Guest editorial introduction to the issue on nanobiophotonics

The papers in this special issue focus on the topic of nanobiophotonics, an advanced field of modern science and biomedical nanotechnology. This new field continues to vastly expend with state-of-the-art developments across the entire spectrum of biomedical applications ranging from fundamental studies of light-nanobiomaterial interactions to clinical diagnostics and therapeutics with nanophotonics. In nanobiophotonics research areas, there has been great impetus recently for noninvasive imaging and sensing intracellular structures and functions as well as for obtaining quantitative information for light-tissue interactions at the cellular, intracellular and molecular level. The papers in this issue offer some of the latest leading-edge developments in nanobiophotonics. Some of these developments include advanced optical nanoimaging and nanosensing techniques based on nanoprobes enhanced imaging and sensing principles employing various highly effective nanobiomaterials such as nanoparticles, quantum dots, and plasmonic nanostructures. These techniques offer an effective and fast way for sensing and monitoring various biomedical quantities in-vivo with a nanoresolution beyond the diffraction limit. Other new developments include optical manipulation of nanoparticles, single molecule spectroscopy and imaging, integrated nanoprobe-enhanced diagnostics and therapeutics, and novel nanobiophotonics devices

Guest editorial introduction to the issue on nanobiophotonics

The papers in this special issue focus on the topic of nanobiophotonics, an advanced field of modern science and biomedical nanotechnology. This new field continues to vastly expend with state-of-the-art developments across the entire spectrum of biomedical applications ranging from fundamental studies of light-nanobiomaterial interactions to clinical diagnostics and therapeutics with nanophotonics. In nanobiophotonics research areas, there has been great impetus recently for noninvasive imaging and sensing intracellular structures and functions as well as for obtaining quantitative information for light-tissue interactions at the cellular, intracellular and molecular level. The papers in this issue offer some of the latest leading-edge developments in nanobiophotonics. Some of these developments include advanced optical nanoimaging and nanosensing techniques based on nanoprobes enhanced imaging and sensing principles employing various highly effective nanobiomaterials such as nanoparticles, quantum dots, and plasmonic nanostructures. These techniques offer an effective and fast way for sensing and monitoring various biomedical quantities in-vivo with a nanoresolution beyond the diffraction limit. Other new developments include optical manipulation of nanoparticles, single molecule spectroscopy and imaging, integrated nanoprobe-enhanced diagnostics and therapeutics, and novel nanobiophotonics devices

Gene transfer using self-assembled ternary complexes of cationic magnetic nanoparticles, plasmid DNA and cell-penetrating tat peptide

10.1016/j.biomaterials.2009.09.085Biomaterials314769-778BIMA

Road vanishing point detection using weber adaptive local filter and salient‐block‐wise weighted soft voting

In this study, a novel and efficient technique is proposed for road vanishing point detection in challenging scenes. Currently, most existing texture‐based methods detect the vanishing point using pixel wise texture orientation estimation and voting map generation, which suffers from high computational complexity. Since only road trails (e.g. road edges, ruts, and tire tracks) would contribute informative votes to vanishing point detection, the Weber adaptive local filter is proposed to distinguish road trails from background noise, which is envisioned to reduce the workload and to eliminate uninformative votes introduced by the background noise. Furthermore, instead of using the conventional pixel‐wise voting scheme, the salient‐block‐wise weighted soft voting is developed to eliminate most of the noise votes introduced by incorrectly estimated pixel‐wise texture orientations, and to further reduce the computation time of voting stage as well. The experimental results on the benchmark dataset demonstrate that the proposed method shows superior performance. The authors’ method is about ten times faster in detection speed and outperforms by 3.6% in detection accuracy, when compared with a well‐known state‐of‐the‐art approach