Statistical modelling of lines and structures in mammograms

Reyer Zwiggelaar; Tim Parr; Caroline Boggis; Sue Astley; Christopher J. Taylor

doi:10.1007/3-540-63046-5_34

Statistical modelling of lines and structures in mammograms

Reyer Zwiggelaar
, Tim Parr
, Caroline Boggis
, Sue Astley
, Christopher J. Taylor

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2 Dyfyniadau (Scopus)

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Computer-aided mammographic prompting systems require the reliable detection of a variety of signs of cancer. The emphasis of the work described is the correct classification of linear structures in mammograms. Statistical modelling, based on principal component analysis (PCA), has been developed for describing the cross-sectional profiles of linear structures, the motivation being that the shapes of intensity profiles may be characteristic of the type of structure. PCA models have been applied to whole mammograms to obtain images in which spicules, linear structures associated with stellate lesions, are emphasised. The aim is to improve the performance of automatic stellate lesion detection by concentrating on those structures most likely to be associated with lesions.

Iaith wreiddiol	Saesneg
Teitl	Information Processing in Medical Imaging
Is-deitl	15th International Conference, IPMI'97, Poultney, Vermont, USA, June 9-13, 1997, Proceedings
Golygyddion	James Duncan, Gene Gindi
Cyhoeddwr	Springer Nature
Tudalennau	405-410
Nifer y tudalennau	6
ISBN (Electronig)	978-3-540-69070-2
ISBN (Argraffiad)	3540630465, 9783540630463
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/3-540-63046-5_34
Statws	Cyhoeddwyd - 21 Mai 1997
Cyhoeddwyd yn allanol	Ie
Digwyddiad	Proceedings of the 15th International Conference : Information Processing in Medical Imaging - Poultney, Unol Daleithiau America Hyd: 09 Meh 1997 → 13 Meh 1997

Cyfres gyhoeddiadau

Enw	Lecture Notes in Computer Science
Cyhoeddwr	Springer Nature
Cyfrol	1230
ISSN (Argraffiad)	0302-9743
ISSN (Electronig)	1611-3349

Cynhadledd

Cynhadledd	Proceedings of the 15th International Conference
Teitl cryno	IPMI'97
Gwlad/Tiriogaeth	Unol Daleithiau America
Dinas	Poultney
Cyfnod	09 Meh 1997 → 13 Meh 1997

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10.1007/3-540-63046-5_34

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Zwiggelaar, R., Parr, T., Boggis, C., Astley, S., & Taylor, C. J. (1997). Statistical modelling of lines and structures in mammograms. Yn J. Duncan, & G. Gindi (Gol.), Information Processing in Medical Imaging: 15th International Conference, IPMI'97, Poultney, Vermont, USA, June 9-13, 1997, Proceedings (tt. 405-410). (Lecture Notes in Computer Science; Cyfrol 1230). Springer Nature. https://doi.org/10.1007/3-540-63046-5_34

@inproceedings{0fcf24911f4b4591bb1b40c27aac6fa0,

title = "Statistical modelling of lines and structures in mammograms",

abstract = "Computer-aided mammographic prompting systems require the reliable detection of a variety of signs of cancer. The emphasis of the work described is the correct classification of linear structures in mammograms. Statistical modelling, based on principal component analysis (PCA), has been developed for describing the cross-sectional profiles of linear structures, the motivation being that the shapes of intensity profiles may be characteristic of the type of structure. PCA models have been applied to whole mammograms to obtain images in which spicules, linear structures associated with stellate lesions, are emphasised. The aim is to improve the performance of automatic stellate lesion detection by concentrating on those structures most likely to be associated with lesions.",

author = "Reyer Zwiggelaar and Tim Parr and Caroline Boggis and Sue Astley and Taylor, \{Christopher J.\}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.; Proceedings of the 15th International Conference : Information Processing in Medical Imaging, IPMI'97 ; Conference date: 09-06-1997 Through 13-06-1997",

