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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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 languageEnglish
Title of host publicationBIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
PublisherSciTePress
Pages49-54
Number of pages6
ISBN (Print)9789897580147
Publication statusPublished - 2014
Event1st 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 2014Mar 6 2014

Other

Other1st International Conference on Bioimaging, BIOIMAGING 2014 - Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014
CountryFrance
CityAngers, Loire Valley
Period3/3/143/6/14

Fingerprint

Computer aided diagnosis
Tumors
Antigens
Screening
Software architecture
Magnetic Resonance Imaging

Keywords

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

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Savino, A., Benso, A., Di Carlo, S., Giannini, V., Vignati, A., Mazzetti, S., ... 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 proceedingConference 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
@inproceedings{4808488f460a48a4975006bd262920c1,
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",
language = "English",
isbn = "9789897580147",
pages = "49--54",
booktitle = "BIOIMAGING 2014 - 1st International Conference on Bioimaging, Proceedings; Part of 7th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2014",
publisher = "SciTePress",

}

TY - GEN

T1 - A prostate cancer computer aided diagnosis software including malignancy tumor probabilistic classification

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

UR - http://www.scopus.com/inward/record.url?scp=84902354664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902354664&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9789897580147

SP - 49

EP - 54

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

PB - SciTePress

ER -