Automatic segmentation of breast and fibroglandular tissue in breast MRI using local adaptive thresholding

Author(s):  
Aida Fooladivanda ◽  
Shahriar B. Shokouhi ◽  
Nasrin Ahmadinejad ◽  
Mohammad R. Mosavi
2017 ◽  
Vol 42 ◽  
pp. 119-125 ◽  
Author(s):  
Akshat C. Pujara ◽  
Artem Mikheev ◽  
Henry Rusinek ◽  
Harikrishna Rallapalli ◽  
Jerzy Walczyk ◽  
...  

2012 ◽  
Vol 22 (12) ◽  
pp. 2641-2647 ◽  
Author(s):  
Valencia King ◽  
Yajia Gu ◽  
Jennifer B. Kaplan ◽  
Jennifer D. Brooks ◽  
Malcolm C. Pike ◽  
...  

2018 ◽  
Vol 60 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Paola Clauser ◽  
Matthias Dietzel ◽  
Michael Weber ◽  
Clemens G Kaiser ◽  
Pascal AT Baltzer

Background Motion artifacts can reduce image quality of breast magnetic resonance imaging (MRI). There is a lack of data regarding their effect on diagnostic estimates. Purpose To evaluate factors that potentially influence readers’ diagnostic estimates in breast MRI: motion artifacts; amount of fibroglandular tissue; background parenchymal enhancement; lesion size; and lesion type. Material and Methods This Institutional Review Board-approved, retrospective, cross-sectional, single-center study included 320 patients (mean age = 55.1 years) with 334 histologically verified breast lesions (139 benign, 195 malignant) who underwent breast MRI. Two expert breast radiologists evaluated the images considering: motion artifacts (1 = minimal to 4 = marked); fibroglandular tissue (BI-RADS FGT); background parenchymal enhancement (BI-RADS BPE); lesion size; lesion type; and BI-RADS score. Univariate (Chi-square) and multivariate (Generalized Estimation Equations [GEE]) statistics were used to identify factors influencing sensitivity, specificity, and accuracy. Results Lesions were: 230 mass (68.9%) and 59 non-mass (17.7%), no foci. Forty-five lesions (13.5%) did not enhance in MRI but were suspicious or unclear in conventional imaging. Sensitivity, specificity, and accuracy were 93.8%, 83.4%, and 89.8% for Reader 1 and 95.4%, 87.8%, and 91.9% for Reader 2. Lower sensitivity was observed in case of increased motion artifacts ( P = 0.007), non-mass lesions ( P < 0.001), and small lesions ≤ 10 mm ( P < 0.021). No further factors (e.g. BPE, FGT) significantly influenced diagnostic estimates. At multivariate analysis, lesion type and size were retained as independent factors influencing the diagnostic performance ( P < 0.033). Conclusion Motion artifacts can impair lesion characterization with breast MRI, but lesion type and small size have the strongest influence on diagnostic estimates.


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