Self-masking subtraction tomosynthesis

Iterative difference deblurring algorithm for linear computed laminography

Linear Computed Laminography (LCL) is used to yield slice images of plate-like objects (PLO) for the advantage of short exposure time, high control precision and low cost. Shift and Add (SAA) is a widely used reconstruction algorithm for LCL. One limitation of SAA is that the reconstructed image of the in-focus layer (IFL) contains information from off-focus layers (OFL), resulting in inter-slice aliasing and blurring. In this paper, an Iterative Difference Deblurring (IDD) algorithm based on LCL is proposed to reduce the blur in reconstructed images. The core idea of the IDD algorithm is: contributions from OFL are subtracted from the projection data to remove the blur from the IFL. The corrected projections are then reconstructed using the SAA to remove the superimposed contributions of OFL from the IFL. An iterative approach is utilized to adjust a weighting factor applied during the subtraction stage. The results demonstrate that IDD algorithm can achieve PLO reconstruction in the LCL system under extremely sparse sampling conditions, and can effectively reduce the inter-slice aliasing and blurring.

Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists' information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

Wavelet denoising for quantum noise removal in chest digital tomosynthesis

PURPOSE

Quantum noise impairs image quality in chest digital tomosynthesis (DT). A wavelet denoising processing algorithm for selectively removing quantum noise was developed and tested.

METHODS

A wavelet denoising technique was implemented on a DT system and experimentally evaluated using chest phantom measurements including spatial resolution. Comparison was made with an existing post-reconstruction wavelet denoising processing algorithm reported by Badea et al. (Comput Med Imaging Graph 22:309-315, 1998). The potential DT quantum noise decrease was evaluated using different exposures with our technique (pre-reconstruction and post-reconstruction wavelet denoising processing via the balance sparsity-norm method) and the existing wavelet denoising processing algorithm. Wavelet denoising processing algorithms such as the contrast-to-noise ratio (CNR), root mean square error (RMSE) were compared with and without wavelet denoising processing. Modulation transfer functions (MTF) were evaluated for the in-focus plane. We performed a statistical analysis (multi-way analysis of variance) using the CNR and RMSE values.

RESULTS

Our wavelet denoising processing algorithm significantly decreased the quantum noise and improved the contrast resolution in the reconstructed images (CNR and RMSE: pre-balance sparsity-norm wavelet denoising processing versus existing wavelet denoising processing, P<0.05; post-balance sparsity-norm wavelet denoising processing versus existing wavelet denoising processing, P<0.05; CNR: with versus without wavelet denoising processing, P<0.05). The results showed that although MTF did not vary (thus preserving spatial resolution), the existing wavelet denoising processing algorithm caused MTF deterioration.

CONCLUSIONS

A balance sparsity-norm wavelet denoising processing algorithm for removing quantum noise in DT was demonstrated to be effective for certain classes of structures with high-frequency component features. This denoising approach may be useful for a variety of clinical applications for chest digital tomosynthesis when quantum noise is present.

Weighted simultaneous algebraic reconstruction technique for tomosynthesis imaging of objects with high-attenuation features

PURPOSE

This paper introduces a nonlinear weighting scheme into the backprojection operation within the simultaneous algebraic reconstruction technique (SART). It is designed for tomosynthesis imaging of objects with high-attenuation features in order to reduce limited angle artifacts.

METHODS

The algorithm estimates which projections potentially produce artifacts in a voxel. The contribution of those projections into the updating term is reduced. In order to identify those projections automatically, a four-dimensional backprojected space representation is used. Weighting coefficients are calculated based on a dissimilarity measure, evaluated in this space. For each combination of an angular view direction and a voxel position an individual weighting coefficient for the updating term is calculated.

