SEM Image Analysis of Megaloblastic Anemia

Megaloblastic anemias are a heterogeneous group of disorders that have common blood abnormalities and symptoms. Its characteristics consist of large oval erythrocytes, hyper segmented neutrophils and large abnormal platelets. In this paper, a new approach is adopted for the diagnosis of megaloblastic anemia in blood smear. Different SEM images of megaloblastic anemia are compared with two level set segmentation models for the diagnosis. The image segmentation result of level set method is subject to appropriate initial contour and optimal configuration of controlling parameters. These models can detect objects whose boundaries are not defined by gradient and local regions. This paper describes an autonomous approach for deciding initial contour of level set and hence help in diagnosis.