I. INTRODUCTION
TRADITIONAL approaches for the segmentation of medical
images such as the use of morphological filters or
thresholding-based techniques may cause either loss of
information for quantification purposes or variability among
observers, which are not desirable for analysis and/or
quantification. Therefore, investigation on the application of
state-of-art segmentation techniques to IlCT is an important
research topic, due to the interesting characteristics and
applications of that imaging modality.
In the present work we describe the application of Artificial
Neural Networks trained with Statistical Context Information
in order to segment a slice of a Rhodnius Prolixus insect
(vector of the Chagas's disease) IlCT scan. Preliminary results
demonstrate the viability of the method in the segmentation of