Optimizing High Resolution Reconstruction in Digital Breast Tomosynthesis Using Filtered Back Projection

Abdurahman, Shiras; Dennerlein, Frank; Jerebko, Anna K.; Fieselmann, Andreas; Mertelmeier, Thomas

doi:10.1007/978-3-319-07887-8_73

Cited by 13 publications

(14 citation statements)

References 2 publications

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“…The 24 cases were reconstructed with 2 mm (which is the proposed standard slice image thickness [12] ), 6 mm and 10 mm slab thickness, all presented with 1 mm overlap. The images were reconstructed using super-resolution reconstruction with statistical artifact reduction [13,14] (SRSAR) followed by slabbing with averageintensity-projection (AIP) technique. The reconstruction software was provided by the system manufacturer (Siemens Healthcare, Erlangen, Germany).…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images

et al. 2016

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The large image volumes in breast tomosynthesis (BT) have led to large amounts of data and a heavy workload for breast radiologists. The number of slice images can be decreased by combining adjacent image planes (slabbing) but the decrease in depth resolution can considerably affect the detection of lesions. The aim of this work was to assess if thicker slabbing of the outer slice images (where lesions seldom are present) could be a viable alternative in order to reduce the number of slice images in BT image volumes.The suggested slabbing (an image volume with thick outer slabs and thin slices between) were evaluated in two steps. Firstly, a survey of the depth of 65 cancer lesions within the breast was performed to estimate how many lesions would be affected by outer slabs of different thicknesses. Secondly, a selection of 24 lesions was reconstructed with 2, 6 and 10 mm slab thickness to evaluate how the appearance of lesions located in the thicker slabs would be affected.The results show that few malignant breast lesions are located at a depth less than 10 mm from the surface (especially for breast thicknesses of 50 mm and above). Reconstruction of BT volumes with 6 mm slab thickness yields an image quality that is sufficient for lesion detection for a majority of the investigated cases. Together, this indicates that thicker slabbing of the outer slice images is a promising option in order to reduce the number of slice images in BT image volumes.

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Section: Methodsmentioning

confidence: 99%

Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images

et al. 2016

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“…DBT volumes were reconstructed using the "Enhanced Multiple Parameter Iterative Reconstruction (EMPIRE)" algorithm. The reconstruction algorithm is a filtered back projection (FBP) with additional iterative processing for artefact reduction, noise reduction and higher resolution [33,34]. Between each scan, the phantom was shaken for 10 s to generate a different background realization.…”

Section: Image Acquisitionmentioning

confidence: 99%

Systematic approach to a channelized Hotelling model observer implementation for a physical phantom containing mass-like lesions: Application to digital breast tomosynthesis

et al. 2019

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Purpose: to develop a channelized model observer (CHO) that matches human reader (HR) scoring of a physical phantom containing breast simulating structure and mass lesion-like targets for use in quality control of digital breast tomosynthesis (DBT) imaging systems. Methods: A total of 108 DBT scans of the phantom was acquired using a Siemens Inspiration DBT system. The detectability of mass-like targets was evaluated by human readers using a 4-alternative forced choice (4-AFC) method. The percentage correct (PC) values were then used as the benchmark for CHO tuning, again using a 4-AFC method. Three different channel functions were considered: Gabor, Laguerre-Gauss and Difference of Gaussian. With regard to the observer template, various methods for generating the expected signal were studied along with the influence of the number of training images used to form the covariance matrix for the observer template. Impact of bias in the training process on the observer template was evaluated next, as well as HR and CHO reproducibility. Results: HR performance was most closely matched by 8 Gabor channels with tuned phase, orientation and frequency, using an observer template generated from training image data. Just 24 DBT image stacks were required to give robust CHO performance with 0% bias, although a bias of up to 33% in the training images also gave acceptable performance. CHO and HR reproducibility were similar (on average 3.2 PC versus 3.4 PC). Conclusions: The CHO algorithm developed matches human reader performance and is therefore a promising candidate for automated readout of phantom studies.

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“…the same power spectrum. Three reconstruction algorithms were applied: standard Filtered Back Projection (FBP), 10 FBP with Super Resolution and Statistical Artifact Reduction (SRSAR) 11 and multigrid Maximum Likelihood for Transmission with Resolution modeling (MLTR pr ). 12,13 These algorithms may affect performance as they lead to very different image characteristics: the noise and the structures inside the phantom have a different appearance, as illustrated in fig.…”

Section: Image and Phantom Propertiesmentioning

confidence: 99%

Development and application of a channelized Hotelling observer for DBT optimization on structured background test images with mass simulating targets

et al. 2016

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Digital breast tomosynthesis (DBT) is a 3D mammography technique that promises better visualization of low contrast lesions than conventional 2D mammography. A wide range of parameters influence the diagnostic information in DBT images and a systematic means of DBT system optimization is needed. The gold standard for image quality assessment is to perform a human observer experiment with experienced readers. Using human observers for optimization is time consuming and not feasible for the large parameter space of DBT. Our goal was to develop a model observer (MO) that can predict human reading performance for standard detection tasks of target objects within a structured phantom and subsequently apply it in a first comparative study. The phantom consists of an acrylic semi-cylindrical container with acrylic spheres of different sizes and the remaining space filled with water. Three types of lesions were included: 3D printed spiculated and non-spiculated mass lesions along with calcification groups. The images of the two mass lesion types were reconstructed with 3 different reconstruction methods (FBP, FBP with SRSAR, MLTR pr ) and read by human readers. A Channelized Hotelling model observer was created for the non-spiculated lesion detection task using five Laguerre-Gauss channels, tuned for better performance. For the non-spiculated mass lesions a linear relation between the MO and human observer results was found, with correlation coefficients of 0.956 for standard FBP, 0.998 for FBP with SRSAR and 0.940 for MLTR pr . Both the MO and human observer percentage correct results for the spiculated masses were close to 100%, and showed no difference from each other for every reconstruction algorithm.

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Optimizing High Resolution Reconstruction in Digital Breast Tomosynthesis Using Filtered Back Projection

Cited by 13 publications

References 2 publications

Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images

Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images

Systematic approach to a channelized Hotelling model observer implementation for a physical phantom containing mass-like lesions: Application to digital breast tomosynthesis

Development and application of a channelized Hotelling observer for DBT optimization on structured background test images with mass simulating targets

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