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Biomedical subjects

H MacMahon

Publications and source records attributed to H MacMahon.

At least 109 records · Page 6Linked to original sources
PubMed1978

The diagnostic significance of gallium lung uptake in patients with normal chest radiographs.

Nine patients were encountered with normal chest radiographs, but diffuse bilateral lung uptake of 67Ga-citrate. They were divided into three groups. The first consisted of 6 patients who had lymphoma or leukemia and had had multiple cycles of chemotherapy. Here, abnormal uptake may have resulted from a toxic effect of the drugs or from a low-grade, subclinical infectious process. The 2 patients in the second group were drug addicts and a subradiographic interstitial inflammatory reaction was probably responsible for abnormal uptake. The last patient had diffuse uptake of 67Ga-citrate throughout the lungs two weeks before lymphomatous infiltrates became radiographically visible.

Adult↗
PubMed1976

Bronchial web diagnosed by bronchography.

Bronchial webs are rare lesions which often go unrecognized. The authors describe a patient who presented with right-lower-lobe bronchiectasis and at-electasis secondary to a web in the right-lower-lobe bronchus. This is the first known instance where such a lesion has been demonstrated by bronchography. The etiology of this and similar lesions reported in the literature remains obscure.

Bronchi↗
PubMedDate not supplied

Automated segmentation and visualization of the pulmonary vascular tree in spiral CT angiography: an anatomy-oriented approach based on three-dimensional image analysis.

A new method for automated segmentation of the pulmonary vascular tree in spiral CT angiography was developed based on 3D image analysis techniques and anatomic knowledge. For efficient and effective segmentation, an anatomy-oriented approach was introduced, in which several anatomic structures are segmented sequentially and the properties of each segmented structure are used for the next step of segmentation and for validation of intermediate results. By use of clinical data of 12 patients, parameters for segmentation were analyzed and optimized. The effectiveness of the segmentation method was evaluated through the visual assessment by comparison between images of the segmentation results by volume rendering and images of maximum intensity projection of the original volume data.

Angiography↗
PubMedDate not supplied

Dual-film cassette technique for studying the effect of radiographic image quality on diagnostic accuracy.

In order to investigate the relationship between diagnostic accuracy and radiographic image quality, we have developed a dual-film cassette which produces two radiographs simultaneously with a single exposure. One of these radiographs is of standard quality; the second is of lower quality because of degraded spatial resolution and a significantly lower exposure. We have studied the basic physical properties of the standard and low-dose screen-film systems which we use in the dual-film cassette by comparing their beam hardening, scatter fractions, contrasts, modulation transfer functions (MTFs), and Wiener spectra. The x-ray spectrum incident on the low-dose system contained more high-energy photons than that incident on the standard system, and the scatter fractions for the low-dose system were slightly less than or comparable to those for the standard system. While the radiographic contrast produced by the two systems were generally comparable, the standard system had a slightly higher contrast than the low-dose system in some cases. The MTF of the low-dose system was considerably lower than that of the standard system, and the low-dose system had a noise level considerably greater than did the standard system. Phantom images and clinical radiographs indicated that, for the low-dose system, the image quality degraded significantly.

Humans↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography. I. Automated detection of microcalcifications in mammography.

We have investigated the application of computer-based methods to the detection of microcalcifications in digital mammograms. The computer detection system is based on a difference-image technique in which a signal-suppressed image is subtracted from a signal-enhanced image to remove the structured background in a mammogram. Signal-extraction techniques adapted to the known physical characteristics of microcalcifications are then used to isolate microcalcifications from the remaining noise background. We employ Monte Carlo methods to generate simulated clusters of microcalcifications that are superimposed on normal mammographic backgrounds. This allows quantitative evaluation of detection accuracy of the computer method and the dependence of this accuracy on the physical characteristics of the microcalcifications. Our present computer method can achieve a true-positive cluster detection rate of approximately 80% at a false-positive detection rate of one cluster per image. The potential application of such a computer-aided system to mammographic interpretation is demonstrated by its ability to detect microcalcifications in clinical mammograms.

Algorithms↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs.

