Development of computer-aided diagnosis system for 3D multi-detector row CT images of livers

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

“…Hadjiiski et al [5] also utilized run length statistic texture features for mammogram classification. Automatic segmentation of parotid glands in head and neck (H&N) CT images have also drawn a lot of attention in recent years, not only for assisting image-based diagnosis but also for modern radiation therapy planning [6]. For diagnosis, parotid glands need to be taken into consideration because lesions in parotids may be associated with diseases [7].…”

Proposal of computer-aided detection system for three dimensional CT images of liver cancer

“…However it is difficult for physicians to interpret the three dimensional (3D) images obtained with such scanner because of a large number of slice (or section) images. In order to help the physicians in the diagnosis, computer-aided detection (CAD) systems have been proposed [1][2][3][4]. However these systems suffer from several limitations.…”

Liver cancer detection by using transition features obtained from multi-phase CT images

“…Not only spatial change of density in an image but also temporal change of density at each point of the image caused by the contrast medium gives significant diagnostic information. For automatic detection of liver cancer from multi-phase CT images, several methods using only one or two phases of CT images have been developed [1,2]. However, there has been no method using transition features of density obtained from all of multi-phase CT images.…”