No abstract

Osteoporosis is characterized by an abnormal loss of bone mineral content, which leads to a tendency to non-traumatic bone fractures or to structural deformations of bone. Thus, bone density has been considered as a most reliable parameter to assess osteoporotic fracture risk. In past decades, by the way, bone texture measures have been studied to estimate other aspect of bone quality. Some studies have been performed on CT or MR images to assess bone quality using trabecular structure analysis. Other studies have been performed on plain x-ray images or ultrasound images to assess trabecular structure. However, most of the studies are focused on individual parameters to distinguish between osteoporotic fractured group and nonfractured group. In this preliminary study, we combine various texture parameters with bone density parameters using a support vector machine and point out the most promising combination of parameters to distinguish between osteoporotic fractured group and nonfractured group.

Various statistical parameters have been tried for the computer-aided diagnosis of the liver fibrosis. The region of interest (ROI) for the liver and spleen parenchymas have been chosen, and the hepatolienal textural contrast for each ultrasound (US) image has been examined. The selectively chosen textural parameters are linearly combined with the pre-determined coefficients to give the computer-aided diagnostic parameter for the liver fibrosis, whose final stage is named as cirrhosis. From the comparison with the clinical diagnosis it is suggested that the proposed calculation scheme using the textural parameters show the quite promising classification performance for the computer-aided diagnosis of the liver cirrhosis.

Osteoporosis is characterized by an abnormal loss of bone mineral content, which leads to a tendency to non-traumatic bone fractures or to structural deformations of bone. Thus, bone density measurement has been considered as a most reliable method to assess bone fracture risk due to osteoporosis. In past decades, X-ray images have been studied in connection with the bone mineral density estimation. However, the estimated bone mineral density from the X-ray image can undergo a relatively large accuracy or precision error. The most relevant origin of the accuracy or precision error may be unstable X-ray image acquisition condition. Thus, we focus our attentions on finding a bone mineral density estimation method that is relatively insensitive to the X-ray image acquisition condition. In this paper, we develop a simple technique for distal radius bone mineral density estimation using the trabecular bone filling factor in the X-ray image and apply the technique to the wrist X-ray images of 20 women. Estimated bone mineral density shows a high linear correlation with a dual-energy X-ray absorptiometry (r=0.87).

No abstract