Rib suppression in frontal chest radiographs: A blind source separation approach

Chest radiographs play an important role in the diagnosis of lung cancer. Detection of pulmonary nodules in chest radiographs forms the basis of early detection. Due to its sparse bone structure and overlapping of the nodule with ribs and clavicles the nodule is difficult to detect in conventional chest radiographs. We present a technique based on independent component analysis (ICA) for the suppression of posterior ribs and clavicles which will enhance the visibility of the nodules and aid the radiologist in diagnosis.

[1]  D. H. Lange,et al.  Modeling and estimation of single evoked brain potential components , 1997, IEEE Transactions on Biomedical Engineering.

[2]  Kunio Doi,et al.  Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN) , 2006, IEEE Transactions on Medical Imaging.

[3]  M. Giger,et al.  Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. , 1997, Medical physics.

[4]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

[5]  Tony Lindeberg,et al.  Feature Detection with Automatic Scale Selection , 1998, International Journal of Computer Vision.

[6]  Alejandro F. Frangi,et al.  Active shape model segmentation with optimal features , 2002, IEEE Transactions on Medical Imaging.

[7]  Noriyuki Tomiyama,et al.  Temporal subtraction for detection of solitary pulmonary nodules on chest radiographs: evaluation of a commercially available computer-aided diagnosis system. , 2002, Radiology.

[8]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[9]  K. Doi,et al.  Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules. , 2000, AJR. American journal of roentgenology.

[10]  K. Doi,et al.  Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study. , 2003, Academic radiology.

[11]  Bram van Ginneken,et al.  A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database , 2006, Medical Image Anal..