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Biomedical subjects

H MacMahon

Publications and source records attributed to H MacMahon.

At least 37 records · Page 2Linked to original sources
PubMed1997

Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks.

We devised an automated classification scheme by using the rule-based method plus artificial neural networks (ANN) for distinction between normal and abnormal lungs with interstitial disease in digital chest radiographs. Four measures used in the classification scheme are determined from the texture and geometric-pattern feature analyses. The rms variation and the first moment of the power spectrum of lung patterns are determined as measures for the texture analysis. In addition, the total area of nodular opacities and the total length of linear opacities are determined as measures for the geometric-pattern feature analysis. In our classification scheme with these measures, we identify obviously normal and abnormal cases first by the rule-based method and then ANN is applied for the remaining difficult cases. The rule-based plus ANN method provided a sensitivity of 0.926 at the specificity of 0.900, which was considerably improved compared to performance of either the rule-based method alone or ANNs alone.

Diagnosis, Computer-Assisted↗
PubMed1997

Automated registration of ventilation-perfusion images with digital chest radiographs.

RATIONALE AND OBJECTIVES: The authors have developed an automated computerized technique for registering radionuclide lung scan images with digital chest radiographs. METHODS: Threshold analysis was used to construct contours around the high-activity regions of radionuclide ventilation-perfusion images. Analogous contours were constructed around the lung regions of the corresponding digitized radiographs. Contour dimensions and anatomic landmark locations were then used to superimpose the radiographic, ventilation, and perfusion images. RESULTS: Evaluation of 25 sets of images indicated that the scheme provided adequate to excellent registration in 91% of the pairwise combinations. CONCLUSION: This automated scheme for registering ventilation-perfusion images with digital chest radiographs has the potential to aid radiologists in the interpretation of these images.

Adult↗
PubMed1997

Computerized analysis of interstitial disease in chest radiographs: improvement of geometric-pattern feature analysis.

We have been developing automated computerized schemes to assist radiologists in interpreting chest radiographs for interstitial disease based on texture analysis and geometric-pattern feature analysis. In this study, we attempted to improve the performance of the geometric-pattern feature analysis, because the current classification performance with geometric-pattern feature analysis is considerably lower than that of texture analysis. In order to improve the performance in distinguishing between normal lungs and abnormal lungs with interstitial disease, we attempted to remove rib edges in regions of interest (ROIs) by using an edge detection technique, and also to reduce false positives by using feature analysis techniques. In addition, the effects of many parameters on classification performance were investigated to identify proper threshold levels, and subsequently the specificity of the geometric-pattern feature analysis was improved from 69.5% to 86.1% at a sensitivity of 95.0%. Using a combined rule-based method with texture analysis and geometric-pattern feature analysis plus the artificial neural network (ANN) method for classification, a high specificity of 96.1% was obtained at a sensitivity of 95.0%.

Biophysical Phenomena↗
PubMed1997

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.

Adult↗
PubMed1997

Digital chest radiography: effect of temporal subtraction images on detection accuracy.

PURPOSE: To improve early detection of disease in chest radiographs, the authors developed a digital processing technique that geometrically warps and subtracts a previous radiograph from a current radiograph to produce a temporal subtraction image. An observer test was performed to evaluate the effects of the temporal subtraction image technique on detection of interval change. MATERIALS AND METHODS: Fifty pairs of chest radiographs, including a baseline examination and a subsequent radiograph, were selected (25 cases in which potentially important new abnormalities had developed, and 25 in which there was no interval change). The baseline examination was chosen from multiple prior radiographs to minimize initial misregistration. By means of receiver operating characteristic (ROC) analysis, the ability of 11 observers to detect pathologic change when viewing the paired digitized baseline and subsequent radiographs was compared with their ability when viewing the same paired radiographs together with temporal subtraction images. Positive cases demonstrated focal new abnormalities that were greater than 1 cm in diameter. RESULTS: The mean area (Az) under the ROC curves increased from 0.89 without to 0.98 with the temporal subtraction images. When the paired digitized previous and current chest radiographs were viewed in conjunction with the temporal subtraction images, a significant improvement in detection of new abnormalities was achieved (P = .00004), whereas the mean interpretation time was reduced by 19.3% (from 52 to 42 seconds, including the time to record the score and to move to the next case) (P = .0019). CONCLUSION: The temporal subtraction technique can significantly improve sensitivity and specificity for detection of interval change in chest radiographs.

Humans↗
PubMed1996

Quantitative analysis of geometric-pattern features of interstitial infiltrates in digital chest radiographs: preliminary results.

