Document Detail

A heuristic approach to automated nipple detection in digital mammograms.
MedLine Citation:
PMID:  23423610     Owner:  NLM     Status:  MEDLINE    
In this paper, a heuristic approach to automated nipple detection in digital mammograms is presented. A multithresholding algorithm is first applied to segment the mammogram and separate the breast region from the background region. Next, the problem is considered separately for craniocaudal (CC) and mediolateral-oblique (MLO) views. In the simplified algorithm, a search is performed on the segmented image along a band around the centroid and in a direction perpendicular to the pectoral muscle edge in the MLO view image. The direction defaults to the horizontal (perpendicular to the thoracic wall) in case of CC view images. The farthest pixel from the base found in this direction can be approximated as the nipple point. Further, an improved version of the simplified algorithm is proposed which can be considered as a subclass of the Branch and Bound algorithms. The mean Euclidean distance between the ground truth and calculated nipple position for 500 mammograms from the Digital Database for Screening Mammography (DDSM) database was found to be 11.03 mm and the average total time taken by the algorithm was 0.79 s. Results of the proposed algorithm demonstrate that even simple heuristics can achieve the desired result in nipple detection thus reducing the time and computational complexity.
Mainak Jas; Sudipta Mukhopadhyay; Jayasree Chakraborty; Anup Sadhu; Niranjan Khandelwal
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of digital imaging     Volume:  26     ISSN:  1618-727X     ISO Abbreviation:  J Digit Imaging     Publication Date:  2013 Oct 
Date Detail:
Created Date:  2013-09-25     Completed Date:  2014-04-25     Revised Date:  2014-10-12    
Medline Journal Info:
Nlm Unique ID:  9100529     Medline TA:  J Digit Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  932-40     Citation Subset:  IM    
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MeSH Terms
Breast Neoplasms / radiography*
Databases, Factual
Mammography / methods*
Nipples / radiography*
Pattern Recognition, Automated / methods*
Radiographic Image Enhancement / methods*
Radiographic Image Interpretation, Computer-Assisted / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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