Title :
Suppression of Translucent Elongated Structures: Applications in Chest Radiography
Author :
Hogeweg, Laurens ; Sanchez, Clara I. ; van Ginneken, Bram
Author_Institution :
Dept. of Radiol., Radboud Univ. Nijmegen Med. Centre, Nijmegen, Netherlands
Abstract :
Projection images, such as those routinely acquired in radiological practice, are difficult to analyze because multiple 3-D structures superimpose at a single point in the 2-D image. Removal of particular superimposed structures may improve interpretation of these images, both by humans and by computers. This work therefore presents a general method to isolate and suppress structures in 2-D projection images. The focus is on elongated structures, which allows an intensity model of a structure of interest to be extracted using local information only. The model is created from profiles sampled perpendicular to the structure. Profiles containing other structures are detected and removed to reduce the influence on the model. Subspace filtering, using blind source separation techniques, is applied to separate the structure to be suppressed from other structures. By subtracting the modeled structure from the original image a structure suppressed image is created. The method is evaluated in four experiments. In the first experiment ribs are suppressed in 20 artificial radiographs simulated from 3-D lung computed tomography (CT) images. The proposed method with blind source separation and outlier detection shows superior suppression of ribs in simulated radiographs, compared to a simplified approach without these techniques. Additionally, the ability of three observers to discriminate between patches containing ribs and containing no ribs, as measured by the area under the receiver operating characteristic curve (AUC), reduced from 0.99-1.00 on original images to 0.75-0.84 on suppressed images. In the second experiment clavicles are suppressed in 253 chest radiographs. The effect of suppression on clavicle visibility is evaluated using the clavicle contrast and border response, showing a reduction of 78% and 34%, respectively. In the third experiment nodules extracted from CT were simulated close to the clavicles in 100 chest radiographs. It was found that after suppressio- contrast of the nodules was higher than of the clavicles (1.35 and 0.55, respectively) than on original images (1.83 and 2.46, respectively). In the fourth experiment catheters were suppressed in chest radiographs. The ability of three observers to discriminate between patches originating from 36 images with and 21 images without catheters, as measured by the AUC, reduced from 0.98-0.99 on original images to 0.64-0.74 on suppressed images. We conclude that the presented method can markedly reduce the visibility of elongated structures in chest radiographs and shows potential to enhance diagnosis.
Keywords :
blind source separation; computerised tomography; diagnostic radiography; feature extraction; filtering theory; medical image processing; sensitivity analysis; 2D projection images; AUC; CT; blind source separation; chest radiography; clavicle border response; clavicle contrast; clavicle visibility; computerisd tomography; enhanced diagnosis; nodule extraction; radiological practice; receiver operating characteristic curve; ribs; subspace filtering; translucent elongated structure suppression; Catheters; Diagnostic radiography; Image reconstruction; Lungs; Principal component analysis; Ribs; Artifact removal; chest radiography; suppression; Adolescent; Adult; Aged; Algorithms; Artifacts; Catheters; Clavicle; Female; Humans; Lung Neoplasms; Male; Middle Aged; Radiographic Image Enhancement; Radiography, Thoracic; Ribs; Young Adult;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2013.2274212