Two-dimensional quantitative profiling of cell morphology with serous effusion by unsupervised machine learning analysis
Cytological evaluation of serous effusion specimens is an important part of cancer diagnosis. In this study we performed two-dimensional (2D) morphometric features and clustering analysis for development of useful techniques for identification and differentiation of malignant and begin cells in sero...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Kerbala
2021
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |