A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification

Alessandro Savino; Alfredo Benso; Stefano Di Carlo; Valentina Giannini; Anna Vignati; Simone Mazzetti; Gianfranco Politano; Daniele Regge

A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification

Alessandro Savino, Alfredo Benso, Stefano Di Carlo, Valentina Giannini, Anna Vignati, Simone Mazzetti, Gianfranco Politano, Daniele Regge

Istituto Oncologico Candiolo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Screening based on Prostate Specific Antigen (PSA) reduces the rate of death by 31%, but it is associated with a high risk of over-diagnosis and over-treatment. Prostate Magnetic Resonance Imaging (MRI) has the potential to improve the specificity of PSA-based screening scenarios as a non-invasive detection tool. Research community effort focused on classification techniques based on MRI in order to produce a malignancy likelihood map. The paper describes the prototyping design, the implemented work-flow and the software architecture of a Computer Aided Diagnosis (CAD) software which aims at providing a comprehensive diagnostic tool, including an integrated classification stack, from a preliminary registration of images to the classification process. This software can improve the diagnostic accuracy of the radiologist, reduce reader variability and speed up the whole diagnostic work-up.

Original language	English
Title of host publication	BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
Publisher	SciTePress
Pages	49-54
Number of pages	6
ISBN (Print)	9789897580147
Publication status	Published - 2014
Event	1st International Conference on Bioimaging, BIOIMAGING 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 - Angers, Loire Valley, France Duration: Mar 3 2014 → Mar 6 2014

Other

Other	1st International Conference on Bioimaging, BIOIMAGING 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
Country	France
City	Angers, Loire Valley
Period	3/3/14 → 3/6/14

Keywords

Computer Aided Diagnosis
Magnetic Resonance Imaging (MRI)
Malignancies Probabilistic Classification
Prostate Cancer
Software Design

ASJC Scopus subject areas

Control and Systems Engineering

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Savino, A., Benso, A., Di Carlo, S., Giannini, V., Vignati, A., Mazzetti, S., Politano, G., & Regge, D. (2014). A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification. In BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014 (pp. 49-54). SciTePress.

A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification. / Savino, Alessandro; Benso, Alfredo; Di Carlo, Stefano; Giannini, Valentina; Vignati, Anna; Mazzetti, Simone; Politano, Gianfranco; Regge, Daniele.

BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress, 2014. p. 49-54.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Savino, A, Benso, A, Di Carlo, S, Giannini, V, Vignati, A, Mazzetti, S, Politano, G & Regge, D 2014, A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification. in BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress, pp. 49-54, 1st International Conference on Bioimaging, BIOIMAGING 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014, Angers, Loire Valley, France, 3/3/14.

Savino A, Benso A, Di Carlo S, Giannini V, Vignati A, Mazzetti S et al. A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification. In BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress. 2014. p. 49-54

Savino, Alessandro ; Benso, Alfredo ; Di Carlo, Stefano ; Giannini, Valentina ; Vignati, Anna ; Mazzetti, Simone ; Politano, Gianfranco ; Regge, Daniele. / A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification. BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014. SciTePress, 2014. pp. 49-54

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title = "A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification",

abstract = "Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Screening based on Prostate Specific Antigen (PSA) reduces the rate of death by 31%, but it is associated with a high risk of over-diagnosis and over-treatment. Prostate Magnetic Resonance Imaging (MRI) has the potential to improve the specificity of PSA-based screening scenarios as a non-invasive detection tool. Research community effort focused on classification techniques based on MRI in order to produce a malignancy likelihood map. The paper describes the prototyping design, the implemented work-flow and the software architecture of a Computer Aided Diagnosis (CAD) software which aims at providing a comprehensive diagnostic tool, including an integrated classification stack, from a preliminary registration of images to the classification process. This software can improve the diagnostic accuracy of the radiologist, reduce reader variability and speed up the whole diagnostic work-up.",

keywords = "Computer Aided Diagnosis, Magnetic Resonance Imaging (MRI), Malignancies Probabilistic Classification, Prostate Cancer, Software Design",

author = "Alessandro Savino and Alfredo Benso and {Di Carlo}, Stefano and Valentina Giannini and Anna Vignati and Simone Mazzetti and Gianfranco Politano and Daniele Regge",

year = "2014",

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AU - Savino, Alessandro

AU - Benso, Alfredo

AU - Di Carlo, Stefano

AU - Giannini, Valentina

AU - Vignati, Anna

AU - Mazzetti, Simone

AU - Politano, Gianfranco

AU - Regge, Daniele

PY - 2014

Y1 - 2014

N2 - Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Screening based on Prostate Specific Antigen (PSA) reduces the rate of death by 31%, but it is associated with a high risk of over-diagnosis and over-treatment. Prostate Magnetic Resonance Imaging (MRI) has the potential to improve the specificity of PSA-based screening scenarios as a non-invasive detection tool. Research community effort focused on classification techniques based on MRI in order to produce a malignancy likelihood map. The paper describes the prototyping design, the implemented work-flow and the software architecture of a Computer Aided Diagnosis (CAD) software which aims at providing a comprehensive diagnostic tool, including an integrated classification stack, from a preliminary registration of images to the classification process. This software can improve the diagnostic accuracy of the radiologist, reduce reader variability and speed up the whole diagnostic work-up.

AB - Prostate Cancer (PCa) is the most common solid neoplasm in males and a major cause of cancer-related death. Screening based on Prostate Specific Antigen (PSA) reduces the rate of death by 31%, but it is associated with a high risk of over-diagnosis and over-treatment. Prostate Magnetic Resonance Imaging (MRI) has the potential to improve the specificity of PSA-based screening scenarios as a non-invasive detection tool. Research community effort focused on classification techniques based on MRI in order to produce a malignancy likelihood map. The paper describes the prototyping design, the implemented work-flow and the software architecture of a Computer Aided Diagnosis (CAD) software which aims at providing a comprehensive diagnostic tool, including an integrated classification stack, from a preliminary registration of images to the classification process. This software can improve the diagnostic accuracy of the radiologist, reduce reader variability and speed up the whole diagnostic work-up.

KW - Computer Aided Diagnosis

KW - Magnetic Resonance Imaging (MRI)

KW - Malignancies Probabilistic Classification

KW - Prostate Cancer

KW - Software Design

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SN - 9789897580147

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BT - BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014

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Y2 - 3 March 2014 through 6 March 2014

ER -

A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification

Abstract

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Keywords

ASJC Scopus subject areas

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