Xin-Wei Xu

Development of an improved CAD scheme for automated detection of lung nodules in digital chest images

Lung cancer is the leading cause of cancer deaths in men and women in the United States, with a 5-year survival rate of only about 13%. However, this survival rate can be improved to 47% if the disease is diagnosed and treated at an early stage. In this study, we developed an improved computer-aided diagnosis (CAD) scheme for the automated detection of lung nodules in digital chest images to assist radiologists, who could miss up to 30% of the actually positive cases in their daily practice. Two hundred PA chest radiographs, 100 normals and 100 abnormals, were used as the database for our study. The presence of nodules in the 100 abnormal cases was confirmed by two experienced radiologists on the basis of CT scans or radiographic follow-up. In our CAD scheme, nodule candidates were selected initially by multiple gray-level thresholding of the difference image (which corresponds to the subtraction of a signal-enhanced image and a signal-suppressed image) and then classified into six groups. A large number of false positives were eliminated by adaptive rule-based tests and an artificial neural network (ANN). The CAD scheme achieved, on average, a sensitivity of 70% with 1.7 false positives per chest image, a performance which was substantially better as compared with other studies. The CPU time for the processing of one chest image was about 20 seconds on an IBM RISC/6000 Powerstation 590. We believe that the CAD scheme with the current performance is ready for initial clinical evaluation.

Image feature analysis for computer‐aided diagnosis: Accurate determination of ribcage boundary in chest radiographs

A computerized method for accurate determination of the ribcage boundary in chest images has been developed for use in computer-aided diagnosis (CAD) schemes for automated detection of abnormalities such as the pulmonary lung nodules, pneumothorax, interstitial disease, cardiomegaly, and interval changes in clinical chest images. With our method, the average position of the top of the lung in the chest image is determined first. Top lung edges and ribcage edges are determined within search ROIs, which are selected over top lung cages and ribcages. Three polynomial functions are applied separately to yield smooth curves for top lung edges and right and left ribcage edges. The complete ribcage boundary is then obtained by smoothly connecting three curves. A total of 1000 radiographs were digitized to 1k x 1k matrix size and a 10-bit gray scale with a laser scanner and analyzed by our method. The subjective evaluation indicated that our method produced moderately to highly accurate results in approximately 96% of the 1000 cases examined.

Comparison of imaging properties of a computed radiography system and screen–film systems

To compare the diagnostic quality of images obtained with a computed radiography (CR) system based on storage phosphor technology with that obtained with conventional screen-film systems, a dual-image recording technique was devised. With this technique, a CR imaging plate is placed behind a screen-film system in a conventional cassette. This makes it possible to obtain two images simultaneously, one from each system, in a clinical examination with the same patient positioning, the same degree of patient motion, the same geometric unsharpness, and no additional exposure. The modulation transfer functions (MTFs) of the CR system with and without the dual-image recording technique were greater at low frequencies, but lower at high frequencies, that the MTFs of the screen-film systems used. The noise Wiener spectra of the CR images at the plane of the imaging plate were greater than those of the screen-film systems, but were comparable to those of the screen-film systems at the plane of the printed film due to the reduction in image size. Clinical chest images obtained with the dual-image recording technique appeared comparable, probably because of the image size reduction and the use of mild unsharp mask processing.

Evaluation of imaging properties of a laser film digitizer

In this paper we provide a quantitative assessment of the basic imaging properties of a laser film digitizer. The characteristic curve of the digitizer was determined in terms of the relationship between input optical density and output pixel value. Spatial resolution of the laser digitizer was characterized using the presampling modulation transfer function (MTF), which was measured using a curve fitting technique with an angulated slit. For the noise analysis, we compared the Wiener spectra of uniformly exposed film samples before and after digitization. The effects of different sampling distances and scanning directions were investigated. Our results show that the characteristic curve of the laser digitizer was linear. The presampling MTFs of the digitizer were similar at different sampling distances and were substantially greater in the vertical scanning direction than in the horizontal direction. The noise of the digitized film sample was mainly affected by the presampling MTF and structure noise of the digitizer.

