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An analysis of the segmentation threshold used in axial-shear strain elastography
Published in Elsevier B.V.
2015
PMID: 25173068
Volume: 55
   
Issue: 1
Pages: 58 - 64
Abstract
Axial-shear strain elastography was introduced recently to image the tumor-host tissue boundary bonding characteristics. The image depicting the axial-shear strain distribution in a tissue under axial compression was termed as an axial-shear strain elastogram (ASSE). It has been demonstrated through simulation, tissue-mimicking phantom experiments, and retrospective analysis of in vivo breast lesion data that metrics quantifying the pattern of axial-shear strain distribution on ASSE can be used as features for identifying the lesion boundary condition as loosely-bonded or firmly-bonded. Consequently, features from ASSE have been shown to have potential in non-invasive breast lesion classification into benign versus malignant. Although there appears to be a broad concurrence in the results reported by different groups, important details pertaining to the appropriate segmentation threshold needed for - (1) displaying the ASSE as a color-overlay on top of corresponding Axial Strain Elastogram (ASE) and/ or sonogram for feature visualization and (2) ASSE feature extraction are not yet fully addressed. In this study, we utilize ASSE from tissue mimicking phantom (with loosely-bonded and firmly-bonded inclusions) experiments and freehand - acquired in vivo breast lesion data (7 benign and 9 malignant) to analyze the effect of segmentation threshold on ASSE feature value, specifically, the "fill-in" feature that was introduced recently. We varied the segmentation threshold from 20% to 70% (of the maximum ASSE value) for each frame of the acquisition cine-loop of every data and computed the number of ASSE pixels within the lesion that was greater than or equal to this threshold value. If at least 40% of the pixels within the lesion area crossed this segmentation threshold, the ASSE frame was considered to demonstrate a " fill-in " that would indicate a loosely-bonded lesion boundary condition (suggestive of a benign lesion). Otherwise, the ASSE frame was considered not to demonstrate a " fill-in " indicating a firmly-bonded lesion boundary condition (suggestive of a malignant lesion). The results demonstrate that in the case of in vivo breast lesion data the appropriate range for the segmentation threshold value seems to be 40-60%. It was noted that for a segmentation threshold within this range (for example, at 50%) all of the analyzed breast lesion cases can be correctly classified into benign and malignant, based on the percentage number of frames within the acquisition cine-loop that demonstrate a " fill-in ". © 2014 Elsevier B.V. All rights reserved.
About the journal
JournalData powered by TypesetUltrasonics
PublisherData powered by TypesetElsevier B.V.
ISSN0041624X
Open AccessYes
Concepts (32)
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    Boundary conditions
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    Feature extraction
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    Medical imaging
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    Pixels
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    Tissue
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    Tissue engineering
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    Benign
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    BONDING CHARACTERISTICS
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    ELASTOGRAPHY
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    Malignant
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    MALIGNANT LESION
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    RETROSPECTIVE ANALYSIS
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    SEGMENTATION THRESHOLD
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    TISSUE MIMICKING PHANTOM
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    Shear strain
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    Article
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    AXIAL-SHEAR STRAIN
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    Breast tumor
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    Echography
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    ELASTOGRAPHY
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    Human
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    Image quality
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    Methodology
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    SEGMENTATION THRESHOLD
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    Shear strength
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    AXIAL-SHEAR STRAIN
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    ELASTOGRAPHY
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    SEGMENTATION THRESHOLD
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    Breast neoplasms
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    ELASTICITY IMAGING TECHNIQUES
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    Humans
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    PHANTOMS, IMAGING