Abstract
The rapid approaching of elderly era has caused the impending needs for applying new technology for elderly and disabled people to improve health conditions and increase the quality of life. Under such a situation, novel bioengineering devices and tools are being developed to gain better understanding of human metabolic, anatomy and functions of organs. On the other hand, chronic diseases cause healthcare to be shared by daily health maintenance, triggering the impending need for intelligence of devices in which preliminary decisions need to be built into the system for providing preliminary recommendations. To achieve the development of novel and intelligent bioengineering and healthcare devices, the techniques of multidimensional signal and image processing and analysis can play one of the major roles. Compared with one dimensional signal analysis, the analysis of multidimensional signals and images provides more information. On the other hand, the high dimensionality of data may also cause large computational cost and, therefore, reduce the feasibility. Consequently, how to extract information for best estimation of health situations from the correlated or uncorrelated signals needs to be addressed. The goal of this special issue is to provide most up-to-date and recent advances of multidimensional signal and image analysis techniques for healthcare applications. This special issue serves as a forum and venue for researchers in academia, clinics and industries working in this area to share their experiences with the readers. For this special issue, we received a total of 13 submissions, each of which has gone through rigorous peer review. Based on the review results, six papers are selected for publication in this special issue, with brief description as follows. In “Enhancement of Blood Vessels in Retinal Imaging Using the Nonsubsampled Contourlet Transform”, Lee et al. propose a modified version of the nonsubsampled
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