Biomedical subjects

K Doi

Publications and source records attributed to K Doi.

At least 955 records · Page 53Linked to original sources

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. 2. Computerized determination of vessel sizes in digital subtraction angiography.

We developed an iterative deconvolution technique to determine the size of a "blurred" vessel in a digital subtraction angiographic (DSA) image by taking into account the unsharpness of the DSA system. Initially, a region of interest over a small segment of the contrast-filled vessel was selected in a DSA image, and the center line of the opacified vessel was determined by polynomial curve fitting of the locations of the peak pixel values along the vessel image. The blurred image profile was then obtained from pixel values across the vessel in a direction perpendicular to the center line. This measured profile was compared iteratively with a calculated profile for various size vessels, which was obtained from a cylindrical vessel model and from the line spread function, until the root-mean-square difference between the two profiles was minimized. The size of a cylindrical vessel yielding the matched profile was considered the best estimate of the unknown vessel size. Studies with a blood vessel phantom indicated that vessels larger than 0.5 mm could be measured with an accuracy and precision of approximately 0.1 mm, which is about 1/3 of the pixel size used in our DSA system. Details of our approach and some clinical vessel images with and without simulated stenotic lesions are presented.

Angiography↗

PubMedDate not supplied

Investigation of basic imaging properties in digital radiography. 11. Multiple slit-beam imaging technique with image intensifier-TV digital system.

We are developing a digital x-ray imaging system using a multiple slit assembly (MSA) and an image intensifier (II)-TV digital system. The advantage of this approach is that the scatter from an object and the veiling glare in the II-TV system can be reduced significantly while the x-ray utilization is maintained much better than that with a single slit-beam technique. The quality of reconstructed images is related to many parameters such as the slit width, the lead spacer, the number of image frames, and the reconstruction algorithm. In this study, reduction of scatter and veiling glare was measured quantitatively, and image artifacts were analyzed. It was found that the fraction of scatter and veiling glare can be reduced to approximately 0.01-0.1 by use of the MSA imaging technique, and that the magnitude of the fractions is strongly dependent upon the slit width and the lead spacer of the MSA used. The artifacts are caused by inaccuracies in the slit width, lead spacer, and scan motion, and by undersampling of image data. The overlap scanning technique was effective in reducing the magnitude of these artifacts in the reconstructed image.

Humans↗

PubMedDate not supplied

Optical image processing with liquid-crystal display for image intensifier/television systems.

We have studied the effect of real-time optical image processing (OIP) in an image intensifier/television (II-TV) radiographic imaging system by using a liquid-crystal display (LCD) placed between the II and the TV camera. The LCD compresses the dynamic range of the transmitted image by modulating the spatial distribution of the light intensity of the image from the output phosphor of the II. The degree of dynamic-range compression can be designed so that the dependence of the signal-to-noise ratio (SNR) of the LCD-TV system on x-ray intensity matches that of the quantum noise. We measured the physical properties of an LCD and evaluated its capability for OIP. Our experimental results demonstrate that it is feasible to use an LCD to compress the dynamic range and to improve the SNR of the image. The advantages of implementing OIP with an LCD in image acquisition systems in which a TV camera is used are discussed.

Humans↗

PubMedDate not supplied

Improvement of spatial resolution properties of image intensifier-TV digital systems with a multiple-narrow-slit beam imaging technique.

Multiple-slit beam imaging technique with an image intensifier (II)-TV digital system has been developed to remove scatter and veiling glare while high x-ray beam utilization is maintained. Although the contrast and signal-to-noise ratio (SNR) are improved with this technique, the overall image quality obtainable with an II-TV digital system is still limited due to low spatial resolution, which is mainly caused by the large pixel size, i.e., by the small matrix size used. In order to overcome the limitation of the pixel size, we have developed a new method of improving the resolution properties of the II-TV digital system by use of a multiple-slit assembly (MSA) having a narrow slit width. When the slit width of the MSA is narrower than the pixel size of the II-TV digital system, two signals from a given slit due to different MSA placements may be detected by the same pixel in different image frames, and the detected signals of the slit images are mapped to a large matrix. In this way, the spatial resolution in the direction perpendicular to the slit openings can be improved along with the increased contrast and SNR as the scatter and veiling glare can be removed. Experimental results are presented, and the effect of an anisotropic resolution property on the overall image quality is discussed.

Hand↗

PubMedDate not supplied

Localization of inter-rib spaces for lung texture analysis and computer-aided diagnosis in digital chest images.

An automated method for sampling lung textures in digital posterior/anterior chest images is being developed for use in computer-aided diagnosis of interstitial pulmonary diseases. In our present approach, two vertical profiles in the periphery of both lungs are fitted with a shift-variant sinusoidal function from which we estimate locations of posterior ribs and inter-rib spaces. Regions of interest (ROI's) for sampling lung textures are then automatically centered on the calculated locations of inter-rib spaces. In tests with 66 chest images, the overall success rate in placing 6.4 mm X 6.4 mm ROI's within inter-rib spaces with this method was 71%, with an average of 18 ROI's selected in 4-5 s/image by a VAX11/750 computer. When four additional alternative ROI's were selected on the sides of each original ROI, the success rate in having at least one ROI correctly located in an inter-rib space increased to 94%. Since we are still developing a fully automated sampling method, the present approach has been incorporated into a semiautomated method that is currently being used to sample lung textures from a large number of clinical cases.

