Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data
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.
Source:
Acta Physica Polonica A, 2009, 116, 4, 690-692Publisher:
- Polish Acad Sciences Inst Physics, Warsaw
Funding / projects:
- Molekularne karakteristike kancera (RS-MESTD-MPN2006-2010-143010)
DOI: 10.12693/APhysPolA.116.690
ISSN: 0587-4246
WoS: 000272317700075
Scopus: 2-s2.0-72449122761
Collections
Institution/Community
Mašinski fakultetTY - JOUR AU - Dramićanin, Miroslav AU - Zeković, Ivana AU - Dimitrijević, B. AU - Ribar, Srđan AU - Dramićanin, Miroslav PY - 2009 UR - https://machinery.mas.bg.ac.rs/handle/123456789/973 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. PB - Polish Acad Sciences Inst Physics, Warsaw T2 - Acta Physica Polonica A T1 - Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data EP - 692 IS - 4 SP - 690 VL - 116 DO - 10.12693/APhysPolA.116.690 ER -
@article{ author = "Dramićanin, Miroslav and Zeković, Ivana and Dimitrijević, 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.", publisher = "Polish Acad Sciences Inst Physics, Warsaw", journal = "Acta Physica Polonica A", title = "Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification of Fluorescence Landscape Data", pages = "692-690", number = "4", volume = "116", doi = "10.12693/APhysPolA.116.690" }
Dramićanin, M., Zeković, I., Dimitrijević, 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 Polish Acad Sciences Inst Physics, Warsaw., 116(4), 690-692. https://doi.org/10.12693/APhysPolA.116.690
Dramićanin M, Zeković I, Dimitrijević B, 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, Miroslav , Zeković, Ivana, Dimitrijević, 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 . .