Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

Sompel, Dominique Van de; Brady, Sir Michael; Boone, John M.

doi:10.1016/j.media.2010.07.004

Cited by 39 publications

(30 citation statements)

References 67 publications

(107 reference statements)

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“…It is important to first quantify signal detectability in the raw data because different postprocessing and reconstruction algorithms may lead to differences in task performance. 43 We represented the discrete-to-discrete x-ray imaging process with the imaging equation:…”

Section: Iiia Detection Of Small Massesmentioning

confidence: 99%

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

et al. 2013

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Purpose: Digital breast tomosynthesis (DBT) is a promising breast cancer screening tool that has already begun making inroads into clinical practice. However, there is ongoing debate over how to quantitatively evaluate and optimize these systems, because different definitions of image quality can lead to different optimal design strategies. Powerful and accurate tools are desired to extend our understanding of DBT system optimization and validate published design principles. Methods: The authors developed a virtual trial framework for task-specific DBT assessment that uses digital phantoms, open-source x-ray transport codes, and a projection-space, spatial-domain observer model for quantitative system evaluation. The authors considered evaluation of reconstruction algorithms as a separate problem and focused on the information content in the raw, unfiltered projection images. Specifically, the authors investigated the effects of scan angle and number of angular projections on detectability of a small (3 mm diameter) signal embedded in randomly-varying anatomical backgrounds. Detectability was measured by the area under the receiver-operating characteristic curve (AUC). Experiments were repeated for three test cases where the detectability-limiting factor was anatomical variability, quantum noise, or electronic noise. The authors also juxtaposed the virtual trial framework with other published studies to illustrate its advantages and disadvantages. Results: The large number of variables in a virtual DBT study make it difficult to directly compare different authors' results, so each result must be interpreted within the context of the specific virtual trial framework. The following results apply to 25% density phantoms with 5.15 cm compressed thickness and 500 μm 3 voxels (larger 500 μm 2 detector pixels were used to avoid voxel-edge artifacts): 1. For raw, unfiltered projection images in the anatomical-variability-limited regime, AUC appeared to remain constant or increase slightly with scan angle. 2. In the same regime, when the authors fixed the scan angle, AUC increased asymptotically with the number of projections. The threshold number of projections for asymptotic AUC performance depended on the scan angle. In the quantum-and electronic-noise dominant regimes, AUC behaviors as a function of scan angle and number of projections sometimes differed from the anatomy-limited regime. For example, with a fixed scan angle, AUC generally decreased with the number of projections in the electronic-noise dominant regime. These results are intended to demonstrate the capabilities of the virtual trial framework, not to be used as optimization rules for DBT. Conclusions:The authors have demonstrated a novel simulation framework and tools for evaluating DBT systems in an objective, task-specific manner. This framework facilitates further investigation of image quality tradeoffs in DBT.

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Section: Iiia Detection Of Small Massesmentioning

confidence: 99%

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

et al. 2013

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“…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

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“…They were corrected by offset and flatfield correction before taking a minus-logarithm transform with an x-ray intensity along the x-ray path in air to represent the line integral of the linear attenuation coefficients of the sample along the x-ray path. For the image reconstruction, because the projection data in the proposed geometry are usually truncated on either or both side(s) of the detector due to the narrow detector width, we employed a compressed-sensing (CS)-based algorithm [7][8][9][10][11], rather than a common filtered-backprojection (FBP) one, for more accurate reconstruction. Here the CS is a state-of-the-art mathematical Here an x-ray tube and a long-rectangular detector rotate together around the rotational axis several times and, concurrently, the detector moves horizontally in the detector coordinate (i.e., s-axis) at a constant speed to cover the whole imaging volume during the projection data acquisition.…”

Section: Methodsmentioning

confidence: 99%

Experimental study on the 3D image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector and its image characteristics

Hong

Cho

et al. 2015

Optics Communications

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Task-based performance analysis of FBP, SART and ML for digital breast tomosynthesis using signal CNR and Channelised Hotelling Observers

Cited by 39 publications

References 67 publications

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data

Digital mammography and tomosynthesis for breast cancer diagnosis

Experimental study on the 3D image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector and its image characteristics

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