Accuracy of nuclear classification in cervical smear images. Quantitative impact of computational deconvolution and 3-D feature computation

Autor: R W, Mackin, L M, Newton, J N, Turner, T J, Holmes, B, Roysam
Rok vydání: 1998
Předmět:
Zdroj: Analytical and quantitative cytology and histology. 20(2)
Popis: To investigate the accuracy with which the nuclei of cells in overlapped and thick clusters in cervical/ vaginal smears can be classified independent of the segmentation algorithm used and to determine the influence of three-dimensional (3-D) processing as compared to two-dimensional (2-D) methods on classification of the nuclei.Cell clusters were imaged from 31 ThinPrep smears composed of 808 nuclei, of which 420 were determined to be abnormal by a cytotechnologist. Sets of 2-D and 3-D volumetric features of the detected nuclei were formulated, and classifiers were constructed. The effect of computational deconvolution on classification was assessed using nearest-neighbor and Wiener filter in 2-D and 3-D before calculating features. A "best focus plane" was calculated for each nucleus from the 3-D data set, and the 2-D features in this plane were also analyzed.
Databáze: OpenAIRE