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Paper
24 March 2016 Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images
Hannie Petersson, Magnus Dustler, Anders Tingberg, Pontus Timberg
Author Affiliations +
Abstract
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hannie Petersson, Magnus Dustler, Anders Tingberg, and Pontus Timberg "Evaluation of the possibility to use thick slabs of reconstructed outer breast tomosynthesis slice images", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97871M (24 March 2016); https://doi.org/10.1117/12.2216688
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KEYWORDS
Breast

Tumors

Image quality

Image quality standards

Medicine

Cancer

Mammography

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