Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials [electronic resource]

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Tác giả:

Ngôn ngữ: eng

Ký hiệu phân loại: 577.3 Forest ecology

Thông tin xuất bản: Los Alamos, N.M. : Oak Ridge, Tenn. : Los Alamos National Laboratory ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2013

Mô tả vật lý: Medium: ED : , digital, PDF file.

Bộ sưu tập: Metadata

ID: 261634

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.
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