Abstract
This paper describes a method for machine (computer) assessment of the quality of a retinal image. The method provides an over-all quantitative and objective measure using a quality index Q. The Q of a retinal image is calculated by the convolution of a template intensity histogram obtained from a set of typically good retinal images and the intensity histogram of the retinal image. After normalization, the Q has a maximum value of 1, indicating excellent quality, and a minimum value of 0, indicating bad quality. The paper also presents several application examples of Q in image enhancement. It is shown that the use of Q can help computer scientists evaluate the suitability and effectiveness of image enhancement methods, both quantitatively and objectively. It can further help computer scientists improve retinal image quality on a more scientific basis. Additionally, this machine image quality measure can also help physicians make medical diagnosis with more certainty and higher accuracy. Finally, it should be noted that although retinal images are used in this study, the methodology is applicable to the image quality assessment and enhancement of other types of medical images.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