RESULTS

The feasibility of the proposed approach is shown based on reconstructions of the following real three-dimensional tomosynthesis datasets: a mammography quality phantom, an apple with metal needles, a dried finger bone in water, and a human hand. Datasets have been acquired with a Siemens Mammomat Inspiration tomosynthesis device and reconstructed using SART with and without suggested weighting. Out-of-focus artifacts are described using line profiles and measured using standard deviation (STD) in the plane and below the plane which contains artifact-causing features. Artifacts distribution in axial direction is measured using an artifact spread function (ASF). The volumes reconstructed with the weighting scheme demonstrate the reduction of out-of-focus artifacts, lower STD (meaning reduction of artifacts), and narrower ASF compared to nonweighted SART reconstruction. It is achieved successfully for different kinds of structures: point-like structures such as phantom features, long structures such as metal needles, and fine structures such as trabecular bone structures.

CONCLUSIONS

Results indicate the feasibility of the proposed algorithm to reduce typical tomosynthesis artifacts produced by high-attenuation features. The proposed algorithm assigns weighting coefficients automatically and no segmentation or tissue-classification steps are required. The algorithm can be included into various iterative reconstruction algorithms with an additive updating strategy. It can also be extended to computed tomography case with the complete set of angular data.

Initial evaluation of linear and spatially oriented planar images from a new dental panoramic system based on tomosynthesis

OBJECTIVE

The purpose of this study was to describe a newly developed dental panoramic system based on the tomosynthesis method and to validate the accuracy of linear and spatially oriented planar images.

STUDY DESIGN

An original robotic mechanism incorporating a new high-speed cadmium-telluride (CdTe) semiconductor detector was fabricated to acquire panoramic images (raw data). The shift-and-add tomosynthesis method was applied to facilitate changes in the depth of the panoramic imaging layer. Using the texture mapping method, planar and spatially oriented images were reconstructed along a custom curved imaging plane. Using a custom phantom and dry skulls, the accuracy of selected linear measurements was evaluated.

RESULTS

Preliminary measurements demonstrated acceptable linear accuracy in reconstructed panoramic images with variations <5%.

CONCLUSIONS

This preliminary investigation demonstrates that dental panoramic images acquired by a novel robotic mechanism and CdTe detector using a tomosynthesis method provides planar and spatially oriented images with an image quality that may be acceptable for dental practice.

Intravenous pyelogram artefacts unique to digital tomosynthesis reconstruction

Recent advances in technology have led to the realisation of digital tomosynthesis (DT) imaging in routine investigations such as intravenous pyelogram (IVP). The major advantage this technology has over other technologies is its ability to perform a retrospective reconstruction of an arbitrary number of coronal image planes from a single data set consisting of a series of low dose discrete projections acquired over a limited angular range using a stationary detector. It is well documented that because DT relies on an angular limited acquisition, the data set is incomplete. This, in combination with the image reconstruction algorithm, results in reconstructed images containing non-focused information from outside the immediate focal plane. This article describes and suggests the cause of two artefacts unique to DT that cannot be explained by blurring alone. We believe the two artefacts are caused by breathing during data acquisition together with a combination of other factors, including the anatomy of the renal system, the method of data acquisition and the reconstructive algorithm used. This could lead to the unaware reporting radiologist falsely diagnosing a duplex collecting system. To avoid these artefacts, we recommend DT IVP should only be used in patients who can adequately perform a breath-hold for the duration of the data acquisition. In addition, we suggest that the study should be performed with breath-held following expiration.

X-ray tomosynthesis: a review of its use for breast and chest imaging

Tomosynthesis is a three-dimensional imaging technique based on the reconstruction of several planar radiographs. During the image acquisition in tomosynthesis, the X-ray tube moves around the detector which is often stationary, and a number of projection images are taken from different angles. Individual slices from the reconstructed volume can be studied. With the effective reduction of the visibility of the overlapping normal tissue, the detection of pathological lesions is improved when compared with projection radiography. Up to now, tomosynthesis has mainly been used for breast and chest examinations and, to some extent, also for orthopaedic, angiographic and dental investigations. For chest, tomosynthesis is used as an alternative to computed tomography with significantly lower cost and radiation dose to the patient. Breast tomosynthesis has, in several studies, proved to be an effective tool for improving detection of breast lesions. As tomosynthesis has many properties that make it suitable as a modality for screening, including good diagnostic performance, short examination time and low radiation dose, it is a strong competitor to the current gold standard breast screening modality, i.e. mammography. In this paper, the principles of tomosynthesis will be presented as well as a few clinical studies showing the potential role of tomosynthesis in clinical routine examinations.

