Paper
14 March 2007 Optimization of image quality in breast tomosynthesis using lumpectomy and mastectomy specimens
Pontus Timberg, Mark Ruschin, Magnus Båth, Bengt Hemdal, Ingvar Andersson, Tony Svahn, Sören Mattsson, Anders Tingberg
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Abstract
The purpose of this study was to determine how image quality in breast tomosynthesis (BT) is affected when acquisition modes are varied, using human breast specimens containing malignant tumors and/or microcalcifications. Images of thirty-one breast lumpectomy and mastectomy specimens were acquired on a BT prototype based on a Mammomat Novation (Siemens) full-field digital mammography system. BT image acquisitions of the same specimens were performed varying the number of projections, angular range, and detector signal collection mode (binned and nonbinned in the scan direction). An enhanced filtered back projection reconstruction method was applied with constant settings of spectral and slice thickness filters. The quality of these images was evaluated via relative visual grading analysis (VGA) human observer performance experiments using image quality criteria. Results from the relative VGA study indicate that image quality increases with number of projections and angular range. A binned detector collecting mode results in less noise, but reduced resolution of structures. Human breast specimens seem to be suitable for comparing image sets in BT with image quality criteria.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pontus Timberg, Mark Ruschin, Magnus Båth, Bengt Hemdal, Ingvar Andersson, Tony Svahn, Sören Mattsson, and Anders Tingberg "Optimization of image quality in breast tomosynthesis using lumpectomy and mastectomy specimens", Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 651032 (14 March 2007); https://doi.org/10.1117/12.709703
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Cited by 7 scholarly publications.
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KEYWORDS
Image quality

Breast

Sensors

3D image reconstruction

Optical filters

Signal detection

Visualization

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