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Building of a composite virtual slide from contiguous tissue samples

BACKGROUND: Currently available microscope slide scanners produce whole slide images at various resolutions from histological sections. Nevertheless, acquisition area and so visualization of large tissue samples are limited by the standardized size of glass slides, used daily in pathology department...

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Detalles Bibliográficos
Autores principales: Plancoulaine, Benoît, Oger, Myriam, Elie, Nicolas, Belhomme, Philippe, Herlin, Paulette, Nasri, Abir, Augé, Célia, Brécin, Mylène, Marnay, Jacques, Bor-Angelier, Catherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4305979/
https://www.ncbi.nlm.nih.gov/pubmed/25565295
http://dx.doi.org/10.1186/1746-1596-9-S1-S9
Descripción
Sumario:BACKGROUND: Currently available microscope slide scanners produce whole slide images at various resolutions from histological sections. Nevertheless, acquisition area and so visualization of large tissue samples are limited by the standardized size of glass slides, used daily in pathology departments. The proposed solution has been developed to build composite virtual slides from images of large tumor fragments. MATERIALS AND METHODS: Images of HES or immunostained histological sections of carefully labeled fragments from a representative slice of breast carcinoma were acquired with a digital slide scanner at a magnification of 20×. The tiling program involves three steps: the straightening of tissue fragment images using polynomial interpolation method, and the building and assembling of strips of contiguous tissue sample whole slide images in × and y directions. The final image is saved in a pyramidal BigTiff file format. The program has been tested on several tumor slices. A correlation quality control has been done on five images artificially cut. RESULTS: Sixty tumor slices from twenty surgical specimens, cut into two to twenty six pieces, were reconstructed. A median of 98.71% is obtained by computing the correlation coefficients between native and reconstructed images for quality control. CONCLUSIONS: The proposed method is efficient and able to adapt itself to daily work conditions of classical pathology laboratories.