Development of a high quality film duplication system using a laser digitizer: Comparison with computed radiography

A high quality film-duplication system was developed in order to improve the image quality of duplicated radiographs and to recover improperly exposed films. The system consists of a laser film digitizer, a laser film printer, a workstation, and a magneto-optical disk. Radiographs are digitized by the laser digitizer, processed by the computer for image enhancement, and then printed on a film by the laser printer. A nonlinear density-correction technique is employed in recovering improperly exposed radiographs using the H&D curve of the screen-film system. Using the new duplication system in our department, the average recovery rate was over 80% for chest and abdominal films rejected due to over- or underexposed. The basic imaging properties of the duplication system were compared with those of a Computed Radiography (CR) system and a conventional screen-film system. For low spatial frequencies, the MTF of the CR system is superior to that of the digital duplication system; however, for high spatial frequencies, the MTF of the duplication system is superior. The noise in the duplication system is about half of that in the CR system.

Computer-aided diagnosis scheme for detecting pulmonary nodules using wavelet transform

To aid radiologists in the detection of lung cancer, we are developing a computer-aided diagnosis (CAD) system that locates areas suspicious for nodules in digital chest radiographs. The system involves a difference-image approach and various feature-extraction techniques. To improve the sensitivity of the overall scheme, we investigated an approach based on the wavelet transform. We found that the wavelet transform is effective in detecting subtle nodules that were not detected by the difference-image technique. By combining the two schemes based on the difference-image and the wavelet transform, the sensitivity was increased from 81% to 86% while maintaining approximately the same level of specificity.

Computer-aided detection of lung cancer on chest radiographs: algorithm performance vs. radiologists' performance by size of cancer

Our goal was to perform a pre-clinical test of the performance of a new pre-commercial system for detection of primary early-stage lung cancer on chest radiographs developed by Deus Technologies, LLC. The RapidScreenTM RS 2000 System integrates state of the art technical development in this field.

Adaptive feature analysis of false positives for computerized detection of lung nodules in digital chest images

To assist radiologists in diagnosing early lung cancer, we have developed a computer-aided diagnosis (CAD) scheme for automated detection of lung nodules in digital chest images. The database used for this study consisted of two hundred PA chest radiographs, including 100 normals and 100 abnormals. Our CAD scheme has four basic steps, namely, (1) preprocessing, (2) identification of initial nodule candidates (rule-based test #1), (3) grouping of initial nodule candidates into six groups, and (4) elimination of false positives (rule-based test #2 - #5 and artificial neural network). Our CAD scheme achieves, on average, a sensitivity of 70%, with 1.7 false positives per chest image. We believe that this CAD scheme with its current performance is ready for clinical evaluation.

Methods for identifying changes in radiologists' behavioral operating point of sensitivity-specificity trade-offs within an ROC study of the use of computer-aided detection of lung cancer

In this paper, we look at a different potentially useful method of behavior analysis, a method that may allow one to derive from the ROC confidence ratings of individual radiologists, a behavioral operating point that closely reflects the point where the radiologist would have decided to act or take no action on a case. This behavioral operating point appears appropriate for the calculation of cost benefit relationships and for studying how a radiologist shifts within ROC space when provided with Computer Aided Diagnosis (CADx) information.

Development of a digital duplication system for portable chest radiographs

To provide high-quality duplicate chest images for the intensive care units, we have developed a digital duplication system in which film digitization is performed in conjunction with nonlinear density correction, contrast adjustment, and unsharp mask filtering. This system provides consistent image densities over a wide exposure range and enhancement of structures in the mediastinum and upper abdominal areas, improving visibility of catheters and tubes. The image quality is often superior to that of the original radiograph and is more consistent from day to day. Repeat rates for portable chest radiographs have been reduced by more than a factor of two since implementation of digitization in December 1991, and the number of repeat examinations caused by exposure errors have been substantially reduced.