We are developing a computerized method for detection and characterization of interstitial diseases based on a quantitative analysis of geometric features of various infiltrate patterns in digital chest radiographs. In our approach, regions of interest (ROIs) with 128 x 128 matrix size (22.4 mm x 22.4 mm) are automatically selected, covering peripheral lung regions. Next, nodular and linear opacities, which are the basic components of interstitial infiltrates, are identified from two processed images obtained by use of a multiple-level thresholding technique and a line enhancement filter, respectively. Finally, the total area of nodular opacities and the total length of linear opacities in each ROI are determined as measures of geometric pattern features. We have applied this computer analysis to 72 ROIs with normal and abnormal patterns that were classified in advance by six chest radiologists. Preliminary results indicate that the distribution of measures of geometric-pattern features correlate well with radiologists' classification. These early results are encouraging, and further evaluation hopes to establish that this computerized method might prove useful to radiologists in their assessment of interstitial diseases.

Humans↗
PubMed1996

The effect of x-ray beam alignment on the performance of antiscatter grids.

While the qualitative effects of grid misalignment are known, we have quantified the effect of different degrees of grid misalignment on image contrast and patient exposure. Radiographs were made of a phantom consisting of five lead disks on top of a 15 cm block of lucite. Four 60 lines/cm grids, having grid ratios of 3:1, 4:1, 6:1, and 8:1 were used. When the tube was angled more than three degrees across the grid lines, the contrast improvement factor decreased substantially for all four grids, as much as 46% for an 8:1 grid with a 12 degrees misalignment. There was a concomitant decrease in film optical density, which if compensated for by an increase in patient exposure, would lead to a higher effective bucky factor. With the exception of the 3:1 grid, if the grid is misaligned by more than 6 degrees, higher signal-to-noise ratios can be attained by removing the grid and using the increased patient exposure to reduce noise.

Colloids↗
PubMed1996

Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs.

PURPOSE: To evaluate the effect of a computer-aided diagnosis (CAD) scheme on radiologists' performance in the detection of lung nodules, and to examine a new method of receiver operating characteristic (ROC) analysis. MATERIALS AND METHODS: One hundred twenty radiographs (60 normal and 60 abnormal with lung nodules of varying subtlety) were used. Sixteen radiologists (two thoracic, six general, and eight residents) participated in an observer study in which they read both conventional radiographs and digitized radiographs. The radiologists' performance was evaluated with ROC analysis with two different methods (independent testing and sequential testing) and a continuous rating scale. RESULTS: Az (area under the best fit binormal ROC curve when it is plotted in the unit square) values obtained from ROC analysis with and without CAD output were 0.940 and 0.894, respectively, in the independent test and 0.948 and 0.906, respectively, in the sequential test. Findings with both methods indicated that the CAD scheme statistically significantly improved diagnostic accuracy, particularly for radiologists with less experience (P < .001). Reading time was not increased when CAD was used. CONCLUSION: The CAD scheme can assist radiologists in the detection of lung nodules on chest radiographs.

Adult↗
PubMed1996

Portable chest radiography techniques and teleradiology.

Despite the large number of portable examinations performed, the quality of bedside radiography is highly variable and has lagged behind the rapid advances in other fields of medical imaging. The authors discuss the technical factors of image production in relation to methods for improving image quality in portable radiography. Digital radiography has significant practical technical advantages in portable applications and also allows transmission and accessibility of images on a computer network.

Humans↗
PubMed1996

Image processing and computer-aided diagnosis.

The future of image processing and CAD in diagnostic radiology is more promising now than ever, with increasingly impressive results being reported from various observer performance studies in both mammography and chest radiography. Clinical trials in years to come will help optimize the accuracy of the programs and determine the actual contribution of CAD to the interpretation process. Radiologists using output from computer analyses of images, however, will still make the final decision regarding diagnosis and patient management. Nonetheless, studies have indicated that the computer output need not have greater overall accuracy than a given radiologist in order to improve his or her performance. A systematic and gradual introduction of CAD into radiology departments will be necessary so that radiologists can become familiar with the strengths and weaknesses of each CAD program, thereby avoiding either excessive reliance or a dismissive attitude toward the computer output. This should ensure the acceptance of CAD and optimal diagnostic performance by the radiologist. Thus, an appropriate role for each CAD program will be determined for each radiologist, according to his or her individual training and observational skills, reducing intraobserver variations and improving diagnostic performance.

Diagnosis, Computer-Assisted↗
PubMed1996

Optical and digital techniques for enhancing radiographic anatomy for identification of human remains.

