Beyond Retinal Layers: A Large Blob Detection for Subretinal Fluid Segmentation in SD-OCT Images

  • Zexuan Ji
  • Qiang Chen
  • Menglin Wu
  • Sijie Niu
  • Wen Fan
  • Songtao Yuan
  • Quansen Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11071)


Purpose: To automatically segment neurosensory retinal detachment (NRD)-associated subretinal fluid in spectral domain optical coherence tomography (SD-OCT) images by constructing a Hessian-based Aggregate generalized Laplacian of Gaussian algorithm without the use of retinal layer segmentation. Methods: The B-scan is first filtered into small blob candidate regions based on local convexity by aggregating the log-scale-normalized convolution responses of each individual gLoG filter. Two Hessian-based regional features are extracted based on the aggregate response map. Pooling with regional intensity, the feature vectors are fed into an unsupervised clustering algorithm. By voting the blob candidates into the superpixels, the initial subretinal fluid regions are obtained. Finally, an active contour with narrowband implementation is utilized to obtain integrated segmentations. Results: The testing data set with 23 longitudinal SD-OCT cube scans from 12 eyes of 12 patients are used to evaluate the proposed algorithm. Comparing with two independent experts’ manual segmentations, our algorithm obtained a mean true positive volume fraction 95.15%, positive predicative value 93.65% and dice similarity coefficient 94.35%, respectively. Conclusions: Without retinal layer segmentation, the proposed algorithm can produce higher segmentation accuracy comparing with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable subretinal fluid segmentations for NRD from SD-OCT images.


Spectral domain optical coherence tomography Subretinal fluid segmentation Neurosensory retinal detachment Blob segmentation 


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjingChina
  2. 2.School of Computer Science and TechnologyNanjing Tech UniversityNanjingChina
  3. 3.School of Information Science and EngineeringUniversity of JinanJinanChina
  4. 4.Department of OphthalmologyThe First Affiliated Hospital with Nanjing Medical UniversityNanjingChina

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