Chest tomosynthesis: technical principles and clinical update

Digital tomosynthesis is a radiographic technique that can produce an arbitrary number of section images of a patient from a single pass of the X-ray tube. It utilizes a conventional X-ray tube, a flat-panel detector, a computer-controlled tube mover, and special reconstruction algorithms to produce section images. While it does not have the depth resolution of computed tomography (CT), tomosynthesis provides some of the tomographic benefits of CT but at lower cost and radiation dose than CT. Compared to conventional chest radiography, chest tomosynthesis results in improved visibility of normal structures such as vessels, airway and spine. By reducing visual clutter from overlying normal anatomy, it also enhances detection of small lung nodules. This review article outlines the components of a tomosynthesis system, discusses results regarding improved lung nodule detection from the recent literature, and presents examples of nodule detection from a clinical trial in human subjects. Possible implementation strategies for use in clinical chest imaging are discussed.

Tomosynthesis imaging: at a translational crossroads

Tomosynthesis is a decades-old technique for section imaging that has seen a recent upsurge in interest due to its promise to provide three-dimensional information at lower dose and potentially lower cost than CT in certain clinical imaging situations. This renewed interest in tomosynthesis began in the late 1990s as a new generation of flat-panel detectors became available; these detectors were the one missing piece of the picture that had kept tomosynthesis from enjoying significant utilization earlier. In the past decade, tomosynthesis imaging has been investigated in a variety of clinical imaging situations, but the two most prominent have been in breast and chest imaging. Tomosynthesis has the potential to substantially change the way in which breast cancer and pulmonary nodules are detected and managed. Commercial tomosynthesis devices are now available or on the horizon. Many of the remaining research activities with tomosynthesis will be translational in nature and will involve physicist and clinician alike. This overview article provides a forward-looking assessment of the translational questions facing tomosynthesis imaging and anticipates some of the likely research and clinical activities in the next five years.

Image artifacts in digital breast tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach

Digital breast tomosynthesis (DBT) is a three-dimensional (3D) x-ray imaging modality that reconstructs image slices parallel to the detector plane. Image acquisition is performed using a limited angular range (less than 50 degrees) and a limited number of projection views (less than 50 views). Due to incomplete data sampling, image artifacts are unavoidable in DBT. In this preliminary study, the image artifacts in DBT were investigated systematically using a linear system approximation. A cascaded linear system model of DBT was developed to calculate the 3D presampling modulation transfer function (MTF) with different image acquisition geometries and reconstruction filters using a filtered backprojection (FBP) algorithm. A thin, slanted tungsten (W) wire was used to measure the presampling MTF of the DBT system in the cross-sectional plane defined by the thickness (z-) and tube travel (x-) directions. The measurement was in excellent agreement with the calculation using the model. A small steel bead was used to calculate the artifact spread function (ASF) of the DBT system. The ASF was correlated with the convolution of the two-dimensional (2D) point spread function (PSF) of the system and the object function of the bead. The results showed that the cascaded linear system model can be used to predict the magnitude of image artifacts of small, high-contrast objects with different image acquisition geometry and reconstruction filters.

