Simplified computer-aided detection scheme of microcalcification clusters in digital breast tomosynthesis images

2016 ◽  
Author(s):  
Ji-Wook Jeong ◽  
Seung-Hoon Chae ◽  
Eun Young Chae ◽  
Hak Hee Kim ◽  
Young Wook Choi ◽  
...  
Keyword(s):  
Digital Breast Tomosynthesis ◽  
Computer Aided Detection ◽  
Breast Tomosynthesis ◽  
Detection Scheme ◽  
Computer Aided ◽  
Microcalcification Clusters

scholarly journals Three-Dimensional Computer-Aided Detection of Microcalcification Clusters in Digital Breast Tomosynthesis

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Ji-wook Jeong ◽  
Seung-Hoon Chae ◽  
Eun Young Chae ◽  
Hak Hee Kim ◽  
Young-Wook Choi ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Digital Breast Tomosynthesis ◽  
Computer Aided Detection ◽  
Segmentation Method ◽  
Breast Tomosynthesis ◽  
Computer Aided ◽  
Bounding Boxes ◽  
Microcalcification Clusters ◽  
The Individual

We propose computer-aided detection (CADe) algorithm for microcalcification (MC) clusters in reconstructed digital breast tomosynthesis (DBT) images. The algorithm consists of prescreening, MC detection, clustering, and false-positive (FP) reduction steps. The DBT images containing the MC-like objects were enhanced by a multiscale Hessian-based three-dimensional (3D) objectness response function and a connected-component segmentation method was applied to extract the cluster seed objects as potential clustering centers of MCs. Secondly, a signal-to-noise ratio (SNR) enhanced image was also generated to detect the individual MC candidates and prescreen the MC-like objects. Each cluster seed candidate was prescreened by counting neighboring individual MC candidates nearby the cluster seed object according to several microcalcification clustering criteria. As a second step, we introduced bounding boxes for the accepted seed candidate, clustered all the overlapping cubes, and examined. After the FP reduction step, the average number of FPs per case was estimated to be 2.47 per DBT volume with a sensitivity of 83.3%.

Computer-Aided Detection and Diagnosis for 3D X-Ray Based Breast Imaging

2012 ◽  
pp. 66-85
Author(s):  
Gautam S. Muralidhar ◽  
Alan C. Bovik ◽  
Mia K. Markey
Keyword(s):  
Breast Imaging ◽  
Digital Breast Tomosynthesis ◽  
Future Research ◽  
Computer Aided Detection ◽  
Breast Tomosynthesis ◽  
X Ray ◽  
Computer Aided ◽  
Recent Developments ◽  
Initial Work ◽  
Detection And Diagnosis

The last 15 years has seen the advent of a variety of powerful 3D x-ray based breast imaging modalities such as digital breast tomosynthesis, digital breast computed tomography, and stereo mammography. These modalities promise to herald a new and exciting future for early detection and diagnosis of breast cancer. In this chapter, the authors review some of the recent developments in 3D x-ray based breast imaging. They also review some of the initial work in the area of computer-aided detection and diagnosis for 3D x-ray based breast imaging. The chapter concludes by discussing future research directions in 3D computer-aided detection.

scholarly journals Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: A 3D approach

2011 ◽  
Vol 39 (1) ◽  
pp. 28-39 ◽  
Author(s):  
Berkman Sahiner ◽  
Heang-Ping Chan ◽  
Lubomir M. Hadjiiski ◽  
Mark A. Helvie ◽  
Jun Wei ◽  
...  
Keyword(s):  
Digital Breast Tomosynthesis ◽  
Computer Aided Detection ◽  
Breast Tomosynthesis ◽  
Computer Aided
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