Identification of suitable fundus images using automated quality assessment methods

ŞEVİK U., KÖSE C., BERBER T., ERDÖL H.

JOURNAL OF BIOMEDICAL OPTICS, cilt.19, sa.4, 2014 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 4
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1117/1.jbo.19.4.046006
  • Dergi Adı: JOURNAL OF BIOMEDICAL OPTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: computer-assisted image analysis, automated image quality assessment, suitable retinal image frame, retinal image analysis, machine learning, SEGMENTATION, COLOR, RETRIEVAL, LOCALIZATION, ALGORITHMS, DIAGNOSIS
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Retinal image quality assessment (IQA) is a crucial process for automated retinal image analysis systems to obtain an accurate and successful diagnosis of retinal diseases. Consequently, the first step in a good retinal image analysis system is measuring the quality of the input image. We present an approach for finding medically suitable retinal images for retinal diagnosis. We used a three-class grading system that consists of good, bad, and outlier classes. We created a retinal image quality dataset with a total of 216 consecutive images called the Diabetic Retinopathy Image Database. We identified the suitable images within the good images for automatic retinal image analysis systems using a novel method. Subsequently, we evaluated our retinal image suitability approach using the Digital Retinal Images for Vessel Extraction and Standard Diabetic Retinopathy Database Calibration level 1 public datasets. The results were measured through the F1 metric, which is a harmonic mean of precision and recall metrics. The highest F1 scores of the IQA tests were 99.60%, 96.50%, and 85.00% for good, bad, and outlier classes, respectively. Additionally, the accuracy of our suitable image detection approach was 98.08%. Our approach can be integrated into any automatic retinal analysis system with sufficient performance scores. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)