A comparison of reconstruction algorithms for C-arm mammography tomosynthesis

Digital tomosynthesis is an imaging technique to produce a tomographic image from a series of angular digital images in a manner similar to conventional focal plane tomography. Unlike film focal plane tomography, the acquisition of the data in a C-arm geometry causes the image receptor to be positioned at various angles to the reconstruction tomogram. The digital nature of the data allows for input images to be combined into the desired plane with the flexibility of generating tomograms of many separate planes from a single set of input data. Angular datasets were obtained of a low contrast detectability (LCD) phantom and cadaver breast utilizing a Lorad stereotactic biopsy unit with a coupled source and digital detector in a C-arm configuration. Datasets of 9 and 41 low-dose projections were collected over a 30 degrees angular range. Tomographic images were reconstructed using a Backprojection (BP) algorithm, an Iterative Subtraction (IS) algorithm that allows the partial subtraction of out-of-focus planes, and an Algebraic Reconstruction (AR) algorithm. These were compared with single view digital radiographs. The methods' effectiveness at enhancing visibility of an obscured LCD phantom was quantified in terms of the Signal to Noise Ratio (SNR), and Signal to Background Ratio (SBR), all normalized to the metric value for the single projection image. The methods' effectiveness at removing ghosting artifacts in a cadaver breast was quantified in terms of the Artifact Spread Function (ASF). The technology proved effective at partially removing out of focus structures and enhancing SNR and SBR. The normalized SNR was highest at 4.85 for the obscured LCD phantom, using nine projections and IS algorithm. The normalized SBR was highest at 23.2 for the obscured LCD phantom, using 41 projections and an AR algorithm. The highest normalized metric values occurred with the obscured phantom. This supports the assertion that the greatest value of tomosynthesis is in imaging fibroglandular breasts. The ASF performance was best with the AR technique and nine projections.

Cone-beam mammo-computed tomography from data along two tilting arcs

Over the past several years there has been an increasing interest in cone-beam computed tomography (CT) for breast imaging. In this article, we propose a new scheme for theoretically exact cone-beam mammo-CT and develop a corresponding Katsevich-type reconstruction algorithm. In our scheme, cone-beam scans are performed along two tilting arcs to collect a sufficient amount of information for exact reconstruction. In our algorithm, cone-beam data are filtered in a shift-invariant fashion and then weighted backprojected into the three-dimensional space for the final reconstruction. Our approach has several desirable features, including tolerance of axial data truncation, efficiency in sequential/parallel implementation, and accuracy for quantitative analysis. We also demonstrate the system performance and clinical utility of the proposed technique in numerical simulations.

Voting strategy for artifact reduction in digital breast tomosynthesis

Artifacts are observed in digital breast tomosynthesis (DBT) reconstructions due to the small number of projections and the narrow angular range that are typically employed in tomosynthesis imaging. In this work, we investigate the reconstruction artifacts that are caused by high-attenuation features in breast and develop several artifact reduction methods based on a "voting strategy." The voting strategy identifies the projection(s) that would introduce artifacts to a voxel and rejects the projection(s) when reconstructing the voxel. Four approaches to the voting strategy were compared, including projection segmentation, maximum contribution deduction, one-step classification, and iterative classification. The projection segmentation method, based on segmentation of high-attenuation features from the projections, effectively reduces artifacts caused by metal and large calcifications that can be reliably detected and segmented from projections. The other three methods are based on the observation that contributions from artifact-inducing projections have higher value than those from normal projections. These methods attempt to identify the projection(s) that would cause artifacts by comparing contributions from different projections. Among the three methods, the iterative classification method provides the best artifact reduction; however, it can generate many false positive classifications that degrade the image quality. The maximum contribution deduction method and one-step classification method both reduce artifacts well from small calcifications, although the performance of artifact reduction is slightly better with the one-step classification. The combination of one-step classification and projection segmentation removes artifacts from both large and small calcifications.

A comparison of reconstruction algorithms for breast tomosynthesis

Three algorithms for breast tomosynthesis reconstruction were compared in this paper, including (1) a back-projection (BP) algorithm (equivalent to the shift-and-add algorithm), (2) a Feldkamp filtered back-projection (FBP) algorithm, and (3) an iterative Maximum Likelihood (ML) algorithm. Our breast tomosynthesis system acquires 11 low-dose projections over a 50 degree angular range using an a-Si (CsI:Tl) flat-panel detector. The detector was stationary during the acquisition. Quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) were used for quantitative evaluation of tomosynthesis reconstructions. The results of the quantitative evaluation were in good agreement with the results of the qualitative assessment. In patient imaging, the superimposed breast tissues observed in two-dimensional (2D) mammograms were separated in tomosynthesis reconstructions by all three algorithms. It was shown in both phantom imaging and patient imaging that the BP algorithm provided the best SDNR for low-contrast masses but the conspicuity of the feature details was limited by interplane artifacts; the FBP algorithm provided the highest edge sharpness for microcalcifications but the quality of masses was poor; the information of both the masses and the microcalcifications were well restored with balanced quality by the ML algorithm, superior to the results from the other two algorithms.

