https://scholars.lib.ntu.edu.tw/handle/123456789/553967
標題: | A Heuristic framework for image filtering and segmentation: Application to blood vessel immunohistochemistry | 作者: | Tsou, C.-H. Lu, Y.-C. ANG YUAN YEUN-CHUNG CHANG CHUNG-MING CHEN |
公開日期: | 2015 | 卷: | 2015 | 來源出版物: | Analytical Cellular Pathology | 摘要: | The blood vessel density in a cancerous tissue sample may represent increased levels of tumor growth. However, identifying blood vessels in the histological (tissue) image is difficult and time-consuming and depends heavily on the observer's experience. To overcome this drawback, computer-aided image analysis frameworks have been investigated in order to boost object identification in histological images. We present a novel algorithm to automatically abstract the salient regions in blood vessel images. Experimental results show that the proposed framework is capable of deriving vessel boundaries that are comparable to those demarcated manually, even for vessel regions with weak contrast between the object boundaries and background clutter. ? 2015 Chi-Hsuan Tsou et al. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/553967 | ISSN: | 2210-7177 | DOI: | 10.1155/2015/589158 | SDG/關鍵字: | A549 cell line; Article; autoanalysis; calculation; cardiovascular system examination; color vision; computer analysis; filtration; frozen section; heuristics; histogram; human; human cell; illumination; image analysis; immunohistochemistry; luminance; machine learning; non small cell lung cancer; priority journal; algorithm; automation; blood vessel; cluster analysis; fuzzy logic; image processing; immunohistochemistry; pathology; staining; tumor cell line; Algorithms; Automation; Blood Vessels; Cell Line, Tumor; Cluster Analysis; Fuzzy Logic; Humans; Image Processing, Computer-Assisted; Immunohistochemistry; Staining and Labeling |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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