Cytodiagnosis by static electronic images-Telecytology of cervical smears and breast aspirates.
نویسندگان
چکیده
منابع مشابه
Telecytology: intraobserver and interobserver reproducibility in the diagnosis of cervical-vaginal smears.
Telecytologic diagnosis of cervical-vaginal smears is potentially useful because it could allow more efficient use of cytopathologist resources and expertise. A pathologist in one location could, in principle, review cytotechnologists' findings using a video display hundreds or thousands of miles away. Currently, bandwidth restrictions limit practical implementation of such a system to review o...
متن کاملCompare of Sensitivity and Specificity of Liquid-Based and Conventional Cytology Smears in Fine Needle Aspirates for Diagnosis of Breast Mass
Introduction: This study aimed to compare the cytology results obtained by the conventional smear method with those obtained by the liquid-based method for the diagnosis of palpable breast masses in women referred to the clinic of Shahid Mohammadi Hospital in Bandar Abbas city. Methods: The research method was descriptive–cross-sectional. The research sample was selected based on purposive and ...
متن کاملTerminology of Cervical Smears
Carcinoma of the cervix is a slow growing cancer, which is preceded by precancerous lesions named cervical intra-epithelial neoplasia (CIN). The slow progression of precancerous lesions allows detecting the lesion at this stage. The cervical smear allows detecting cytological abnormalities at the microscope. The cells are taken by a spatula or a brush, smeared on glasses and stained by the meth...
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The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most relevant information of X. These eigenvectors are called principal components [8]. Ass...
متن کاملCompression of Breast Cancer Images By Principal Component Analysis
The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most relevant information of X. These eigenvectors are called principal components [8]. Ass...
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ژورنال
عنوان ژورنال: The Journal of the Japanese Society of Clinical Cytology
سال: 1999
ISSN: 1882-7233,0387-1193
DOI: 10.5795/jjscc.38.517