We are developing an automated method for determining physical measures of lung textures in digital chest radiographs in order to detect and characterize interstitial lung disease. With this method, the underlying background density variations caused by the gross lung and chest wall anatomy are corrected for in order to isolate the fluctuating patterns of the underlying lung texture for subsequent computer analysis. The power spectrum of lung texture, which is obtained from the two-dimensional Fourier transform, is filtered by the visual system response of the human observer. The magnitude and coarseness (or fineness) of the lung textures are then quantified by the root-mean-square (rms) variation and the first moment of the power spectrum, respectively. Preliminary results indicate that the rms variations and/or the first moments of the texture of abnormal lungs with various interstitial diseases are clearly different from those of normal lungs. Our results suggest strongly that quantitative texture measures calculated from digital chest images may be useful to radiologists in their assessment of interstitial disease.

Fourier Analysis↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields.

We are investigating the characteristic features of lung nodules and the surrounding normal anatomic background in order to develop an algorithm of computer vision for use as an aid in the detection of nodules in digital chest radiographs. Our technique involves an attempt to eliminate the background anatomic structures in the lung fields by means of a difference image approach. Then, feature-extraction techniques, such as tests for circularity, size, and their variation with threshold level, are applied so that suspected nodules can be isolated. Preliminary results of this automated detection scheme yielded high true-positive rates and low false-positive rates in the peripheral lung regions of the chest. This detection scheme, which can assist the final diagnosis by the clinician, has the potential to improve the early detection of lung carcinomas.

Diagnostic Errors↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: classification of normal and abnormal lungs with interstitial disease in chest images.

In order to detect and characterize interstitial disease in the lungs, we are developing an automated method for the determination of physical texture measures, which assess the magnitude and coarseness (or fineness) of lung texture in digital chest radiographs. This method is based on an analysis of the power spectrum of lung texture. We now describe an automated classification method for distinction between normal and abnormal lungs with interstitial disease, in which we employ these texture measures and their data base. This computerized method includes three independent tests, one for a definitely abnormal focal pattern, one for a relatively localized abnormal pattern, and one for a diffuse abnormal pattern. The performance of this computerized classification scheme is compared with that of radiologists by means of receiver operating characteristic (ROC) analysis. Our results indicate that this computerized method can be a valuable aid to radiologists in their assessment of interstitial infiltrates.

Diagnosis, Computer-Assisted↗
PubMedDate not supplied

Computerized detection of pulmonary nodules in digital chest images: use of morphological filters in reducing false-positive detections.

Currently, radiologists can fail to detect lung nodules in up to 30% of actually positive cases. If a computerized scheme could alert the radiologist to locations of suspected nodules, then potentially the number of missed nodules could be reduced. We are developing such a computerized scheme that involves a difference-image approach and various feature-extraction techniques. In this paper, we describe our use of digital morphological processing in the reduction of computer-identified false-positive detections. A feature-extraction technique, which includes the sequential application of nonlinear filters of erosion and dilation, is employed to reduce the camouflaging effect of ribs and vessels on nodule detection. This additional feature-extraction technique reduced the true-positive rate of the computerized scheme by 13% and the false-positive rate by 50%. In a comparison of the scheme with and without the additional feature-extraction technique, inclusion of the additional technique increased the detection sensitivity by about half at the level of three to four false-positive detections per chest image.

False Positive Reactions↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: automated analysis of sizes of heart and lung in chest images.

We are developing an automated method for determining a number of parameters related to the size and shape of the heart and of the lungs in chest radiographs. In order to obtain standard patterns of the cardiac shadow as "gold standards," four radiologists traced their best estimates of the entire contour of the heart, including the largely invisible inferior margin, on 11 radiographs. These contours were analyzed by Fourier transform, and the results were used as a guide to obtain a shift-variant cosine function which was applied to the prediction of the cardiac contour by fitting a limited number of detected heart boundary points. These points were obtained from analysis of edge gradients in two orthogonal directions. A simple observer study indicated that the contours of the heart shadows computed for 60 chest radiographs were generally acceptable to radiologists for estimation of the size and area of the projected heart. We also detected the rib cage and the edges of the diaphragm, which enabled us to determine the projected thoracic area. From these results, we calculated the cardiothoracic ratio and other parameters, such as the ratio of the projected heart area to the projected thoracic area.

Cardiomegaly↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: effect of digital parameters on the accuracy of computerized analysis of interstitial disease in digital chest radiographs.

