Application of Deep Learning in Early Diagnosis Assistant System of Keratoconus / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 83-85, 2019.
Article
in Chinese
| WPRIM
| ID: wpr-772559
ABSTRACT
In view of the problem that there is no standard diagnosis for early stage keratoconus disease,at the same time to assist the special examiner and ophthalmologist to make the early diagnosis effectively,the advantages and disadvantages of each testing instrument were analyzed.In order to construct an assistant system for early diagnosis of keratoconus,a deep learning technique was applied in corneal OCT examination.The system used improved VGG-16 to realize the recognition accuracy of about 68% keratoconus keratopathy,and the clinical results showed that the system can help doctors to give diagnosis confidence to a certain extent.At the same time,the physician's re-marking of OCT can help train the system for more accurate judgment.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Diagnostic Imaging
/
Corneal Topography
/
Tomography, Optical Coherence
/
Early Diagnosis
/
Deep Learning
/
Keratoconus
Type of study:
Diagnostic study
/
Screening study
Limits:
Humans
Language:
Chinese
Journal:
Chinese Journal of Medical Instrumentation
Year:
2019
Type:
Article
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