Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review

Journal Title:	Clinical imaging 2013, Vol.37 (3), p.420-426
Main Author:	Jalalian, Afsaneh
Other Authors:	Mashohor, Syamsiah B.T , Mahmud, Hajjah Rozi , Saripan, M. Iqbal B , Ramli, Abdul Rahman B , Karasfi, Babak
Format:	Electronic Article
Language:	English
Subjects:	Accuracy Algorithms Artificial Intelligence Breast Breast cancer Breast Neoplasms - diagnostic imaging Breasts Cancer Classification Computer-aided detection Computer-aided diagnosis Diagnosis Female Gold Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging Mammography Mammography - methods Medical imaging Methods Neural networks Pattern Recognition, Automated - methods Radiology Reproducibility of Results Sensitivity and Specificity Standards Studies Survivability Ultrasonic imaging Ultrasonography, Mammary - methods Ultrasound Wavelet transforms
Quelle:	Alma/SFX Local Collection
Publisher:	United States: Elsevier Inc
ID:	ISSN: 0899-7071
Link:	https://www.ncbi.nlm.nih.gov/pubmed/23153689
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title:	Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review
format:	Article
creator:	Jalalian, Afsaneh Mashohor, Syamsiah B.T Mahmud, Hajjah Rozi Saripan, M. Iqbal B Ramli, Abdul Rahman B Karasfi, Babak
subjects:	Accuracy Algorithms Artificial Intelligence Breast Breast cancer Breast Neoplasms - diagnostic imaging Breasts Cancer Classification Computer-aided detection Computer-aided diagnosis Diagnosis Female Gold Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging Mammography Mammography - methods Medical imaging Methods Neural networks Pattern Recognition, Automated - methods Radiology Reproducibility of Results Sensitivity and Specificity Standards Studies Survivability Ultrasonic imaging Ultrasonography, Mammary - methods Ultrasound Wavelet transforms
ispartof:	Clinical imaging, 2013, Vol.37 (3), p.420-426
description:	Abstract Breast cancer is the most common form of cancer among women worldwide. Early detection of breast cancer can increase treatment options and patients' survivability. Mammography is the gold standard for breast imaging and cancer detection. However, due to some limitations of this modality such as low sensitivity especially in dense breasts, other modalities like ultrasound and magnetic resonance imaging are often suggested to achieve additional information. Recently, computer-aided detection or diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) preprocessing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. This paper presents the approaches which are applied to develop CAD systems on mammography and ultrasound images. The performance evaluation metrics of CAD systems are also reviewed.
language:	eng
source:	Alma/SFX Local Collection
identifier:	ISSN: 0899-7071
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Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review

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Jalalian, Afsaneh ; Mashohor, Syamsiah B.T ; Mahmud, Hajjah Rozi ; Saripan, M. Iqbal B ; Ramli, Abdul Rahman B ; Karasfi, Babak

creatorcontrib

Jalalian, Afsaneh ; Mashohor, Syamsiah B.T ; Mahmud, Hajjah Rozi ; Saripan, M. Iqbal B ; Ramli, Abdul Rahman B ; Karasfi, Babak

description

Abstract Breast cancer is the most common form of cancer among women worldwide. Early detection of breast cancer can increase treatment options and patients' survivability. Mammography is the gold standard for breast imaging and cancer detection. However, due to some limitations of this modality such as low sensitivity especially in dense breasts, other modalities like ultrasound and magnetic resonance imaging are often suggested to achieve additional information. Recently, computer-aided detection or diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) preprocessing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. This paper presents the approaches which are applied to develop CAD systems on mammography and ultrasound images. The performance evaluation metrics of CAD systems are also reviewed.

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2	DOI: 10.1016/j.clinimag.2012.09.024
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United States: Elsevier Inc

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Accuracy ; Algorithms ; Artificial Intelligence ; Breast ; Breast cancer ; Breast Neoplasms - diagnostic imaging ; Breasts ; Cancer ; Classification ; Computer-aided detection ; Computer-aided diagnosis ; Diagnosis ; Female ; Gold ; Humans ; Image Enhancement - methods ; Image Interpretation, Computer-Assisted - methods ; Imaging ; Mammography ; Mammography - methods ; Medical imaging ; Methods ; Neural networks ; Pattern Recognition, Automated - methods ; Radiology ; Reproducibility of Results ; Sensitivity and Specificity ; Standards ; Studies ; Survivability ; Ultrasonic imaging ; Ultrasonography, Mammary - methods ; Ultrasound ; Wavelet transforms

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Clinical imaging, 2013, Vol.37 (3), p.420-426

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0	Elsevier Inc.
1	2013 Elsevier Inc.
2	Copyright © 2013 Elsevier Inc. All rights reserved.
3	COPYRIGHT 2013 Elsevier B.V.
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creationdate	2013
title	Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review
author	Jalalian, Afsaneh ; Mashohor, Syamsiah B.T ; Mahmud, Hajjah Rozi ; Saripan, M. Iqbal B ; Ramli, Abdul Rahman B ; Karasfi, Babak

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0	Accuracy
1	Algorithms
2	Artificial Intelligence
3	Breast
4	Breast cancer
5	Breast Neoplasms - diagnostic imaging
6	Breasts
7	Cancer
8	Classification
9	Computer-aided detection
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23	Pattern Recognition, Automated - methods
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25	Reproducibility of Results
26	Sensitivity and Specificity
27	Standards
28	Studies
29	Survivability
30	Ultrasonic imaging
31	Ultrasonography, Mammary - methods
32	Ultrasound
33	Wavelet transforms

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Clinical imaging

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1	Mashohor, Syamsiah B.T
2	Mahmud, Hajjah Rozi
3	Saripan, M. Iqbal B
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atitle

Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review

jtitle

Clinical imaging

addtitle

Clin Imaging

date

2013

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420

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abstract

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United States

pub

Elsevier Inc

pmid

23153689

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10.1016/j.clinimag.2012.09.024

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Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review