Temporal performance of amorphous selenium mammography detectors

We investigated temporal performance of amorphous selenium (a-Se) detectors specifically designed for mammographic imaging. Our goal is to quantify the inherent lag and ghosting of a-Se photoconductor as a function of imaging conditions. Two small area electroded a-Se samples, one positively and the other negatively biased on the entrance side of x rays, were used in the experiments. The study of lag and ghosting was performed by delivering a number of raw exposures as experienced in screening mammography to the samples at different electric field strength E(Se) while measuring the current through the a-Se sample. Ghosting at different operational conditions was quantified as the percentage x-ray sensitivity (x-ray generated photocurrent measured from the sample) reduction compared to before irradiation. Lag was determined by measuring the residual current of a-Se at a given time after the end of each x-ray exposure. Both lag and ghosting were measured as a function of E(Se) and cumulative exposure. The values of E(Se) used in our experiments ranged from 1 to 20 V/microm. It was found that ghosting increases with exposure and decreases with E(Se) for both samples because of the dominant effect of recombination between trapped electrons and x-ray generated holes. Lag on the other hand has different dependence on E(Se) and cumulative exposure. At E(Se) < or = 10 V/microm, the first frame lag for both samples changed slowly with cumulative exposure, with a range of 0.2%-1.7% for the positively biased sample and 0.5%-8% for the negatively biased sample. Overall the positively biased sample has better temporal performance than the negatively biased sample due to the lower density of trapped electrons. The impact of time interval between exposures on the temporal performance was also investigated. Recovery of ghosting with longer time interval was observed, which was attributed to the neutralization of trapped electrons by injected holes through dark current.

Digital x-ray tomosynthesis: current state of the art and clinical potential

Digital x-ray tomosynthesis is a technique for producing slice images using conventional x-ray systems. It is a refinement of conventional geometric tomography, which has been known since the 1930s. In conventional geometric tomography, the x-ray tube and image receptor move in synchrony on opposite sides of the patient to produce a plane of structures in sharp focus at the plane containing the fulcrum of the motion; all other structures above and below the fulcrum plane are blurred and thus less visible in the resulting image. Tomosynthesis improves upon conventional geometric tomography in that it allows an arbitrary number of in-focus planes to be generated retrospectively from a sequence of projection radiographs that are acquired during a single motion of the x-ray tube. By shifting and adding these projection radiographs, specific planes may be reconstructed. This topical review describes the various reconstruction algorithms used to produce tomosynthesis images, as well as approaches used to minimize the residual blur from out-of-plane structures. Historical background and mathematical details are given for the various approaches described. Approaches for optimizing the tomosynthesis image are given. Applications of tomosynthesis to various clinical tasks, including angiography, chest imaging, mammography, dental imaging and orthopaedic imaging, are also described.

Comparison of tomosynthesis methods used with digital mammography

RATIONALE AND OBJECTIVES

The authors performed this study to investigate the potential applicability of tomosynthesis to digital mammography. Four methods of tomosynthesis-tuned aperture computed tomography (TACT)-backprojection, TACT-iterative restoration, iterative reconstruction with expectation maximization, and Bayesian smoothing-were compared to planar mammography and analyzed in terms of their contrast-detail characteristics. Specific comparisons between the tomosynthesis methods were not attempted in this study.

MATERIALS AND METHODS

A full-field, amorphous, silicon-based, flat-panel digital mammographic system was used to obtain planar and tomosynthesis projection images. A composite tomosynthesis phantom with a centrally located contrast-detail insert was used as the object of interest. The total exposure for multiple views with tomosynthesis was always equal to or less than that for the planar technique. Algorithms were used to reconstruct the object from the acquired projections.

RESULTS

Threshold contrast characteristics with all tomosynthesis reconstruction methods were significantly better than those with planar mammography, even when planar mammography was performed at more than twice the exposure level. Reduction of out-of-plane structural components was observed in all the tomosynthesis methods analyzed.

