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 |
Fingerprint
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
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
}
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
AN - SCOPUS:84902354664
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 -