Literature DB >> 22949053

Automated delineation of calcified vessels in mammography by tracking with uncertainty and graphical linking techniques.

Jie-Zhi Cheng, Chung-Ming Chen, Elodia B Cole, Etta D Pisano, Dinggang Shen.   

Abstract

As a potential biomarker for women's cardiovascular and chronic kidney diseases, breast arterial calcification (BAC) in mammography has become an emerging research topic in recent years. To provide more objective measurement for vascular structures with calcium depositions in mammography, a new computerized method is introduced in this paper to delineate the calcified vessels. Specifically, we leverage two underlying cues, namely calcification and vesselness, into a multiple seeded tracking with uncertainty scheme. This new vessel-tracking scheme generates plenty of sampling paths to describe the complicated topology of the vascular structures with calcium depositions. A compiling and linking process is further carried out to organize the sampling paths together to be the vessel segments that likely belong to the same vessel tract. The proposed method has been evaluated on 63 mammograms, by comparison with manual delineations from two experts using various assessment metrics. The experiment results confirm the efficacy and stability of the proposed method, and also indicate that the proposed method can be potentially used as a convenient BAC measurement tool in replacement of the trivial and tedious manual delineation tasks.

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Year:  2012        PMID: 22949053     DOI: 10.1109/TMI.2012.2215880

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  7 in total

1.  Resolution enhancement of lung 4D-CT via group-sparsity.

Authors:  Arnav Bhavsar; Guorong Wu; Jun Lian; Dinggang Shen
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

2.  Harnessing group-sparsity regularization for resolution enhancement of lung 4D-CT.

Authors:  Arnav Bhavsar; Guorong Wu; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2013

3.  Detecting Cardiovascular Disease from Mammograms With Deep Learning.

Authors:  Juan Wang; Huanjun Ding; Fatemeh Azamian Bidgoli; Brian Zhou; Carlos Iribarren; Sabee Molloi; Pierre Baldi
Journal:  IEEE Trans Med Imaging       Date:  2017-01-19       Impact factor: 10.048

4.  Segmentation of perivascular spaces in 7T MR image using auto-context model with orientation-normalized features.

Authors:  Sang Hyun Park; Xiaopeng Zong; Yaozong Gao; Weili Lin; Dinggang Shen
Journal:  Neuroimage       Date:  2016-04-01       Impact factor: 6.556

5.  Semiquantitative score of breast arterial calcifications on mammography (BAC-SS): intra- and inter-reader reproducibility.

Authors:  Rubina Manuela Trimboli; Marina Codari; Andrea Cozzi; Caterina Beatrice Monti; Davide Capra; Carolina Nenna; Diana Spinelli; Giovanni Di Leo; Giuseppe Baselli; Francesco Sardanelli
Journal:  Quant Imaging Med Surg       Date:  2021-05

6.  Enhancement of Perivascular Spaces in 7 T MR Image using Haar Transform of Non-local Cubes and Block-matching Filtering.

Authors:  Yingkun Hou; Sang Hyun Park; Qian Wang; Jun Zhang; Xiaopeng Zong; Weili Lin; Dinggang Shen
Journal:  Sci Rep       Date:  2017-08-17       Impact factor: 4.379

7.  Breast Arterial Calcification: a New Marker of Cardiovascular Risk?

Authors:  Carlos Iribarren; Sabee Molloi
Journal:  Curr Cardiovasc Risk Rep       Date:  2013-02-03
  7 in total

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