Enhanced algorithms for lesion detection and recognition in ultrasound breast images

Mammography is the gold standard for breast cancer detection. However, it has very high false positive rates and is based on ionizing radiation. This has led to interest in using multi-modal approaches. One modality is diagnostic ultrasound, which is based on non-ionizing radiation and picks up many...

Full description

Bibliographic Details
Main Author:	Yap, Moi Hoon
Published:	Loughborough University 2008
Subjects:	616.07
Online Access:	https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516226

id	ndltd-bl.uk-oai-ethos.bl.uk-516226
record_format	oai_dc
spelling	ndltd-bl.uk-oai-ethos.bl.uk-5162262018-11-08T03:20:57ZEnhanced algorithms for lesion detection and recognition in ultrasound breast imagesYap, Moi Hoon2008Mammography is the gold standard for breast cancer detection. However, it has very high false positive rates and is based on ionizing radiation. This has led to interest in using multi-modal approaches. One modality is diagnostic ultrasound, which is based on non-ionizing radiation and picks up many of the cancers that are generally missed by mammography. However, the presence of speckle noise in ultrasound images has a negative effect on image interpretation. Noise reduction, inconsistencies in capture and segmentation of lesions still remain challenging open research problems in ultrasound images. The target of the proposed research is to enhance the state-of-art computer vision algorithms used in ultrasound imaging and to investigate the role of computer processed images in human diagnostic performance.616.07Loughborough Universityhttps://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516226https://dspace.lboro.ac.uk/2134/35018Electronic Thesis or Dissertation
collection	NDLTD
sources	NDLTD
topic	616.07
spellingShingle	616.07 Yap, Moi Hoon Enhanced algorithms for lesion detection and recognition in ultrasound breast images
description	Mammography is the gold standard for breast cancer detection. However, it has very high false positive rates and is based on ionizing radiation. This has led to interest in using multi-modal approaches. One modality is diagnostic ultrasound, which is based on non-ionizing radiation and picks up many of the cancers that are generally missed by mammography. However, the presence of speckle noise in ultrasound images has a negative effect on image interpretation. Noise reduction, inconsistencies in capture and segmentation of lesions still remain challenging open research problems in ultrasound images. The target of the proposed research is to enhance the state-of-art computer vision algorithms used in ultrasound imaging and to investigate the role of computer processed images in human diagnostic performance.
author	Yap, Moi Hoon
author_facet	Yap, Moi Hoon
author_sort	Yap, Moi Hoon
title	Enhanced algorithms for lesion detection and recognition in ultrasound breast images
title_short	Enhanced algorithms for lesion detection and recognition in ultrasound breast images
title_full	Enhanced algorithms for lesion detection and recognition in ultrasound breast images
title_fullStr	Enhanced algorithms for lesion detection and recognition in ultrasound breast images
title_full_unstemmed	Enhanced algorithms for lesion detection and recognition in ultrasound breast images
title_sort	enhanced algorithms for lesion detection and recognition in ultrasound breast images
publisher	Loughborough University
publishDate	2008
url	https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516226
work_keys_str_mv	AT yapmoihoon enhancedalgorithmsforlesiondetectionandrecognitioninultrasoundbreastimages
_version_	1718789600453853184

Enhanced algorithms for lesion detection and recognition in ultrasound breast images

Similar Items