Paper Info
Title
Automatic Segmentation Of Neonates Thermal Imaging For Evaluation Of Trunk Thermal Asymmetry
Abstract
This paper proposes a new method for automatic segmentation of neonates's trunks in thermal images. The method is based on an algorithm that use a threshold, associated with an active contour technique. The hypothesis is that it is possible to correlate a given temperature map, presented in a thermal image, with the persistence of the heart ductus arteriosus of a newborn. From this region of interest (ROI), it is possible to capture quantitative and statistical information on the pathology's temperature map, in order to use them as input in a machine learning applications to, in addition to aiding early diagnosis, to enable its automation. However, the presence of clothing, bandages, sheets, and other objects during the catches may alter the temperature to be considered in the diagnosis. Thus, in order to guarantee the consistency of the data extracted from such images, the region of interest must be segmented and analyzed separately. The proposed automatic segmentation obtained low error rates, generating outputs very similar to those obtained in manual segmentation.
Year
DOI
Venue
2018
10.1109/BIBM.2018.8621553
PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)
Keywords
Field
DocType
Patent Ductus Arteriosus, Automatic Segmentation, Thermal Images, Trunk, Neonates
Active contour model,Thermal,Pattern recognition,Computer science,Segmentation,Automation,Artificial intelligence,Region of interest,Asymmetry,Machine learning,Trunk
Conference
ISSN
Citations 
PageRank 
2156-1125
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Thyago Maia Tavares de Farias100.34
Manoel Eusebio de Lima2298.12
Sandra da Silva Mattos384.68
Juliana Souza S. de Araujo400.34
Lucia Roberta D. N. Mozer500.34
Felipe Alves Mourato600.34