Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "87.19.xj" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Development of Low-Cost Photodynamic Therapy Device
Autorzy:
Momchilov, N.
Bliznakova, I.
Borisova, E.
Troyanova, P.
Avramov, L.
Powiązania:
https://bibliotekanauki.pl/articles/2047897.pdf
Data publikacji:
2007-11
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
42.72.Bj
87.64.kv
87.19.xj
Opis:
Photodiagnosis and photodynamic therapy of non-melanoma skin cancers using delta-aminolevulinic acid/protoporphyrin IX (5-ALA/PpIX) give a combined application with broadest dissemination in the current clinical practice. The problems with using of lasers as light sources are the expenses associated with the operation of these types of installations. This is why we test the capability of cheaper sources - light-emitting diodes at 405 nm for fluorescence excitation of PpIX and 635 nm for photodynamic action initiation. A LED matrix is developed in our laboratory using two types of LEDs and a combined photodiagnosis/photodynamic theory device applicable for clinical practice is built. Geometrically matrix is formed in such way that power density at 635 nm is about 40 mW/cm$\text{}^{2}$, which allow to reach treatment doses for a 15-20 min irradiation depending of the lesion size in the focus of the system. The therapeutic mode of system developed can be used also with some other photosensitizers from the porphyrins derivatives family.
Źródło:
Acta Physica Polonica A; 2007, 112, 5; 1125-1130
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optical Biopsy Method for Breast Cancer Diagnosis Based on Artificial Neural Network Classification οf Fluorescence Landscape Data
Autorzy:
Dramićanin, T.
Zeković, I.
Dimitrijević, B.
Ribar, S.
Dramićanin, M.
Powiązania:
https://bibliotekanauki.pl/articles/1795706.pdf
Data publikacji:
2009-10
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
87.64.kv
84.35.+i
87.19.xj
33.50.-j
Opis:
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°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.
Źródło:
Acta Physica Polonica A; 2009, 116, 4; 690-692
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies