Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data
2009
Autori
Dramićanin, TatjanaZeković, Ivana Lj.
Dimitrijević, Bogomir B.
Ribar, Srđan
Dramićanin, Miroslav
Članak u časopisu
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Supervised self-organizing map, a type of artificial neural network, is applied for classification of human breast tissue samples utilizing data obtained from fluorescence landscape measurements. Female breast tissue samples were taken soon after the surgical resection, identified and stored at -80 degrees C until fluorescence measurements. From fluorescence landscapes obtained in UV-VIS region spectral features showing statistically significant differences between malignant and normal samples are identified and further quantified to serve as a training input to neural network. Additional set of samples was used as a test group input to trained network in order to evaluate performance of proposed optical biopsy method. Classification sensitivity of 83.9% and specificity of 88.9% are found.
Izvor:
Acta Physica Polonica A, 2009, 116, 4, 690-692Finansiranje / projekti:
- Molekularne karakteristike kancera (RS-MESTD-MPN2006-2010-143010)
Napomena:
- International School and Conference on Photonics (PHOTONICA09), Aug 24-28, 2009, Belgrade, Serbia
DOI: 10.12693/APhysPolA.116.690
ISSN: 0587-4246
WoS: 000272317700075
Scopus: 2-s2.0-72449122761
Kolekcije
Institucija/grupa
VinčaTY - JOUR AU - Dramićanin, Tatjana AU - Zeković, Ivana Lj. AU - Dimitrijević, Bogomir B. AU - Ribar, Srđan AU - Dramićanin, Miroslav PY - 2009 UR - https://vinar.vin.bg.ac.rs/handle/123456789/6848 AB - Supervised self-organizing map, a type of artificial neural network, is applied for classification of human breast tissue samples utilizing data obtained from fluorescence landscape measurements. Female breast tissue samples were taken soon after the surgical resection, identified and stored at -80 degrees C until fluorescence measurements. From fluorescence landscapes obtained in UV-VIS region spectral features showing statistically significant differences between malignant and normal samples are identified and further quantified to serve as a training input to neural network. Additional set of samples was used as a test group input to trained network in order to evaluate performance of proposed optical biopsy method. Classification sensitivity of 83.9% and specificity of 88.9% are found. T2 - Acta Physica Polonica A T1 - Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data VL - 116 IS - 4 SP - 690 EP - 692 DO - 10.12693/APhysPolA.116.690 ER -
@article{ author = "Dramićanin, Tatjana and Zeković, Ivana Lj. and Dimitrijević, Bogomir B. and Ribar, Srđan and Dramićanin, Miroslav", year = "2009", abstract = "Supervised self-organizing map, a type of artificial neural network, is applied for classification of human breast tissue samples utilizing data obtained from fluorescence landscape measurements. Female breast tissue samples were taken soon after the surgical resection, identified and stored at -80 degrees C until fluorescence measurements. From fluorescence landscapes obtained in UV-VIS region spectral features showing statistically significant differences between malignant and normal samples are identified and further quantified to serve as a training input to neural network. Additional set of samples was used as a test group input to trained network in order to evaluate performance of proposed optical biopsy method. Classification sensitivity of 83.9% and specificity of 88.9% are found.", journal = "Acta Physica Polonica A", title = "Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data", volume = "116", number = "4", pages = "690-692", doi = "10.12693/APhysPolA.116.690" }
Dramićanin, T., Zeković, I. Lj., Dimitrijević, B. B., Ribar, S.,& Dramićanin, M.. (2009). Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data. in Acta Physica Polonica A, 116(4), 690-692. https://doi.org/10.12693/APhysPolA.116.690
Dramićanin T, Zeković IL, Dimitrijević BB, Ribar S, Dramićanin M. Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data. in Acta Physica Polonica A. 2009;116(4):690-692. doi:10.12693/APhysPolA.116.690 .
Dramićanin, Tatjana, Zeković, Ivana Lj., Dimitrijević, Bogomir B., Ribar, Srđan, Dramićanin, Miroslav, "Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data" in Acta Physica Polonica A, 116, no. 4 (2009):690-692, https://doi.org/10.12693/APhysPolA.116.690 . .