Segmentation of the Pectoral Muscle Boundary in Breast MR Images

2011 ◽  
Author(s):  
Myungeun Lee ◽  
Yanjuan Chen ◽  
Soohyung Kim ◽  
Jonghyo Kim
Keyword(s):  
Pectoral Muscle ◽  
Mr Images ◽  
Breast Mr

scholarly journals Automated Segmentation of the Pectoral Muscle in Axial Breast MR Images

2019 ◽  
pp. 345-356
Author(s):  
Sahar Zafari ◽  
Mazen Diab ◽  
Tuomas Eerola ◽  
Summer E. Hanson ◽  
Gregory P. Reece ◽  
...  
Keyword(s):  
Pectoral Muscle ◽  
Automated Segmentation ◽  
Mr Images ◽  
Breast Mr

scholarly journals Segmentation of breast MR images based on multiresolution level set algorithm

2014 ◽  
Vol 63 (11) ◽  
pp. 118701
Author(s):  
Fan Hong ◽  
Zhu Yan-Chun ◽  
Wang Fang-Mei ◽  
Zhang Xu-Mei
Keyword(s):  
Level Set ◽  
Mr Images ◽  
Breast Mr

scholarly journals Malignant lesion segmentation in contrast-enhanced breast MR images based on the marker-controlled watershed

2009 ◽  
Vol 36 (10) ◽  
pp. 4359-4369 ◽  
Author(s):  
Yunfeng Cui ◽  
Yongqiang Tan ◽  
Binsheng Zhao ◽  
Laura Liberman ◽  
Rakesh Parbhu ◽  
...  
Keyword(s):  
Malignant Lesion ◽  
Lesion Segmentation ◽  
Mr Images ◽  
Contrast Enhanced ◽  
Breast Mr

Fat suppression techniques for obtaining high resolution dynamic contrast enhanced bilateral breast MR images at 7 T

2016 ◽  
Vol 34 (4) ◽  
pp. 462-468 ◽  
Author(s):  
Tijl A. van der Velden ◽  
Alexander M.Th. Schmitz ◽  
Kenneth G.A. Gilhuijs ◽  
Wouter B. Veldhuis ◽  
Peter R. Luijten ◽  
...  
Keyword(s):  
High Resolution ◽  
Fat Suppression ◽  
Mr Images ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced ◽  
Breast Mr ◽  
Fat Suppression Techniques

Automatic Segmentation of Breast MR Images Through a Markov Random Field Statistical Model

2014 ◽  
Vol 33 (10) ◽  
pp. 1986-1996 ◽  
Author(s):  
S. Ribes ◽  
D. Didierlaurent ◽  
N. Decoster ◽  
E. Gonneau ◽  
L. Risser ◽  
...  
Keyword(s):  
Statistical Model ◽  
Random Field ◽  
Markov Random Field ◽  
Automatic Segmentation ◽  
Mr Images ◽  
Markov Random ◽  
Breast Mr

Evaluation of Pectoralis Major Muscle in Patients with Posterior Breast Tumors on Breast MR Images: Early Experience

Radiology ◽  
2000 ◽  
Vol 214 (1) ◽  
pp. 67-72 ◽  
Author(s):  
Elizabeth A. Morris ◽  
Lawrence H. Schwartz ◽  
Michele B. Drotman ◽  
Su J. Kim ◽  
Lee K. Tan ◽  
...  
Keyword(s):  
Pectoralis Major Muscle ◽  
Early Experience ◽  
Breast Tumors ◽  
Pectoralis Major ◽  
Mr Images ◽  
Breast Mr

scholarly journals Grammatical Fireworks Algorithm Method for Breast Lesion Segmentation in DCE-MR Images

2021 ◽  
Vol 10 (7) ◽  
pp. 170-182
Author(s):  
D. K. Patra* ◽  
S. Mondal ◽  
P. Mukherjee
Keyword(s):  
Tissue Characterization ◽  
Lesion Detection ◽  
Mr Images ◽  
Dce Mri ◽  
Fireworks Algorithm ◽  
Clustering Technique ◽  
Analysis Task ◽  
Breast Mr ◽  
Segmented Images ◽  
Experimental Findings

For cancer detection and tissue characterization, DCE-MRI segmentation and lesion detection is a critical image analysis task. To segment breast MR images for lesion detection, a hard-clustering technique with Grammatical Fireworks algorithm (GFWA) is proposed in this paper. GFWA is a Swarm Programming (SP) system for automatically generating computer programs in any language. GFWA is used to create the cluster core for clustering the breast MR images in this article. The presence of noise and intensity inhomogeneities in MR images complicates the segmentation process. As a result, the MR images are denoised at the start, and strength inhomogeneities are corrected in the preprocessing stage. The proposed GFWA-based clustering technique is used to segment the preprocessed MR images. Finally, from the segmented images, the lesions are removed. The proposed approach is tested on 5 patients’ 25 DCE-MRI slices. The proposed method’s experimental findings are compared to those of the Grammatical Swarm (GS)-based clustering technique and the K-means algorithm. The proposed method outperforms other approaches in terms of both quantitative and qualitative results.

Sign in / Sign up

Export Citation Format

Share Document