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Adaptive mammographic image enhancement using first derivative and local statistics

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4 Author(s)
Jong Kook Kim ; Dept. of Inf. & Commun. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea ; Jeong Mi Park ; Koun Sik Song ; Hyun Wook Park

This paper proposes an adaptive image enhancement method for mammographic images, which is based on the first derivative and the local statistics. The adaptive enhancement method consists of three processing steps. The first step is to remove the film artifacts which may be misread as microcalcifications. The second step is to compute the gradient images by using the first derivative operators. The third step is to enhance the important features of the mammographic image by adding the adaptively weighted gradient images. Local statistics of the image are utilized for adaptive realization of the enhancement, so that image details can be enhanced and image noises can be suppressed. The objective performances of the proposed method were compared with those by the conventional image enhancement methods for a simulated image and the seven mammographic images containing real microcalcifications. The performance of the proposed method was also evaluated by means of the receiver operating characteristics (ROC) analysis for 78 real mammographic images with and without microcalcifications.

Published in:

IEEE Transactions on Medical Imaging  (Volume:16 ,  Issue: 5 )