [pii]
LID - 10.1016/j.cmpb.2019.105101 [doi]
AB  - BACKGROUND AND OBJECTIVE: Accurate assessment of geographic atrophy (GA) is 
      critical for diagnosis and therapy of non-exudative age-related macular 
      degeneration (AMD). Herein, we propose a novel GA segmentation framework for 
      spectral-domain optical coherence tomography (SD-OCT) images that employs 
      synthesized fundus autofluorescence (FAF) images. METHODS: An en-face OCT image 
      is created via the restricted sub-volume projection of three-dimensional OCT 
      data. A GA region-aware conditional generative adversarial network is employed to 
      generate a plausible FAF image from the en-face OCT image. The network balances 
      the consistency between the entire synthesize FAF image and the lesion. We use a 
      fully convolutional deep network architecture to segment the GA region using the 
      multimodal images, where the features of the en-face OCT and synthesized FAF 
      images are fused on the front-end of the network. RESULTS: Experimental results 
      for 56 SD-OCT scans with GA indicate that our synthesis algorithm can generate 
      high-quality synthesized FAF images and that the proposed segmentation network 
      achieves a dice similarity coefficient, an overlap ratio, and an absolute area 
      difference of 87.2%, 77.9%, and 11.0%, respectively. CONCLUSION: We report an 
      automatic GA segmentation method utilizing synthesized FAF images. SIGNIFICANCE: 
      Our method is effective for multimodal segmentation of the GA region and can 
      improve AMD treatment.
CI  - Copyright (c) 2019. Published by Elsevier B.V.
FAU - Wu, Menglin
AU  - Wu M
AD  - School of Computer Science and Technology, Nanjing Tech University, Nanjing, 
      China.
FAU - Cai, Xinxin
AU  - Cai X
AD  - School of Computer Science and Technology, Nanjing Tech University, Nanjing, 
      China.
FAU - Chen, Qiang
AU  - Chen Q
AD  - School of Computer Science and Engineering, Nanjing University of Science and 
      Technology, Nanjing, China.
FAU - Ji, Zexuan
AU  - Ji Z
AD  - School of Computer Science and Engineering, Nanjing University of Science and 
      Technology, Nanjing, China.
FAU - Niu, Sijie
AU  - Niu S
AD  - School of Information Science and Engineering, University of Jinan, Jinan, China.
FAU - Leng, Theodore
AU  - Leng T
AD  - Byers Eye Institute at Stanford, Stanford University School of Medicine, Palo 
      Alto, CA, USA.
FAU - Rubin, Daniel L
AU  - Rubin DL
AD  - Department of Radiology and Medicine (Biomedical Informatics Research) and 
      Ophthalmology, Stanford University School of Medicine, Stanford, CA 94305, USA.
FAU - Park, Hyunjin
AU  - Park H
AD  - School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, 
      South Korea; Center for Neuroscience Imaging Research, Institute of Basic 
      Science, Suwon, South Korea. Electronic address: hyunjinp@skku.edu.
LA  - eng
PT  - Journal Article
DEP - 20190928
PL  - Ireland
TA  - Comput Methods Programs Biomed
JT  - Computer methods and programs in biomedicine
JID - 8506513
SB  - IM
MH  - Automation
MH  - *Fundus Oculi
MH  - Geographic Atrophy/*diagnostic imaging
MH  - Humans
MH  - Optical Imaging/*methods
MH  - Tomography, Optical Coherence/*methods
OTO - NOTNLM
OT  - Biomedical image segmentation
OT  - Geographic atrophy
OT  - Image synthesis
OT  - Optical coherence tomography
OT  - Retinal image analysis
EDAT- 2019/10/11 06:00
MHDA- 2020/05/06 06:00
CRDT- 2019/10/11 06:00
PHST- 2019/06/11 00:00 [received]
PHST- 2019/09/04 00:00 [revised]
PHST- 2019/09/27 00:00 [accepted]
PHST- 2019/10/11 06:00 [pubmed]
PHST- 2020/05/06 06:00 [medline]
PHST- 2019/10/11 06:00 [entrez]
AID - S0169-2607(19)30905-8 [pii]
AID - 10.1016/j.cmpb.2019.105101 [doi]
PST - ppublish
SO  - Comput Methods Programs Biomed. 2019 Dec;182:105101. doi: 
      10.1016/j.cmpb.2019.105101. Epub 2019 Sep 28.