Application of temporal subtraction for detection of interval changes on chest radiographs: improvement of subtraction images using automated initial image matching.
The authors developed a temporal subtraction scheme based on a nonlinear geometric warping technique to assist radiologists in the detection of interval changes in chest radiographs obtained on different occasions. The performance of the current temporal subtraction scheme is reasonably good; however, severe misregistration can occur in some cases. The authors evaluated the quality of 100 chest temporal subtraction images selected from their clinical image database. Severe misregistration was mainly attributable to initial incorrect global matching. Therefore, they attempted to improve the quality of the subtraction images by applying a new initial image matching technique to determine the global shift value between the current and the previous chest images. A cross-correlation method was employed for the initial image matching by use of blurred low-resolution chest images. Nineteen cases (40.4%) among 47 poor registered subtraction images were improved. These results show that the new initial image matching technique is very effective for improving the quality of chest temporal subtraction images, which can greatly enhance subtle changes in chest radiographs. (+info)
Lung field segmenting in dual-energy subtraction chest X-ray images.
The purpose of this study was to develop and test a method to delineate lung field boundaries in dual-energy chest x-ray images. The segmenting method uses soft-tissue images and spatial frequency-dependent, background-subtracted images. Large-scale chest anatomy features are located and used to select the lung apices, the lateral lung boundaries, and the lung-mediastinum and lung-diaphragm boundaries. Extraneous parts of the contours are removed and they are joined to form complete lung boundaries. The reliability measure uses a statistical shape model to estimate the probability of occurrence of a contour. The method was experimentally tested with 30 human subject images. It has higher accuracy and specificity and a sensitivity parameter equal to the best previously reported method. The reliability measure is able to detect contours with unusual lung outlines or errors in the processing. The method exploits the characteristics of dual-energy subtraction images to improve lung field segmenting performance. (+info)
Interobserver variation of prostatic volume estimation with digital rectal examination by urological staffs with different experiences.
PURPOSE: To compare the accuracy of estimating prostatic volume with digital rectal examination (DRE) by urological staffs with different experiences. Measurement of prostatic volume with transrectal ultrasonography (TRUS) serves as the reference standard. MATERIALS AND METHODS: Thirty-nine consecutive male patients admitted with acute urinary retention had their prostatic volume estimated with DRE by a urology junior trainee, a urology higher trainee and a trained urologist. All patients had TRUS to measure their prostatic volumes. Pearson correlation coefficients (r) were used to assess the relationships between the prostatic volume measured with TRUS and that estimated with DRE by the 3 urological staffs. Wilcoxon signed ranks tests were used to compare the discrepancies between the prostatic volume measured with TRUS and that estimated with DRE for the 3 Urological staffs, and to assess the inter-observer differences of these discrepancies. RESULTS: The correlation coefficients for the 3 urological staffs were r = 0.573 for the urology junior trainee, r = 0.541 for the urology higher trainee, and r = 0.640 for the trained urologist. The median discrepancies between the prostatic volume measured with TRUS and that estimated with DRE were -9.1 mL for the urology junior trainee, -1.3 mL for the urology higher trainee and 0.9 mL for the trained urologist. These discrepancies were statistically significant only in the case of urology junior trainee (p = 0.015, Wilcoxon signed ranks test). The difference in these discrepancies was statistically significant only between the urology junior trainee and the trained urologist (p = 0.003, Wilcoxon signed ranks test). CONCLUSIONS: The trained urologist was more accurate in estimating prostatic volume with DRE than the urology junior trainee. (+info)
Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases.
We are investigating image processing and analysis techniques to improve the ability of dual-energy digital radiography (DR) for the detection of cardiac calcification. Computed tomography (CT) is an established tool for the diagnosis of coronary artery diseases. Dual-energy digital radiography could be a cost-effective alternative. In this study, we use three-dimensional (3D) CT images as the "gold standard" to evaluate the DR X-ray images for calcification detection. To this purpose, we developed an automatic registration method for 3D CT volumes and two-dimensional (2D) X-ray images. We call this 3D-to-2D registration. We first use a 3D CT image volume to simulate X-ray projection images and then register them with X-ray images. The registered CT projection images are then used to aid the interpretation dual-energy X-ray images for the detection of cardiac calcification. We acquired both CT and X-ray images from patients with coronary artery diseases. Experimental results show that the 3D-to-2D registration is accurate and useful for this new application. (+info)
Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection.
We are investigating three-dimensional (3D) to two-dimensional (2D) registration methods for computed tomography (CT) and dual-energy digital radiography (DEDR). CT is an established tool for the detection of cardiac calcification. DEDR could be a cost-effective alternative screening tool. In order to utilize CT as the "gold standard" to evaluate the capability of DEDR images for the detection and localization of calcium, we developed an automatic, intensity-based 3D-to-2D registration method for 3D CT volumes and 2D DEDR images. To generate digitally reconstructed radiography (DRR) from the CT volumes, we developed several projection algorithms using the fast shear-warp method. In particular, we created a Gaussian-weighted projection for this application. We used normalized mutual information (NMI) as the similarity measurement. Simulated projection images from CT values were fused with the corresponding DEDR images to evaluate the localization of cardiac calcification. The registration method was evaluated by digital phantoms, physical phantoms, and clinical data sets. The results from the digital phantoms show that the success rate is 100% with a translation difference of less than 0.8 mm and a rotation difference of less than 0.2 degrees. For physical phantom images, the registration accuracy is 0.43 +/- 0.24 mm. Color overlay and 3D visualization of clinical images show that the two images registered well. The NMI values between the DRR and DEDR images improved from 0.21 +/- 0.03 before registration to 0.25 +/- 0.03 after registration. Registration errors measured from anatomic markers decreased from 27.6 +/- 13.6 mm before registration to 2.5 +/- 0.5 mm after registration. Our results show that the automatic 3D-to-2D registration is accurate and robust. This technique can provide a useful tool for correlating DEDR with CT images for screening coronary artery calcification. (+info)
Quantitative kinetic analysis of lung nodules using the temporal subtraction technique in dynamic chest radiographies performed with a flat panel detector.