A Prostate Cancer Computer Aided Diagnosis Software including Malignancy Tumor Probabilistic Classification

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

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.

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Paper Citation


in Harvard Style

Savino A., Benso A., Di Carlo S., Giannini V., Vignati A., Politano G., Mazzetti S. and Regge D. (2014). A Prostate Cancer Computer Aided Diagnosis Software including Malignancy Tumor Probabilistic Classification . In Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2014) ISBN 978-989-758-014-7, pages 49-54. DOI: 10.5220/0004799100490054


in Bibtex Style

@conference{bioimaging14,
author={Alessandro Savino and Alfredo Benso and Stefano Di Carlo and Valentina Giannini and Anna Vignati and Gianfranco Politano and Simone Mazzetti and Daniele Regge},
title={A Prostate Cancer Computer Aided Diagnosis Software including Malignancy Tumor Probabilistic Classification},
booktitle={Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2014)},
year={2014},
pages={49-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004799100490054},
isbn={978-989-758-014-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2014)
TI - A Prostate Cancer Computer Aided Diagnosis Software including Malignancy Tumor Probabilistic Classification
SN - 978-989-758-014-7
AU - Savino A.
AU - Benso A.
AU - Di Carlo S.
AU - Giannini V.
AU - Vignati A.
AU - Politano G.
AU - Mazzetti S.
AU - Regge D.
PY - 2014
SP - 49
EP - 54
DO - 10.5220/0004799100490054