Automatic gray-scale transformation in the Konica direct digitizer system

Sumiya Nagatsuka; Akiko Kano; Hisanori Tsuchino; Hideyuki Handa

doi:10.1117/12.59453

1 June 1992 Automatic gray-scale transformation in the Konica direct digitizer system

Sumiya Nagatsuka, Akiko Kano, Hisanori Tsuchino, Hideyuki Handa

Proceedings Volume 1652, Medical Imaging VI: Image Processing; (1992) https://doi.org/10.1117/12.59453
Event: Medical Imaging VI, 1992, Newport Beach, CA, United States

Abstract

In x-ray radiographs for use in the medical field, it is desired that the density in the region of interest (ROI, area containing important image consistent for diagnosis) on the x-ray radiograph image is stable and its gradation is adjusted so that the structure of human body and the shade and shadow of the lesion can be observed easily. In developing the Konica Direct Digitizer, which is a digital radiographic image input apparatus to be used exclusively for chest and abdomen images, we have developed a new automatic gray scale transformation algorithm capable of providing most suitable images for diagnosis. The remarkable characteristic of the automatic gray scale transformation algorithm developed this time is to identify automatically the position of ROI in the image and to determine the gray scale transformation conditions based on the image data in the ROI. We investigated 50 clinical images radiographed by Konica Direct Digitizer from the viewpoint of the accuracy of the position of ROI established by the automatic gray scale transformation and of the image finish conditions accomplished by the automatic gray scale transformation. As a result, we have learned that both of them were stable and sufficiently accurate. From now on, we further improve its accuracy by increasing clinical images and applying this system to various regions.

Citation Download Citation

Sumiya Nagatsuka, Akiko Kano, Hisanori Tsuchino, and Hideyuki Handa "Automatic gray-scale transformation in the Konica direct digitizer system", Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); https://doi.org/10.1117/12.59453

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