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Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images.

Abstract Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE), central serous chorioretinopathy (CSCR), or age related macular degeneration (ARMD). Optical coherence tomography (OCT) imaging is the latest eye testing technique that can detect these syndromes in early stages. Many researchers have used OCT images to detect retinal abnormalities. However, to the best of our knowledge, no research that presents a fully automated system to detect all of these macular syndromes is reported. This paper presents the world's first ever decision support system to automatically detect RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The automated disease diagnosis in our proposed system is based on multilayered support vector machines (SVM) classifier trained on 40 labeled OCT scans (10 healthy, 10 RE, 10 CSCR, and 10 ARMD). After training, SVM forms an accurate decision about the type of retinal pathology using 9 extracted features. We have tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR) of 502 patients from two different datasets and our proposed system correctly diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity ratings of 99.92%, 100%, and 99.86%, respectively.
PMID
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Authors

Mayor MeshTerms

Image Processing, Computer-Assisted

Keywords
Journal Title biomed research international
Publication Year Start




PMID- 28424788
OWN - NLM
STAT- MEDLINE
DA  - 20170420
DCOM- 20170508
LR  - 20170508
IS  - 2314-6141 (Electronic)
VI  - 2017
DP  - 2017
TI  - Fully Automated Robust System to Detect Retinal Edema, Central Serous
      Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence
      Tomography Images.
PG  - 7148245
LID - 10.1155/2017/7148245 [doi]
AB  - Maculopathy is the excessive damage to macula that leads to blindness. It mostly 
      occurs due to retinal edema (RE), central serous chorioretinopathy (CSCR), or age
      related macular degeneration (ARMD). Optical coherence tomography (OCT) imaging
      is the latest eye testing technique that can detect these syndromes in early
      stages. Many researchers have used OCT images to detect retinal abnormalities.
      However, to the best of our knowledge, no research that presents a fully
      automated system to detect all of these macular syndromes is reported. This paper
      presents the world's first ever decision support system to automatically detect
      RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The
      automated disease diagnosis in our proposed system is based on multilayered
      support vector machines (SVM) classifier trained on 40 labeled OCT scans (10
      healthy, 10 RE, 10 CSCR, and 10 ARMD). After training, SVM forms an accurate
      decision about the type of retinal pathology using 9 extracted features. We have 
      tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR)
      of 502 patients from two different datasets and our proposed system correctly
      diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity
      ratings of 99.92%, 100%, and 99.86%, respectively.
FAU - Khalid, Samina
AU  - Khalid S
AUID- ORCID: 0000-0003-4771-6842
AD  - Department of Computer Science & Information Technology, Mirpur University of
      Science and Technology, Mirpur, Pakistan.
AD  - Department of Software Engineering, Bahria University, Islamabad, Pakistan.
FAU - Akram, M Usman
AU  - Akram MU
AUID- ORCID: 0000-0002-6208-7231
AD  - Department of Computer Engineering, National University of Sciences and
      Technology, Islamabad, Pakistan.
FAU - Hassan, Taimur
AU  - Hassan T
AD  - Department of Computer Engineering, National University of Sciences and
      Technology, Islamabad, Pakistan.
AD  - Department of Electrical Engineering, Bahria University, Islamabad, Pakistan.
FAU - Nasim, Ammara
AU  - Nasim A
AD  - Department of Electrical Engineering, Bahria University, Islamabad, Pakistan.
FAU - Jameel, Amina
AU  - Jameel A
AD  - Department of Computer Engineering, Bahria University, Islamabad, Pakistan.
LA  - eng
PT  - Journal Article
DEP - 20170323
PL  - United States
TA  - Biomed Res Int
JT  - BioMed research international
JID - 101600173
SB  - IM
MH  - Algorithms
MH  - Automation
MH  - Central Serous Chorioretinopathy/*diagnosis
MH  - Choroid/pathology
MH  - Female
MH  - Humans
MH  - *Image Processing, Computer-Assisted
MH  - Macular Degeneration/*diagnosis
MH  - Macular Edema/*diagnosis
MH  - Male
MH  - Reproducibility of Results
MH  - Retina/*pathology
MH  - Tomography, Optical Coherence/*methods
PMC - PMC5382397
EDAT- 2017/04/21 06:00
MHDA- 2017/05/10 06:00
CRDT- 2017/04/21 06:00
PHST- 2016/12/27 [received]
PHST- 2017/02/23 [revised]
PHST- 2017/03/08 [accepted]
AID - 10.1155/2017/7148245 [doi]
PST - ppublish
SO  - Biomed Res Int. 2017;2017:7148245. doi: 10.1155/2017/7148245. Epub 2017 Mar 23.

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