Cervical cell recognition and morphometric grading by image analysis.
Cervical cell recognition by morphometric image analysis was compared to human visual cell recognition on the same 6,375 cells from 40 dysplastic, CIS, invasive, and 10 normal pap smears. The experimental approach defined receiver operating characteristic (ROC) curves for morphometric image analysis which could be rigorously compared to previously established human visual cell recognition ROCs on the same cells. Overall performance was measured Az, the area under the ROC curves in the two instances. For morphometric image analysis cell recognition, Az = 0.91, and for human visual cell recognition, Az = 0.87. These results clearly demonstrated that morphometric image analysis is equivalent to experienced human observers in ability to recognize isolated cells from cervical smears. An approach was also developed to link the ROC analytic methods of this study to a cytopathological or histopathological grading system, or "scale", that could be expressed in terms of normal deviate units of morphometric descriptors. This approach has the advantage of describing the grading scale in terms of its ROC characteristics; in essence, it describes performance for that grading scale at any decision point along the scale, if used for two-category classification. Additionally, This concept provides for a uniform final scale, regardless of which cells or tissues are graded. Also, this type of grading scale would automatically adjust itself for measurement variance for different types of cells or tissue, by reference to normal cells or tissues, so that a standard reference could be maintained.
Bacus
J W
JW
Bacus Research Laboratories, Inc., Elmhurst, IL 60126, USA.
D002278:Carcinoma in Situ / Q000473:pathology*; D003581:Cytodiagnosis / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D012372:ROC Curve; D002583:Uterine Cervical Neoplasms / Q000473:pathology*