We are developing a computerized method for measurement of lung texture in digital chest radiographs for detection and characterization of interstitial disease. Physical texture measures are obtained from analysis of the power spectrum of the lung texture. We have investigated the effect of digital parameters such as pixel size, regions of interest size, the number of quantitation levels, and the peak frequency of the visual system response, as well as the effect of the unsharp masking technique on the performance of this computerized method. We calculated the texture measures by changing digital parameters for 100 normal lungs and 100 abnormal lungs in our database. Receiver operating characteristic (ROC) curves were employed for evaluation of the performance of this computerized method for distinguishing between normal and abnormal lungs. We used the area under the ROC curve to compare the detection accuracy for interstitial infiltrates. We believe that the results of this study may be useful as a guide in the design of computerized schemes for lung texture analysis in digital chest radiographs.

Diagnosis, Computer-Assisted↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: automated delineation of posterior ribs in chest images.

In order to facilitate computerized quantitative analysis of digital chest radiographs, an automated method for accurate delineation of posterior ribs in frontal chest images is being developed. This method is based on an analysis of vertical profiles in the lung regions and a statistical analysis of edge gradients and their orientations in small selected regions-of-interest (ROIs). A shift-variant function is fitted to vertical profiles to obtain initial estimates of locations of rib edges. Rib edges are then determined more accurately by analyzing cumulative edge gradients and their orientations in small ROIs that are located adjacent to the initially estimated edges. The present computerized method can achieve a good agreement between the detected and the actual rib structures for posterior ribs in 74% of 50 cases examined. This suggests that automated detection of posterior ribs by a computerized method is feasible, and may be useful for computer-aided diagnostic schemes in the chest.

Adult↗
PubMedDate not supplied

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.

Humans↗
PubMedDate not supplied

The nature and subtlety of abnormal findings in chest radiographs.

All detected abnormal findings were recorded for 1085 consecutive chest x-ray examinations. Each finding was classified by descriptive criteria and graded for subtlety. Accuracy of interpretation was evaluated in a randomized sample of 100 cases using follow-up or multiple readers. Seventy percent of standard examinations and 93% of bedside examinations revealed abnormal findings. Pulmonary infiltrates were the most commonly detected abnormality, being present in 55% of abnormal cases. Noncalcified pulmonary nodules and pneumothoraces were each present in approximately 5% of abnormal cases. The most commonly encountered subtle findings were due to intravenous catheters, pulmonary infiltrates, pneumothoraces, rib lesions, and pulmonary nodules in descending order of frequency. It is concluded that it is reasonable to use selected examples of these findings in observer tests when evaluating new imaging modalities such as digital radiography.

Data Interpretation, Statistical↗
PubMedDate not supplied

Image feature analysis and computer-aided diagnosis in digital radiography: automated detection of pneumothorax in chest images.

In order to aid radiologists in the diagnosis of pneumothorax from chest radiographs, an automated method for detection of subtle pneumothorax is being developed. The computerized method is based on the detection of a fine curved-line pattern, which is a unique feature of radiographic findings of pneumothorax. Initially, regions of interest (ROIs) are determined in each upper lung area, where subtle pneumothoraces commonly appear. The pneumothorax pattern is enhanced by the selection of edge gradients within a limited range of orientations. Rib edges included in this edge-enhanced image are removed, based on the locations of posterior ribs that are determined separately. A subtle curved line due to pneumothorax is then detected by means of the Hough transform. The detected pneumothorax pattern is marked on the chest image displayed on a CRT monitor. With the present computer method applied to 50 chest images (28 normals and 22 abnormals with pneumothorax), we were able to detect 77% of pneumothoraces, with 0.44 false-positives per image.

Humans↗
PubMedDate not supplied

Automated selection of regions of interest for quantitative analysis of lung textures in digital chest radiographs.

In order to implement a computerized scheme for quantitative analysis of interstitial lung disease in chest radiographs in clinical situations, a fully automated method of selecting many square regions of interest (ROIs) in peripheral lung areas are developed. First, the peripheral lung regions are identified, based on the automated detection of lung apices, ribcage edges, and diaphragm. Then a large number of ROIs are selected sequentially by filling in the identified peripheral regions. Finally, those ROIs containing sharp edges are removed based on an edge gradient analysis, for which a gradient-weighted edge orientation histogram is employed. Approximately 200-400 ROIs were automatically selected for each case with this method. The evaluation of using ROC analysis indicated that the automated ROI selection method was effective in quantitative analysis of lung textures in digital chest radiographs.

Biophysical Phenomena↗