Fig 1.
Types of White Blood Cell.
Fig 2.
Normal Red and White Blood Cell.
Fig 3.
The Proposed Framework.
Fig 4.
Generic structure of ResNet.
Fig 5.
Residual block structure.
Fig 6.
ODE block Structure.
Fig 7.
Architecture of the proposed technique.
Fig8.
(a) The accuracy of the training and validation set (b) The losses in the training and validation set.
Fig 9.
(a) Orignal Image (b) Label Images (c) Pre-segmentation using Unet++.
Fig 10.
(a) Foreground Marker (b) Segmented White Blood Cells.
FIG 11.
(a) Original ima ge (b) Label image (c) Final Result.
Table 1.
Confusion matrix.
Table 2.
Quantitative results of three algorithms.
Fig 12.
The box-plots of three measure segmentation accuracy.