Segmenting overlapped objects in images. A study to support the diagnosis of sickle cell disease.

Abstract

[eng] Overlapped objects are found on multiple kinds of images, they are a source of problem due its partial information. Multiple types of algorithm are used to address this problem from simple and naive methods to more complex ones. In this work we propose a new method for the segmentation of overlapped object. We also introduce some known neural networks architectures to solve this problem. Finally we compare the results of this algorithm with the state-of-art in two experiments: one with a new dataset, developed specially for this work, and red blood smears from sickle-cell disease patients.