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Biomedical subjects

David Conover

Publications and source records attributed to David Conover.

3 recordsLinked to original sources
PubMed2004

Image denoising based on multiscale singularity detection for cone beam CT breast imaging.

It was recently reported that the real-time flat panel detector-based cone-beam computed tomography (CBCT) breast imaging can help improve the detectability of small breast tumors with an X-ray dose comparable to that of the conventional mammography. In this paper, an efficient denoising algorithm is proposed to further reduce the X-ray exposure level required by a CBCT scan to acquire acceptable image quality. The proposed wavelet-based denoising algorithm possesses three significant characteristics: 1) wavelet coefficients at each scale are classified into two categories: irregular coefficients, and edge-related and regular coefficients; 2) noise in irregular coefficients is reduced as much as possible without producing artifacts to the denoised images; and 3) for the edge-related and regular coefficients, if they are at the first decomposition level, they are further denoised, otherwise, no modifications are made to them so as to obtain good visual quality for diagnosis. By applying the proposed denoising algorithm to the filtered projection images, the X-ray exposure level necessary for the CBCT scan can be reduced by up to 60% while obtaining clinically acceptable image quality. This denoising result indicates that in the clinical application of CBCT breast imaging, the patient radiation dose can be significantly reduced.

Algorithms↗
PubMed2004

X-ray scatter correction algorithm for cone beam CT imaging.

Developing and optimizing an x-ray scatter control and reduction technique is one of the major challenges for cone beam computed tomography (CBCT) because CBCT will be much less immune to scatter than fan-beam CT. X-ray scatter reduces image contrast, increases image noise and introduces reconstruction error into CBCT. To reduce scatter interference, a practical algorithm that is based upon the beam stop array technique and image sequence processing has been developed on a flat panel detector-based CBCT prototype scanner. This paper presents a beam stop array-based scatter correction algorithm and the evaluation results through phantom studies. The results indicate that the beam stop array-based scatter correction algorithm is practical and effective to reduce and correct x-ray scatter for a CBCT imaging task.

Algorithms↗
PubMed2003

Flat panel detector-based cone beam computed tomography with a circle-plus-two-arcs data acquisition orbit: preliminary phantom study.

Cone beam computed tomography (CBCT) has been investigated in the past two decades due to its potential advantages over a fan beam CT. These advantages include (a) great improvement in data acquisition efficiency, spatial resolution, and spatial resolution uniformity, (b) substantially better utilization of x-ray photons generated by the x-ray tube compared to a fan beam CT, and (c) significant advancement in clinical three-dimensional (3D) CT applications. However, most studies of CBCT in the past are focused on cone beam data acquisition theories and reconstruction algorithms. The recent development of x-ray flat panel detectors (FPD) has made CBCT imaging feasible and practical. This paper reports a newly built flat panel detector-based CBCT prototype scanner and presents the results of the preliminary evaluation of the prototype through a phantom study. The prototype consisted of an x-ray tube, a flat panel detector, a GE 8800 CT gantry, a patient table and a computer system. The prototype was constructed by modifying a GE 8800 CT gantry such that both a single-circle cone beam acquisition orbit and a circle-plus-two-arcs orbit can be achieved. With a circle-plus-two-arcs orbit, a complete set of cone beam projection data can be obtained, consisting of a set of circle projections and a set of arc projections. Using the prototype scanner, the set of circle projections were acquired by rotating the x-ray tube and the FPD together on the gantry, and the set of arc projections were obtained by tilting the gantry while the x-ray tube and detector were at the 12 and 6 o'clock positions, respectively. A filtered backprojection exact cone beam reconstruction algorithm based on a circle-plus-two-arcs orbit was used for cone beam reconstruction from both the circle and arc projections. The system was first characterized in terms of the linearity and dynamic range of the detector. Then the uniformity, spatial resolution and low contrast resolution were assessed using different phantoms mainly in the central plane of the cone beam reconstruction. Finally, the reconstruction accuracy of using the circle-plus-two-arcs orbit and its related filtered backprojection cone beam volume CT reconstruction algorithm was evaluated with a specially designed disk phantom. The results obtained using the new cone beam acquisition orbit and the related reconstruction algorithm were compared to those obtained using a single-circle cone beam geometry and Feldkamp's algorithm in terms of reconstruction accuracy. The results of the study demonstrate that the circle-plus-two-arcs cone beam orbit is achievable in practice. Also, the reconstruction accuracy of cone beam reconstruction is significantly improved with the circle-plus-two-arcs orbit and its related exact CB-FPB algorithm, as compared to using a single circle cone beam orbit and Feldkamp's algorithm.

Algorithms↗