scholarly journals Computer aided lesion detection, segmentation and characterization on mammography and breast MRI

2020 ◽  
Author(s):  
Hang Min
2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
F. Steinbruecker ◽  
A. Meyer-Baese ◽  
T. Schlossbauer ◽  
D. Cremers

Motion-induced artifacts represent a major problem in detection and diagnosis of breast cancer in dynamic contrast-enhanced magnetic resonance imaging. The goal of this paper is to evaluate the performance of a new nonrigid motion correction algorithm based on the optical flow method. For each of the small lesions, we extracted morphological and dynamical features describing both global and local shape, and kinetics behavior. In this paper, we compare the performance of each extracted feature set under consideration of several 2D or 3D motion compensation parameters for the differential diagnosis of enhancing lesions in breast MRI. Based on several simulation results, we determined the optimal motion compensation parameters. Our results have shown that motion compensation can improve the classification results. The results suggest that the computerized analysis system based on the non-rigid motion compensation technique and spatiotemporal features has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.


2010 ◽  
Vol 12 (S3) ◽  
Author(s):  
O Hatsiopoulou ◽  
O Kubassova ◽  
I Jolley ◽  
C Ingram

Author(s):  
Ghazal Rouhafzay ◽  
Yonggang Li ◽  
Haitao Guan ◽  
Chang Shu ◽  
Rafik Goubran ◽  
...  

2003 ◽  
Vol 36 (15) ◽  
pp. 163-167
Author(s):  
Zhe Chen ◽  
David Dagan Feng ◽  
Weidong Cai

2005 ◽  
Author(s):  
Anke Meyer-Baese ◽  
Oliver Lange ◽  
Axel Wismuller ◽  
Gerda Leinsinger

1997 ◽  
Vol 44 (6) ◽  
pp. 2509-2521 ◽  
Author(s):  
C.C. Huang ◽  
X. Yu ◽  
P.S. Conti

2013 ◽  
Vol 112 (3) ◽  
pp. 508-517 ◽  
Author(s):  
Yan-Hao Huang ◽  
Yeun-Chung Chang ◽  
Chiun-Sheng Huang ◽  
Tsung-Ju Wu ◽  
Jeon-Hor Chen ◽  
...  

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