CONCLUSION

The contrast-detail trends of all the tomosynthesis methods analyzed in this study were better than those of planar mammography. Further optimization of the algorithms could lead to better image reconstruction, which would improve visualization of valuable diagnostic information.

Three-dimensional localisation based on projectional and tomographic image correlation: an application for digital tomosynthesis

Accurate three-dimensional tumor localisation in Radiotherapy, is critical to the treatment outcome, particularly when high dose gradients are present. A number of techniques have been proposed for the localisation of anatomical structures or markers. The present study proposes an approach to a concurrent maximisation of localisation accuracy and efficiency by correlation of tomographic and projectional images. The method introduces an element of direct verification and interactive optimisation of the process. Tomographic images are used for the identification of a point of interest. Its position is computed within the treatment co-ordinate system and verification of this position is achieved by obtaining the beam's eye view of the identified point on two projection radiographs. The key element of the approach is that all images used should be part of one single image data set. The implementation of this localisation method, as part of the functionality of a Digital Tomosynthesis prototype, has provided an integrated facility for localisation, of optimised accuracy and precision, while easy and efficient to use. The considerations are general and apply in principle to any imaging system that can augment tomographic images with projections.

A wavelet-based method for removal of out-of-plane structures in digital tomosynthesis

Reconstructed images in digital tomosynthesis (DTS) are affected by artifacts due to blur from planes other than the fulcrum plane. A wavelet-based method has been developed for the discrimination and subsequent removal of unrelated structures from the reconstructed plane. The approach exploits both the specific pattern of noise in DTS and the spatial locality of the wavelet transformation. The technique was implemented on a DTS clinical protoype system. Experimental evaluation on angiographic types of images demonstrated excellent noise differentiation and elimination. The method is therefore particularly useful for certain medical imaging applications such as vascular DTS imaging.

Blur reduction of conventional film-based tomograms for pre-surgical evaluation of potential mandibular implant sites

The usefulness of motion-based cross-sectional tomography to evaluate osseous support and adjacent anatomical structures for dental implant placement is limited by the inherent blurring in these images. The goal of this study was to develop a method to remove blurring while permitting accurate dimensional analysis of the potential implant site. Defined regions (anterior, cuspid, premolar, molar) on two preserved human mandibles were imaged using cross-sectional linear tomography. Algorithms were developed as a personal computer application to remove the blur and to aid in identification of the cortical plate borders and the mandibular canal. The data set of eight tomograms was digitized and the blur reduced with the developed algorithm. An operator measured the height and width of the mandible on each original tomogram and each deblurred tomogram in triplicate. Method error was calculated as the difference between direct caliper measurements of the respective skull regions and image measurements of height and width for both the original digitized tomograms and the deblurred tomograms. Method error using the original images (height: -2.72 +/- 2.15 mm; width: -0.58 +/- 1.36 mm) compared to the deblurred tomograms (height: -0.58 +/- 1.16 mm; width: 0.37 +/- 0.59 mm) was significantly greater for both height (t-test level of significance, P = 0.0047) and width (t-test level of significance, P = 0.0001). These findings suggest that the method developed may greatly improve the ability of clinicians to accurately assess the implant site using cross-sectional film-based linear tomograms.

Digital tomosynthesis: phantom and patient studies with a prototype unit

A prototype digital linear tomographic system has been developed and used in patient and phantom studies. Phantom work demonstrated 0.6 line pairs/mm of spatial resolution, a slice thickness of 5 mm to 6 mm, range of reconstruction of 1 cm to 20 cm above tabletop, reconstruction time of 2 to 45 seconds per slice depending on matrix size, and a 280 mm field of view at the tabletop. Patient studies were conducted in three categories: renal imaging in 8 patients during intravenous urography (IVU); central airways imaging in 4 patients undergoing laser resection of endobronchial tumor; the knee of one volunteer. The digital tomograms from IVU studies were similar to the conventional film tomograms, and the only parenchymal abnormality, a renal cyst, was identified by both modalities. Digital tomograms of the mediastinum were superior to the chest radiographs in determining the patency of the central airways. With further development, digital tomosynthesis could offer greater spatial resolution, faster reconstructions, and less radiation than computed tomography (CT) or conventional tomography.