Retinal Spot Lesion Detection Using Adaptive Multiscale Morphological Processing

  • Xin Zhang
  • Guoliang Fan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4292)


We present a new spot lesion detection algorithm for retinal images with background diabetic retinopathy (DR) pathologies. The highlight of this algorithm is its capability to deal with all DR-related spot lesions of various sizes and shapes that is accomplished by a unique adaptive multiscale morphological processing technique. A scale map is generated to delineate lesion areas based an edge model, and it is used to fuse multiscale morphological processing results for lesion enhancements. The local/releative entropy thresholding techniques are employed to segment lesion regions, and a scale-guided validation process is used to remove over-detections based on the scale map. The proposed algorithm is tested on 30 retinal images where all spot lesions are hand-labelled for performance evaluation. Compared with two existing algorithms, the proposed one significantly improves the overall performance of spot lesion detection producing higher sensitivity and/or predictive values.


Diabetic Retinopathy Retinal Image Lesion Detection Optimal Scale Early Treatment Diabetic Retinopathy Study 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xin Zhang
    • 1
  • Guoliang Fan
    • 1
  1. 1.School of Electrical and Computer EngineeringOklahoma State UniversityStillwaterUSA

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