Penalized Maximum Likelihood Reconstruction for Improved Microcalcification Detection in Breast Tomosynthesis

Das, Mini; Gifford, Howard C.; O’Connor, J. Michael; Glick, Stephen J.

doi:10.1109/tmi.2010.2089694

Cited by 52 publications

(36 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The so-called projection images that are acquired during the tube movement are reconstructed to a 3D volume with mathematical algorithms, similar to computed tomography (CT). Filtered back-projection (FBP) has frequently been used because of its speed, but several research groups are developing and evaluating this and other types of reconstruction algorithms, for example maximum likelihood expectation maximization (MLEM) and simultaneous algebraic reconstruction technique (SART) [39][40][41][42][43]. No general conclusion on which algorithm is the better one has yet been reached.…”

Section: Breast Tomosynthesismentioning

confidence: 99%

Digital mammography and tomosynthesis for breast cancer diagnosis

Tingberg

Zackrisson

2011

Expert Opinion on Medical Diagnostics

View full text Add to dashboard Cite

Section: Breast Tomosynthesismentioning

confidence: 99%

Digital mammography and tomosynthesis for breast cancer diagnosis

Tingberg

Zackrisson

2011

Expert Opinion on Medical Diagnostics

View full text Add to dashboard Cite

“…Although a number of studies have investigated the performance of iterative reconstruction for CT, 3 very few have been addressed specifically to the upcoming new modality of breast CT. Previously, Das et al 4 observed improvements in the accuracy of detecting microcalcifications, when using statistical iterative reconstruction (SIR) for breast tomosynthesis. In this study, we investigate SIR algorithms for breast CT.…”

Section: Introductionmentioning

confidence: 99%

Investigation of statistical iterative reconstruction for dedicated breast CT

Makeev

Glick

2013

Med. Phys.

Self Cite

View full text Add to dashboard Cite

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved performance (by a factor of greater than 10) compared to FBP. The hyperbolic prior was also observed to be superior to the TV norm. A few of the best-performing parameter pairs for the PML method also demonstrated superior performance for various radiation doses. In fact, using PML with certain parameter values results in better images, acquired using 2 mGy dose, than FBP-reconstructed images acquired using 6 mGy dose. Conclusions: A range of optimal free parameters for the PML algorithm with hyperbolic and TV norm-based potentials is presented for the microcalcification detection task, in dedicated breast CT. The reported values can be used as starting values of the free parameters, when SIR techniques are used for image reconstruction. Significant improvement in image quality can be achieved by using PML with optimal combination of parameters, as compared to FBP. Importantly, these results suggest improved detection of microcalcifications can be obtained by using PML with lower radiation dose to the patient, than using FBP with higher dose.

show abstract

“…Instead, an algebraic matrix is used to selectively identify and then subtract noise from the image according to a mathematical model. The objective with MLEM (statistical method) is to identify the reconstructed image that maximizes the likelihood of having observed the particular projection measurements [15]. In the MLEM algorithm, because high-frequency noise in the data is amplified by each iteration of the reconstruction algorithm, a smaller number of iterations may be optimal for detection of low-contrast objects, such as small tumors [3].…”

Section: Discussionmentioning

confidence: 99%

Comparison of Different Reconstruction Algorithms for Decreasing the Exposure Dose during Digital Breast Tomosynthesis: A Phantom Study

Gomi¹

2015

JBiSE

View full text Add to dashboard Cite

We compared reconstruction algorithms [filtered back projection (FBP), maximum likelihood expectation maximization (MLEM), and the simultaneous iterative reconstruction technique (SIRT)] in terms of the radiation dose and image quality, for exploring the possibility of decreasing the radiation dose during digital breast tomosynthesis (DBT). The three algorithms were implemented using a DBT system and experimentally evaluated using measurements, such as signal differenceto-noise ratio (SDNR) and intensity profile, on a BR3D phantom (in-focus plane image). The possible radiation dose reduction, contrast improvement, and artifact reduction in DBT were evaluated using different exposure levels and the three reconstruction techniques. We performed statistical analysis (one-way analysis of variance) of the SDNR data. The effectiveness of each technique for enhancing the visibility of the BR3D phantom was quantified with regard to SDNR (FBP versus MLEM, P < 0.05; FBP vs. SIRT, P < 0.05; MLEM vs. SIRT, P = 0.945); the artifact reduction was quantified with regard to the intensity profile. MLEM and SIRT produced reconstructed images with SDNR values indicative of low-contrast visibility. The SDNR value for the half-radiation dose MLEM and SIRT images was close to that of the FBP reference radiation dose image. Artifacts were decreased in the MLEM and SIRT images (in the in-focus plane) according to the intensity profiles that we obtained. With MLEM and SIRT, the radiation dose may be decreased to half comparison with FBP.

show abstract

Penalized Maximum Likelihood Reconstruction for Improved Microcalcification Detection in Breast Tomosynthesis

Cited by 52 publications

References 48 publications

Digital mammography and tomosynthesis for breast cancer diagnosis

Digital mammography and tomosynthesis for breast cancer diagnosis

Investigation of statistical iterative reconstruction for dedicated breast CT

Comparison of Different Reconstruction Algorithms for Decreasing the Exposure Dose during Digital Breast Tomosynthesis: A Phantom Study

Contact Info

Product

Resources

About