Removal of pectoral muscle based on topographic map and shape-shifting silhouette

Abstract Background In digital mammography, finding accurate breast profile segmentation of women’s mammogram is considered a challenging task. The existence of the pectoral muscle may mislead the diagnosis of cancer due to its high-level similarity to breast body. In addition, some other challenges...

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Main Authors: Bushra Mughal, Nazeer Muhammad, Muhammad Sharif, Amjad Rehman, Tanzila Saba
Format: Article
Language:English
Published: BMC 2018-08-01
Series:BMC Cancer
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12885-018-4638-5
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spelling doaj-8c79a57577a94526be865a467afcfa9e2020-11-24T23:52:10ZengBMCBMC Cancer1471-24072018-08-0118111410.1186/s12885-018-4638-5Removal of pectoral muscle based on topographic map and shape-shifting silhouetteBushra Mughal0Nazeer Muhammad1Muhammad Sharif2Amjad Rehman3Tanzila Saba4Department of Computer Science, COMSATS University IslamabadDepartment of Mathematics, COMSATS University IslamabadDepartment of Computer Science, COMSATS University IslamabadCollege of Computer and Information Systems, Al-Yamamah UniversityDepartment of Information Systems, Prince Sultan UniversityAbstract Background In digital mammography, finding accurate breast profile segmentation of women’s mammogram is considered a challenging task. The existence of the pectoral muscle may mislead the diagnosis of cancer due to its high-level similarity to breast body. In addition, some other challenges due to manifestation of the breast body pectoral muscle in the mammogram data include inaccurate estimation of the density level and assessment of the cancer cell. The discrete differentiation operator has been proven to eliminate the pectoral muscle before the analysis processing. Methods We propose a novel approach to remove the pectoral muscle in terms of the mediolateral-oblique observation of a mammogram using a discrete differentiation operator. This is used to detect the edges boundaries and to approximate the gradient value of the intensity function. Further refinement is achieved using a convex hull technique. This method is implemented on dataset provided by MIAS and 20 contrast enhanced digital mammographic images. Results To assess the performance of the proposed method, visual inspections by radiologist as well as calculation based on well-known metrics are observed. For calculation of performance metrics, the given pixels in pectoral muscle region of the input scans are calculated as ground truth. Conclusions Our approach tolerates an extensive variety of the pectoral muscle geometries with minimum risk of bias in breast profile than existing techniques.http://link.springer.com/article/10.1186/s12885-018-4638-5Mediolateral-oblique (MLO)Pectoral muscleBreast profileCranial-caudal (cc)Label and artifacts
collection DOAJ
language English
format Article
sources DOAJ
author Bushra Mughal
Nazeer Muhammad
Muhammad Sharif
Amjad Rehman
Tanzila Saba
spellingShingle Bushra Mughal
Nazeer Muhammad
Muhammad Sharif
Amjad Rehman
Tanzila Saba
Removal of pectoral muscle based on topographic map and shape-shifting silhouette
BMC Cancer
Mediolateral-oblique (MLO)
Pectoral muscle
Breast profile
Cranial-caudal (cc)
Label and artifacts
author_facet Bushra Mughal
Nazeer Muhammad
Muhammad Sharif
Amjad Rehman
Tanzila Saba
author_sort Bushra Mughal
title Removal of pectoral muscle based on topographic map and shape-shifting silhouette
title_short Removal of pectoral muscle based on topographic map and shape-shifting silhouette
title_full Removal of pectoral muscle based on topographic map and shape-shifting silhouette
title_fullStr Removal of pectoral muscle based on topographic map and shape-shifting silhouette
title_full_unstemmed Removal of pectoral muscle based on topographic map and shape-shifting silhouette
title_sort removal of pectoral muscle based on topographic map and shape-shifting silhouette
publisher BMC
series BMC Cancer
issn 1471-2407
publishDate 2018-08-01
description Abstract Background In digital mammography, finding accurate breast profile segmentation of women’s mammogram is considered a challenging task. The existence of the pectoral muscle may mislead the diagnosis of cancer due to its high-level similarity to breast body. In addition, some other challenges due to manifestation of the breast body pectoral muscle in the mammogram data include inaccurate estimation of the density level and assessment of the cancer cell. The discrete differentiation operator has been proven to eliminate the pectoral muscle before the analysis processing. Methods We propose a novel approach to remove the pectoral muscle in terms of the mediolateral-oblique observation of a mammogram using a discrete differentiation operator. This is used to detect the edges boundaries and to approximate the gradient value of the intensity function. Further refinement is achieved using a convex hull technique. This method is implemented on dataset provided by MIAS and 20 contrast enhanced digital mammographic images. Results To assess the performance of the proposed method, visual inspections by radiologist as well as calculation based on well-known metrics are observed. For calculation of performance metrics, the given pixels in pectoral muscle region of the input scans are calculated as ground truth. Conclusions Our approach tolerates an extensive variety of the pectoral muscle geometries with minimum risk of bias in breast profile than existing techniques.
topic Mediolateral-oblique (MLO)
Pectoral muscle
Breast profile
Cranial-caudal (cc)
Label and artifacts
url http://link.springer.com/article/10.1186/s12885-018-4638-5
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