Retinal Vessel Detection and Measurement for Computer-aided Medical Diagnosis

详细信息    查看全文

• 作者：Xiaokun Li (1)
  William G. Wee (2)
  
• 关键词：Computer ; aided medical diagnosis ; Image processing ; Computer vision ; Artificial intelligence
• 刊名：Journal of Digital Imaging
• 出版年：2014
• 出版时间：February 2014
• 年：2014
• 卷：27
• 期：1
• 页码：120-132
• 全文大小：862 KB
• 作者单位：Xiaokun Li (1)
  William G. Wee (2)
  
  1. TASC, Inc, 475 School Street SW, Washington, DC, 20024, USA
  2. Department of ECE, University of Cincinnati, Cincinnati, OH, 45220, USA
  
• ISSN：1618-727X

文摘

Since blood vessel detection and characteristic measurement for ocular retinal images is a fundamental problem in computer-aided medical diagnosis, automated algorithms/systems for vessel detection and measurement are always demanded. To support computer-aided diagnosis, an integrated approach/solution for vessel detection and diameter measurement is presented and validated. In the proposed approach, a Dempster–Shafer (D–S)-based edge detector is developed to obtain initial vessel edge information and an accurate vascular map for a retinal image. Then, the appropriate path and the centerline of a vessel of interest are identified automatically through graph search. Once the vessel path has been identified, the diameter of the vessel will be measured accordingly by the algorithm in real time. To achieve more accurate edge detection and diameter measurement, mixed Gaussian-matched filters are designed to refine the initial detection and measures. Other important medical indices of retinal vessels can also be calculated accordingly based on detection and measurement results. The efficiency of the proposed algorithm was validated by the retinal images obtained from different public databases. Experimental results show that the vessel detection rate of the algorithm is 100?% for large vessels and 89.9?% for small vessels, and the error rate on vessel diameter measurement is less than 5?%, which are all well within the acceptable range of deviation among the human graders.