Automated analysis using CellaVision DM9600

CellaVision DM9600 uses artificial neural networks to locate, identify, and categorize RBCs. This system automatically categorizes RBCs (pre-classification), and the user subsequently manually verifies or re-classifies the RBCs before signing off the sample (post-classification). The CellaVision Advanced RBC Application uses a 50× objective lens to select and scan one zone of the slide for the analysis of approximately 2,000 to 4,000 RBCs per blood smear [5, 6]. The RBC category results are reported semi-quantitatively in four flag levels (0, 1, 2, and 3) based on cut-off percentages established by each laboratory. The results may also be represented quantitatively as a percentage count of all analyzed RBCs (Fig. 1). We used software version 7.0.1 for the evaluation.

Overview of the CellaVision DM9600 Advanced RBC Application. (A) The software provides an overview image using the RBC morphological category results, which are graded semi-quantitatively in four flag levels. (B) Image depicting individual cells categorized into each RBC morphological abnormality.

Abbreviation: RBC, red blood cell.