Investigating solidity as a shape feature in the selection of HRCT thorax images

Abstract

Scoring indices from high resolution computed tomography (HRCT) thorax images are essential for grading various changes in the abnormalities of the lung. The scoring index requires the radiologist to view and grade the signs and changes of the lung tissues at five predetermined levels of the HRCT images based on the lung anatomy; level 1:aortic arch, level 2: trachea carina, level 3: pulmonary hilar, level 4: pulmonary venous confluence and level 5: 1 to 2 cm above the dome of right hemidiaphragm. The enormous number of slices to be observed emphasize the need for a computer-aided system to assist in subsequent investigations. This paper propose a statistical shape feature, solidity of the heart, right lung and left lung, to be used in an automatic segmentation algorithm to retrieve level 4 and level 5. The segmentation algorithm used involved multilevel thresholding and multiscale morphological filtering. The quality of the segmentation was confirmed by the senior radiologist. No outlier was detected using the leave-one-out method (LOM) suggesting that the solidity shape feature is robust. The success rate of 82.35% for level 4 identification was achieved, whereas, the level 5 identification yielded 70.59% success rate which was obtained using the nearest-neighbour method. The proposed procedure suggests that the solidity shape feature of the heart, right lung and left lung may be used as one of the indicator for the discrimination and identification of level 4 and level 5 HRCT Thorax image.