Out of a total of more than 300 radiographic identifications made by one of us (JJF), there were 11 cases in which radiologic adjuncts were used because the antemortem radiographs were either miniaturized or because anatomical landmarks could not be clearly discerned. The techniques used included slide projection (two cases), photographic enlargement and enhancement (two cases), digitization (three cases), and digitization with computer enhancement (three cases), commercial digitization (one case). In a 12th case, where identification was made by comparison of antemortem and postmortem film X-rays, the films were digitized as a further evaluation of a commercial system. This is the first reported use of these techniques.

Aged↗
PubMed1995

Digital chest radiography at the University of Chicago: present status and future plans.

Storage-phosphor computed radiography and film digitization systems have been in routine clinical use at the University of Chicago for several years. During this time we have implemented numerous modifications including techniques for scatter reduction, image processing enhancements and display systems to improve the image quality and utility of these devices. We have also evaluated the image quality and functionality of digital systems relative to conventional screen-film radiography. In this paper, we review our experience and summarize our impressions. In addition, we summarize our plans for a rapid transition into picture archiving and communication systems, with hardcopy interpretation being phased out for most modalities over the next 2 to 5 years.

Chicago↗
PubMed1995

Computerized analysis of interstitial infiltrates on chest radiographs: a new scheme based on geometric pattern features and Fourier analysis.

RATIONALE AND OBJECTIVES: Detection of interstitial infiltrates on chest radiographs is difficult and subjective. Therefore, we developed a computerized method to provide quantitative analysis of lung texture to increase diagnostic accuracy. METHODS: Two hundred chest radiographs--100 healthy and 100 abnormal with interstitial infiltrates--were digitized using a laser scanner. They were analyzed by an automated computerized scheme that uses a combination of two methods for detection of interstitial infiltrates: a lung texture analysis based on the Fourier transform and a geometric pattern feature analysis based on filtering techniques. RESULTS: The overall sensitivity and specificity of the computerized scheme were 92% and 90%, respectively. The scheme achieved a sensitivity of 80% in subtle cases (n = 15) and 88% in cases with localized interstitial disease (n = 26), whereas the specificity remained unchanged. There was good correlation between the computer output and the radiologists' severity rating. CONCLUSION: This enhanced computerized scheme exhibits high sensitivity and specificity with a large database.

Adolescent↗
PubMed1995

Computer-aided diagnosis for interstitial infiltrates in chest radiographs: optical-density dependence of texture measures.

We have been developing a computerized scheme for automated detection and characterization of interstitial infiltrates based on the Fourier transform of lung texture. To improve the performance of the scheme, which was developed using digitized screen-film radiographs, optical-density dependence of both the gradient of the film used and the system noise associated with the laser scanner were investigated. Two hundred chest radiographs, including 100 abnormal cases with interstitial infiltrates, were digitized using a laser scanner. The root-mean-square (RMS) variations and the first moments of the power spectra, which correspond to the magnitude and coarseness of lung texture, were determined by Fourier transform of lung textures in numerous regions of interest (ROIs). The RMS variation was dependent upon the average optical density in the ROI, though no obvious trend existed for the first moment of the power spectrum. Dependence of the RMS variations on optical density was corrected for using the gradient curve of the film. Also, system noise associated with the laser scanner was corrected. Results indicated that the specificity was improved from 81% (without correction) to 89% (with corrections), without any loss of sensitivity (90%). Thus, the correspondence between the computer output and consensus interpretation of radiologists was improved with the new scheme compared to the previous one. This improved computerized scheme may be useful to radiologists in detecting interstitial infiltrates in chest radiographs.

Automation↗
PubMed1994

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.

Computer Systems↗
PubMed1994

Computerized detection of pulmonary nodules in computed tomography images.

RATIONALE AND OBJECTIVES: Interpretation of computed tomographic (CT) scans of the lungs is a time-consuming task that involves visual correlation of possible nodules in one section with those in contiguous sections to distinguish actual nodules from blood vessels. Thus, the authors are developing automated methods to detect nodules on CT images of the thorax. METHODS: The computerized technique uses various computer-vision techniques and a priori information of the morphologic characteristics of pulmonary nodules. In each section, the external thoracic wall and lung boundaries are detected, and the features within the lung boundaries are subjected to gray-level thresholding operations. By analyzing the relationships between features arising at different threshold levels with respect to their shape, size, and location, each feature is assigned a likelihood of being a nodule or a vessel. Features in adjacent sections are compared to resolve ambiguous features. Detected nodule candidates are displayed in three dimensions within the lung. RESULTS: The system provided a sensitivity of 94% for nodule detection and an average of 1.25 false-positive results per case. CONCLUSIONS: Continued development of an automated method for detecting pulmonary nodules in CT scans is expected to aid radiologists in the task of locating nodules in three dimensions.

Artificial Intelligence↗