Image Segmentation Techniques for Healthcare Systems
- Authors: Gambino, Orazio; Conti, Vincenzo; Galdino, Sergio; Valenti, Cesare Fabio; Dos Santos, Wellington Pinheiro
- Publication year: 2019
- Type: Articolo in rivista (Articolo in rivista)
- OA Link: http://hdl.handle.net/10447/356407
The present special issue of the Journal of Healthcare Engineering collects articles written by researchers scattered around the world who belong to the academic and industrial environments. The papers of this special issue have been selected by a rigorous peer-reviewing process with the support of at least two reviewers per paper, along with the opinion written in the final decision by a component of the editorial staff. Different methods on biomedical image segmentation dedicated to healthcare systems have been developed regarding, for example, the fields of machine learning, deformable models, fuzzy models, and so on. Such methods have been applied on different biomedical image modalities (MRI, CT, mammograms, optical coherence tomography, and others) of various anatomical districts, such as the brain, thyroid, lung, and breast. J. Gauci et al. present an automatic approach to determine the temperature of the body’s extremities by means of thermal images in diabetic patients.