Implementation of a low-cost mobile devices to support medical diagnosis.
Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Carlos
C
García Sánchez
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Guillermo
G
Botella Juan
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Fermín
F
Ayuso Márquez
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Diego
D
González Rodríguez
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Manuel
M
Prieto-Matías
Department of Computer Architecture and Automation, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Francisco
F
Tirado Fernández
D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*