Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)

Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)

Breast cancer is the leading cancer killer among women. Early detection and new treatments have improved survival rates. Although mammography is the gold standard for breast cancer screening, increasing awareness indicate that there is some limitation for part of women whom mammography reduce sensit...

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Main Authors: Jalalin, Afsaneh, Mashohor, Syamsiah, Mahmud, Rozi
Format: Conference or Workshop Item
Language:English
Published: UPM-MAKNA Cancer Research Laboratory, Institute of Bioscience 2014
Online Access:http://psasir.upm.edu.my/id/eprint/20179/
http://psasir.upm.edu.my/id/eprint/20179/1/ABSTRACT%20CAC%202014_2%20medic%2030.pdf
id upm-20179
recordtype eprints
spelling upm-201792016-04-26T04:57:35Z http://psasir.upm.edu.my/id/eprint/20179/ Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM) Jalalin, Afsaneh Mashohor, Syamsiah Mahmud, Rozi Breast cancer is the leading cancer killer among women. Early detection and new treatments have improved survival rates. Although mammography is the gold standard for breast cancer screening, increasing awareness indicate that there is some limitation for part of women whom mammography reduce sensitivity based on their breast density. Other modalities such as ultrasound and magnetic resonance imaging and recently computed tomography laser mammography (CTLM) are often suggested as an adjunct to mammography to achieve additional information and increase sensitivity. The angiogenesis is known a critical for tumor growth and spread of breast cancers. Computed tomography laser mammography (CTLM) CTLM has been introduced to verify angiogenesis at early stage. In this modality, there are no restriction factors such as age or breast density. Main difficulty for radiologists is closeness of color shade to interpret CTLM images. Computer-aided detection /diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) pre-processing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. The aim of this research is to develop a CAD system in computed tomography laser mammography (CTLM) to detect and classify benign and malignant lesions in the breast. UPM-MAKNA Cancer Research Laboratory, Institute of Bioscience 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/20179/1/ABSTRACT%20CAC%202014_2%20medic%2030.pdf Jalalin, Afsaneh and Mashohor, Syamsiah and Mahmud, Rozi (2014) Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM). In: Scientific Cancer Research Poster Competition in conjunction with Cancer Awareness Carnival 2014, 10 May 2014, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia. .
repository_type Digital Repository
institution_category Local University
institution Universiti Putra Malaysia
building UPM Institutional Repository
collection Online Access
language English
description Breast cancer is the leading cancer killer among women. Early detection and new treatments have improved survival rates. Although mammography is the gold standard for breast cancer screening, increasing awareness indicate that there is some limitation for part of women whom mammography reduce sensitivity based on their breast density. Other modalities such as ultrasound and magnetic resonance imaging and recently computed tomography laser mammography (CTLM) are often suggested as an adjunct to mammography to achieve additional information and increase sensitivity. The angiogenesis is known a critical for tumor growth and spread of breast cancers. Computed tomography laser mammography (CTLM) CTLM has been introduced to verify angiogenesis at early stage. In this modality, there are no restriction factors such as age or breast density. Main difficulty for radiologists is closeness of color shade to interpret CTLM images. Computer-aided detection /diagnosis (CAD) systems have been developed to help radiologists in order to increase diagnosis accuracy. Generally, a CAD system consists of four stages: (a) pre-processing, (b) segmentation of regions of interest, (c) feature extraction and selection, and finally (d) classification. The aim of this research is to develop a CAD system in computed tomography laser mammography (CTLM) to detect and classify benign and malignant lesions in the breast.
format Conference or Workshop Item
author Jalalin, Afsaneh
Mashohor, Syamsiah
Mahmud, Rozi
spellingShingle Jalalin, Afsaneh
Mashohor, Syamsiah
Mahmud, Rozi
Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
author_facet Jalalin, Afsaneh
Mashohor, Syamsiah
Mahmud, Rozi
author_sort Jalalin, Afsaneh
title Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
title_short Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
title_full Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
title_fullStr Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
title_full_unstemmed Computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (CTLM)
title_sort computer aided detection/diagnisis for breast cancer detection in computed tomography laser mammography (ctlm)
publisher UPM-MAKNA Cancer Research Laboratory, Institute of Bioscience
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/20179/
http://psasir.upm.edu.my/id/eprint/20179/1/ABSTRACT%20CAC%202014_2%20medic%2030.pdf
first_indexed 2018-09-07T14:15:39Z
last_indexed 2018-09-07T14:15:39Z
_version_ 1610958493160833024

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