Humans↗

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

Investigation of basic imaging properties in digital radiography. 12. Effect of matrix configuration on spatial resolution.

We investigated the effects of three matrix configurations (a conventional 512 X 512 matrix, a double-sampling matrix, and a high-resolution 1024 X 1024 matrix) on the resolution properties of an image intensifier (II)-TV digital radiographic imaging system. Expressions for the optical transfer function were derived theoretically for each of the three matrix configurations, and the corresponding digital modulation transfer functions (MTF's) were calculated using the measured MTF's of the presampling analog components and the parameters of the digital system. In addition, digital images of a star pattern phantom and a hand phantom were obtained with the II-TV system for each matrix type. From our results, we conclude that, in order to increase the resolution of an II-TV digital imaging system, it is necessary not only to increase the matrix size, but also to improve the resolution capabilities of analog components such as the II and/or TV camera. In addition, if the system cannot be upgraded to a 1024 X 1024 matrix configuration, a double-sampling technique with an 512 X 512 matrix may be employed.

Hand↗

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

Contrast enhancement of noisy images by windowing: limitations due to the finite dynamic range of the display system.

A theoretical model has been developed to explain the effects of simple linear windowing on the apparent contrasts of signals in displayed digital images. The model predicts, and experimental results demonstrate, that the effective displayed contrast of a digital radiographic signal depends in a complex way upon interactions among the endpoints of the display scale, the signal contrast and noise level of the original data, the window center and display center selected, and the contrast enhancement factor applied. The results obtained from this work apply quantitatively to the highly idealized situation in which (i) a uniform signal is superimposed on a uniform background containing Gaussian pixel-value noise, and (ii) a linear (or exponential) relationship exists between the optical density of a film display (or the light intensity of a luminous display) and pixel value in some finite range. However, the qualitative effects demonstrated here may be expected to arise in a broad variety of situations involving strong digital contrast enhancement.

Computer Simulation↗

PubMedDate not supplied

Investigation of basic imaging properties in digital radiography. 13. Effect of simple structured noise on the detectability of simulated stenotic lesions.

We investigated the effects of structured background noise on the detectability of stenotic lesions. Digital subtraction angiographic (DSA) images of stenotic blood vessels were simulated and superimposed onto uniform noise samples. Eighteen-alternative forced choice (18-AFC) experiments were employed to determine the detectability of the stenotic lesion in the structured-noise background of a blood vessel. In this study, the dependence of detectability on lesion size, vessel size, and incident x-ray exposure was examined. Our results indicate that the presence of structured noise in an image will reduce the detectability of a lesion. However, the relative performance of an observer when the lesion size and incident exposure were varied was the same with and without the presence of the structured background. Thus, conclusions obtained previously with regard to changes in the detectability of a lesion in the presence of uniform background noise can be applied directly to conditions in which simple structured anatomic background is present.

Angiography↗

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

Measurement of the presampling modulation transfer function of film digitizers using a curve fitting technique.

A curve fitting technique combined with an angulated slit image has been developed for the measurement of the presampling modulation transfer function (MTF) of film digitizers. The noisy line spread functions (LSFs) acquired from an angulated slit image are fitted using a combination of two functions by means of a nonlinear least-square fitting technique. The parameters in the model function for each LSF are obtained by minimizing the residual root mean square (RMS), and then averaged over all the LSF fittings. The resulting analytical function is representative of the continuous presampled LSF. We have found that a combination of Gaussian and exponential functions provides a good fit to the LSFs obtained with film digitizers. The corresponding analytical Fourier transformation of the model function yields the presampling MTF, without Nyquist frequency limitation. Measurements of spatial resolution properties using this method were performed for two laser scanners and an optical drum scanner.

Biophysical Phenomena↗

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

Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images.

A computerized scheme is being developed for the detection of masses in digital mammograms. Based on the deviation from the normal architectural symmetry of the right and left breasts, a bilateral subtraction technique is used to enhance the conspicuity of possible masses. The scheme employs two pairs of conventional screen-film mammograms (the right and left mediolateral oblique views and craniocaudal views), which are digitized by a TV camera/Gould digitizer. The right and left breast images in each pair are aligned manually during digitization. A nonlinear bilateral subtraction technique that involves linking multiple subtracted images has been investigated and compared to a simple linear subtraction method. Various feature-extraction techniques are used to reduce false-positive detections resulting from the bilateral subtraction. The scheme has been evaluated using 46 pairs of clinical mammograms and was found to yield a 95% true-positive rate at an average of three false-positive detections per image. This preliminary study indicates that the scheme is potentially useful as an aid to radiologists in the interpretation of screening mammograms.

Breast Neoplasms↗

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↗