Title :
A computer-aided diagnosis for locating abnormalities in bone scintigraphy by a fuzzy system with a three-step minimization approach
Author :
Yin, Tang-Kai ; Chiu, Nan-Tsing
Author_Institution :
Dept. of Manage. Inf. Sci., Chia-Nan Univ. of Pharmacy & Sci., Tainan, Taiwan
fDate :
5/1/2004 12:00:00 AM
Abstract :
Bone scintigraphy is an effective method to diagnose bone diseases such as bone tumors. In the scintigraphic images, bone abnormalities are widely scattered on the whole body. Conventionally, radiologists visually check the whole-body images and find the distributed abnormalities based on their expertise. This manual process is time-consuming and it is not unusual to miss some abnormalities. In this paper, a computer-aided diagnosis (CAD) system is proposed to assist radiologists in the diagnosis of bone scintigraphy. The system will provide warning marks and abnormal scores on some locations of the images to direct radiologists´ attention toward these locations. A fuzzy system called characteristic-point-based fuzzy inference system (CPFIS) is employed to implement the diagnosis system and three minimizations are used to systematically train the CPFIS. Asymmetry and brightness are chosen as the two inputs to the CPFIS according to radiologists´ knowledge. The resulting CAD system is of a small-sized rule base such that the resulting fuzzy rules can be not only easily understood by radiologists, but also matched to and compared with their expert knowledge. The prototype CAD system was tested on 82 abnormal images and 27 normal images. We employed free-response receiver operating characteristics method with the mean number of false positives (FPs) and the sensitivity as performance indexes to evaluate the proposed system. The sensitivity is 91.5% (227 of 248) and the mean number of FPs is 37.3 per image. The high sensitivity and moderate numbers of FP marks per image shows that the proposed method can provide an effective second-reader information to radiologists in the diagnosis of bone scintigraphy.
Keywords :
bone; fuzzy logic; fuzzy systems; image segmentation; inference mechanisms; medical image processing; minimisation; radioisotope imaging; asymmetry; bone abnormalities; bone diseases; bone scintigraphy; bone tumors; brightness; characteristic-point-based fuzzy interference system; computer-aided diagnosis; false positives; free-response receiver operating characteristics method; fuzzy system; radiologists; second-reader information; three-step minimization approach; whole-body images; Biomedical imaging; Bone diseases; Brightness; Computer aided diagnosis; Fuzzy systems; Medical diagnostic imaging; Minimization methods; Neoplasms; Pixel; Scattering; Algorithms; Bone Diseases; Bone and Bones; Expert Systems; Fuzzy Logic; Humans; Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Tomography, Emission-Computed; Whole-Body Counting;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2004.826355