PMID- 31728935
OWN - NLM
STAT- MEDLINE
DCOM- 20201008
LR  - 20201008
IS  - 1741-0444 (Electronic)
IS  - 0140-0118 (Linking)
VI  - 58
IP  - 1
DP  - 2020 Jan
TI  - AOCT-NET: a convolutional network automated classification of multiclass retinal 
      diseases using spectral-domain optical coherence tomography images.
PG  - 41-53
LID - 10.1007/s11517-019-02066-y [doi]
AB  - Since introducing optical coherence tomography (OCT) technology for 2D eye 
      imaging, it has become one of the most important and widely used imaging 
      modalities for the noninvasive assessment of retinal eye diseases. Age-related 
      macular degeneration (AMD) and diabetic macular edema eye disease are the leading 
      causes of blindness being diagnosed using OCT. Recently, by developing machine 
      learning and deep learning techniques, the classification of eye retina diseases 
      using OCT images has become quite a challenge. In this paper, a novel automated 
      convolutional neural network (CNN) architecture for a multiclass classification 
      system based on spectral-domain optical coherence tomography (SD-OCT) has been 
      proposed. The system used to classify five types of retinal diseases (age-related 
      macular degeneration (AMD), choroidal neovascularization (CNV), diabetic macular 
      edema (DME), and drusen) in addition to normal cases. The proposed CNN 
      architecture with a softmax classifier overall correctly identified 100% of cases 
      with AMD, 98.86% of cases with CNV, 99.17% cases with DME, 98.97% cases with 
      drusen, and 99.15% cases of normal with an overall accuracy of 95.30%. This 
      architecture is a potentially impactful tool for the diagnosis of retinal 
      diseases using SD-OCT images.
FAU - Alqudah, Ali Mohammad
AU  - Alqudah AM
AUID- ORCID: 0000-0002-5417-0043
AD  - Department of Biomedical Systems and Informatics Engineering, Yarmouk University, 
      Irbid, Jordan. ali_qudah@hotmail.com.
LA  - eng
PT  - Journal Article
DEP - 20191114
PL  - United States
TA  - Med Biol Eng Comput
JT  - Medical & biological engineering & computing
JID - 7704869
SB  - IM
MH  - *Algorithms
MH  - Automation
MH  - Databases as Topic
MH  - Entropy
MH  - Humans
MH  - *Imaging, Three-Dimensional
MH  - *Neural Networks, Computer
MH  - ROC Curve
MH  - Retinal Diseases/*classification/*diagnostic imaging
MH  - *Tomography, Optical Coherence
MH  - User-Computer Interface
OTO - NOTNLM
OT  - Classification
OT  - Deep learning
OT  - Optical coherence tomography
OT  - Retina
OT  - Spectral domain
EDAT- 2019/11/16 06:00
MHDA- 2020/10/09 06:00
CRDT- 2019/11/16 06:00
PHST- 2019/05/11 00:00 [received]
PHST- 2019/11/02 00:00 [accepted]
PHST- 2019/11/16 06:00 [pubmed]
PHST- 2020/10/09 06:00 [medline]
PHST- 2019/11/16 06:00 [entrez]
AID - 10.1007/s11517-019-02066-y [pii]
AID - 10.1007/s11517-019-02066-y [doi]
PST - ppublish
SO  - Med Biol Eng Comput. 2020 Jan;58(1):41-53. doi: 10.1007/s11517-019-02066-y. Epub 
      2019 Nov 14.