year = "1997",

month = may,

day = "21",

doi = "10.1007/3-540-63046-5\_34",

language = "English",

isbn = "3540630465",

series = "Lecture Notes in Computer Science",

publisher = "Springer Nature",

pages = "405--410",

editor = "James Duncan and Gene Gindi",

booktitle = "Information Processing in Medical Imaging",

address = "Switzerland",

}

Zwiggelaar, R, Parr, T, Boggis, C, Astley, S & Taylor, CJ 1997, Statistical modelling of lines and structures in mammograms. yn J Duncan & G Gindi (gol.), Information Processing in Medical Imaging: 15th International Conference, IPMI'97, Poultney, Vermont, USA, June 9-13, 1997, Proceedings. Lecture Notes in Computer Science, cyfrol. 1230, Springer Nature, tt. 405-410, Proceedings of the 15th International Conference , Poultney, Vermont, Unol Daleithiau America, 09 Meh 1997. https://doi.org/10.1007/3-540-63046-5_34

Statistical modelling of lines and structures in mammograms. / Zwiggelaar, Reyer; Parr, Tim; Boggis, Caroline et al.
Information Processing in Medical Imaging: 15th International Conference, IPMI'97, Poultney, Vermont, USA, June 9-13, 1997, Proceedings. gol. / James Duncan; Gene Gindi. Springer Nature, 1997. t. 405-410 (Lecture Notes in Computer Science; Cyfrol 1230).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (ISBN)

TY - GEN

T1 - Statistical modelling of lines and structures in mammograms

AU - Zwiggelaar, Reyer

AU - Parr, Tim

AU - Boggis, Caroline

AU - Astley, Sue

AU - Taylor, Christopher J.

PY - 1997/5/21

Y1 - 1997/5/21

N2 - Computer-aided mammographic prompting systems require the reliable detection of a variety of signs of cancer. The emphasis of the work described is the correct classification of linear structures in mammograms. Statistical modelling, based on principal component analysis (PCA), has been developed for describing the cross-sectional profiles of linear structures, the motivation being that the shapes of intensity profiles may be characteristic of the type of structure. PCA models have been applied to whole mammograms to obtain images in which spicules, linear structures associated with stellate lesions, are emphasised. The aim is to improve the performance of automatic stellate lesion detection by concentrating on those structures most likely to be associated with lesions.

AB - Computer-aided mammographic prompting systems require the reliable detection of a variety of signs of cancer. The emphasis of the work described is the correct classification of linear structures in mammograms. Statistical modelling, based on principal component analysis (PCA), has been developed for describing the cross-sectional profiles of linear structures, the motivation being that the shapes of intensity profiles may be characteristic of the type of structure. PCA models have been applied to whole mammograms to obtain images in which spicules, linear structures associated with stellate lesions, are emphasised. The aim is to improve the performance of automatic stellate lesion detection by concentrating on those structures most likely to be associated with lesions.

UR - https://www.scopus.com/pages/publications/77954631619

U2 - 10.1007/3-540-63046-5_34

DO - 10.1007/3-540-63046-5_34

M3 - Conference Proceeding (ISBN)

SN - 3540630465

SN - 9783540630463

T3 - Lecture Notes in Computer Science

SP - 405

EP - 410

BT - Information Processing in Medical Imaging

A2 - Duncan, James

A2 - Gindi, Gene

PB - Springer Nature

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ER -

Zwiggelaar R, Parr T, Boggis C, Astley S, Taylor CJ. Statistical modelling of lines and structures in mammograms. Yn Duncan J, Gindi G, golygyddion, Information Processing in Medical Imaging: 15th International Conference, IPMI'97, Poultney, Vermont, USA, June 9-13, 1997, Proceedings. Springer Nature. 1997. t. 405-410. (Lecture Notes in Computer Science). doi: 10.1007/3-540-63046-5_34

Statistical modelling of lines and structures in mammograms

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