This system could be used when screening for diabetic retinopathy. At 94.8% sensitivity setting the number of normal images requiring examination by a human grader could be halved.

No abstract

In this chapter, the usability of finger vein biometric devices is reviewed and discussed from various viewpoints. Since the usability requirements vary on both the applications and the situations in which the device is used, the requirements need to be carefully reviewed in light of each viewpoint and reflected to the product design.

Hiroto NAGAYOSHI†a) , Yoshitaka HIRAMATSU †b) , Hiroshi SAKO †c) , Mitsutoshi HIMAGA † †d) , Members, and Satoshi KATO † † †e) , Nonmember SUMMARY A system for detecting fundus lesions caused by diabetic retinopathy from fundus images is being developed. The system can screen the images in advance in order to reduce the inspection workload on doctors. One of the difficulties that must be addressed in completing this system is how to remove false positives (which tend to arise near blood vessels) without decreasing the detection rate of lesions in other areas. To overcome this difficulty, we developed classifier selection according to the position of a candidate lesion, and we introduced new features that can distinguish true lesions from false positives. A system incorporating classifier selection and these new features was tested in experiments using 55 fundus images with some lesions and 223 images without lesions. The results of the experiments confirm the effectiveness of the proposed system, namely, degrees of sensitivity and specificity of 98% and 81%, respectively.