Fluorescent Imaging and Multifusion Segmentation for Enhanced Visualization and Delineation of Glioblastomas Margins
| Autor: | Nicolas Douard, Wafa Elmannai, Charles Barnes, George C. Giakos, Suman Shrestha, Yi Wang, Martin Nowak, Paniz Foroutan, Alexandros Kerwick, George Livanos, Thomas Cambria, Gloria Bauman, Jennifer L. Cutter, Tannaz Farrahi, Zoe Giakos, Michalis Zervakis, Anthony Beninati, James P. Basilion, Aditi Deshpande |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Fluorescence-lifetime imaging microscopy
Computer science entropy-based thresholding Brain tumor Fluorescence-guided surgery (FGS) Image processing 02 engineering and technology confocal laser endomicroscopy (CLE) glioblastoma multiforme (GBM) Green fluorescent protein mean shift clustering Otsu thresholding 03 medical and health sciences 0302 clinical medicine fluorescence imaging Glioma unsupervised segmentation tools 0202 electrical engineering electronic engineering information engineering medicine Segmentation Mean-shift T57-57.97 Applied mathematics. Quantitative methods medicine.disease Autofluorescence 030220 oncology & carcinogenesis imaging of cancer margins 020201 artificial intelligence & image processing fusion of cluster-based segmentation schemes Biomedical engineering |
| Zdroj: | Signals Volume 2 Issue 2 Pages 20-335 Signals, Vol 2, Iss 20, Pp 304-335 (2021) |
| ISSN: | 2624-6120 |
| DOI: | 10.3390/signals2020020 |
| Popis: | This study investigates the potential of fluorescence imaging in conjunction with an original, fused segmentation framework for enhanced detection and delineation of brain tumor margins. By means of a test bed optical microscopy system, autofluorescence is utilized to capture gray level images of brain tumor specimens through slices, obtained at various depths from the surface, each of 10 µm thickness. The samples used in this study originate from tumor cell lines characterized as Gli36ϑEGRF cells expressing a green fluorescent protein. An innovative three-step biomedical image analysis framework is presented aimed at enhancing the contrast and dissimilarity between the malignant and the remaining tissue regions to allow for enhanced visualization and accurate extraction of tumor boundaries. The fluorescence image acquisition system implemented with an appropriate unsupervised pipeline of image processing and fusion algorithms indicates clear differentiation of tumor margins and increased image contrast. Establishing protocols for the safe administration of fluorescent protein molecules, these would be introduced into glioma tissues or cells either at a pre-surgery stage or applied to the malignant tissue intraoperatively typical applications encompass areas of fluorescence-guided surgery (FGS) and confocal laser endomicroscopy (CLE). As a result, this image acquisition scheme could significantly improve decision-making during brain tumor resection procedures and significantly facilitate brain surgery neuropathology during operation. |
| Databáze: | OpenAIRE |
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