Classification of Microcalcification Clusters Based on Morphological Topology Analysis

Zhili Chen; Erika R. E. Denton; Reyer Zwiggelaar

doi:10.1007/978-3-642-31271-7_67

Classification of Microcalcification Clusters Based on Morphological Topology Analysis

Zhili Chen, Erika R. E. Denton, Reyer Zwiggelaar

Adran Cyfrifiadureg

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

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The presence of microcalcification clusters is a primary sign of breast cancer. It is difficult and time consuming for radiologists to diagnose microcalcifications. In this paper, we present a novel method for classification of malignant and benign microcalcification clusters in mammograms. We analyse the connectivity/topology between individual microcalcifications within a cluster using multiscale morphology. A microcalcification graph is constructed to represent the topological structure of clusters. A multiscale topological feature vector is generated by extracting two microcalcification graph properties. The validity of the proposed method is evaluated using a dataset taken from the MIAS database. The performance of including SFS feature selection is investigated. Using a k-nearest neighbour classifier, a classification accuracy of 95% and an area under the ROC curve of 0.93 are achieved. A comparison with existing approaches is presented.

Iaith wreiddiol	Saesneg
Teitl	Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings
Is-deitl	11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings
Golygyddion	Andrew D. A. Maidment, Predrag R. Bakic, Sara Gavenonis
Cyhoeddwr	Springer Nature
Tudalennau	521-528
Nifer y tudalennau	8
ISBN (Electronig)	978-3-642-31271-7
ISBN (Argraffiad)	978-3-642-31270-0
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/978-3-642-31271-7_67
Statws	Cyhoeddwyd - 22 Meh 2012
Digwyddiad	11th International Workshop on Breast Imaging: IWDM 2012 - Philadelphia, Unol Daleithiau America Hyd: 08 Gorff 2012 → 11 Gorff 2012

Cyfres gyhoeddiadau

Enw	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Cyfrol	7361 LNCS
ISSN (Argraffiad)	0302-9743
ISSN (Electronig)	1611-3349

Cynhadledd

Cynhadledd	11th International Workshop on Breast Imaging
Gwlad/Tiriogaeth	Unol Daleithiau America
Dinas	Philadelphia
Cyfnod	08 Gorff 2012 → 11 Gorff 2012

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10.1007/978-3-642-31271-7_67

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Chen, Z., Denton, E. R. E., & Zwiggelaar, R. (2012). Classification of Microcalcification Clusters Based on Morphological Topology Analysis. Yn A. D. A. Maidment, P. R. Bakic, & S. Gavenonis (Gol.), Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings (tt. 521-528). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Cyfrol 7361 LNCS). Springer Nature. https://doi.org/10.1007/978-3-642-31271-7_67

Chen, Zhili ; Denton, Erika R. E. ; Zwiggelaar, Reyer. / Classification of Microcalcification Clusters Based on Morphological Topology Analysis. Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings. Gol. / Andrew D. A. Maidment ; Predrag R. Bakic ; Sara Gavenonis. Springer Nature, 2012. tt. 521-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{3ad77c30156f43cb92767ae15cb98b12,

title = "Classification of Microcalcification Clusters Based on Morphological Topology Analysis",

abstract = "The presence of microcalcification clusters is a primary sign of breast cancer. It is difficult and time consuming for radiologists to diagnose microcalcifications. In this paper, we present a novel method for classification of malignant and benign microcalcification clusters in mammograms. We analyse the connectivity/topology between individual microcalcifications within a cluster using multiscale morphology. A microcalcification graph is constructed to represent the topological structure of clusters. A multiscale topological feature vector is generated by extracting two microcalcification graph properties. The validity of the proposed method is evaluated using a dataset taken from the MIAS database. The performance of including SFS feature selection is investigated. Using a k-nearest neighbour classifier, a classification accuracy of 95% and an area under the ROC curve of 0.93 are achieved. A comparison with existing approaches is presented.",

author = "Zhili Chen and Denton, {Erika R. E.} and Reyer Zwiggelaar",

year = "2012",

month = jun,

day = "22",

doi = "10.1007/978-3-642-31271-7_67",

language = "English",

isbn = "978-3-642-31270-0",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Nature",

pages = "521--528",

editor = "Maidment, {Andrew D. A.} and Bakic, {Predrag R.} and Sara Gavenonis",

booktitle = "Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings",

address = "Switzerland",

note = "11th International Workshop on Breast Imaging : IWDM 2012 ; Conference date: 08-07-2012 Through 11-07-2012",

}

Chen, Z, Denton, ERE & Zwiggelaar, R 2012, Classification of Microcalcification Clusters Based on Morphological Topology Analysis. yn ADA Maidment, PR Bakic & S Gavenonis (gol.), Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), cyfrol. 7361 LNCS, Springer Nature, tt. 521-528, 11th International Workshop on Breast Imaging, Philadelphia, Pennsylvania, Unol Daleithiau America, 08 Gorff 2012. https://doi.org/10.1007/978-3-642-31271-7_67

Classification of Microcalcification Clusters Based on Morphological Topology Analysis. / Chen, Zhili; Denton, Erika R. E.; Zwiggelaar, Reyer.
Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings. gol. / Andrew D. A. Maidment; Predrag R. Bakic; Sara Gavenonis. Springer Nature, 2012. t. 521-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Cyfrol 7361 LNCS).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

TY - GEN

T1 - Classification of Microcalcification Clusters Based on Morphological Topology Analysis

AU - Chen, Zhili

AU - Denton, Erika R. E.

AU - Zwiggelaar, Reyer

PY - 2012/6/22

Y1 - 2012/6/22

N2 - The presence of microcalcification clusters is a primary sign of breast cancer. It is difficult and time consuming for radiologists to diagnose microcalcifications. In this paper, we present a novel method for classification of malignant and benign microcalcification clusters in mammograms. We analyse the connectivity/topology between individual microcalcifications within a cluster using multiscale morphology. A microcalcification graph is constructed to represent the topological structure of clusters. A multiscale topological feature vector is generated by extracting two microcalcification graph properties. The validity of the proposed method is evaluated using a dataset taken from the MIAS database. The performance of including SFS feature selection is investigated. Using a k-nearest neighbour classifier, a classification accuracy of 95% and an area under the ROC curve of 0.93 are achieved. A comparison with existing approaches is presented.

AB - The presence of microcalcification clusters is a primary sign of breast cancer. It is difficult and time consuming for radiologists to diagnose microcalcifications. In this paper, we present a novel method for classification of malignant and benign microcalcification clusters in mammograms. We analyse the connectivity/topology between individual microcalcifications within a cluster using multiscale morphology. A microcalcification graph is constructed to represent the topological structure of clusters. A multiscale topological feature vector is generated by extracting two microcalcification graph properties. The validity of the proposed method is evaluated using a dataset taken from the MIAS database. The performance of including SFS feature selection is investigated. Using a k-nearest neighbour classifier, a classification accuracy of 95% and an area under the ROC curve of 0.93 are achieved. A comparison with existing approaches is presented.

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SN - 978-3-642-31270-0

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 528

BT - Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings

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A2 - Bakic, Predrag R.

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ER -

Chen Z, Denton ERE, Zwiggelaar R. Classification of Microcalcification Clusters Based on Morphological Topology Analysis. Yn Maidment ADA, Bakic PR, Gavenonis S, golygyddion, Breast Imaging - 11th International Workshop, IWDM 2012, Proceedings: 11th International Workshop, IWDM 2012, Philadelphia, PA, USA, July 8-11, 2012, Proceedings. Springer Nature. 2012. t. 521-528. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-31271-7_67

Classification of Microcalcification Clusters Based on Morphological Topology Analysis

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