Recently, a bacteria-based drug delivery system has been proposed to achieve effective and localized drug delivery. Researchers have shown that flagellated bacteria have a chemotactic property to tumor cells, and they can be used as an energy source for active drug delivery. Our previous results have reported that a circular droplet made by a biodegradable polymer can be used in this bacteria-based, robotic drug delivery. In this paper, using laminated cubic structures made of several layers of biodegradable polymers for bacteria-based microrobot is proposed. The structures are made by laminating polymer layers and then, micromachining them using a deep X-ray synchrotron radiation into 40 μm x 40 μm x 40 μm cubes. The cubic structure is more beneficial in attaching bacteria in only selective surface directions than a circular structure, and in controlling the volume of drugs to be encapsulated with the outer polymer layer.
Binocular indirect ophthalmoscope (BIO) provides a wider view of fundus with stereopsis contrary to the direct one.
Proposed system is composed of portable BIO and 3D viewing unit. The illumination unit of BIO utilized high flux LED
as a light source, LED condensing lens cap for beam focusing, color filters and small lithium ion battery. In optics unit of
BIO, beam splitter was used to distribute an examinee's fundus image both to examiner's eye and to CMOS camera
module attached to device. Captured retinal video stream data from stereo camera modules were sent to PC through USB
2.0 connectivity. For 3D viewing, two video streams having parallax between them were aligned vertically and
horizontally and made into side-by-side video stream for cross-eyed stereoscopy. And the data were converted into
autostereoscopic video stream using vertical interlacing for stereoscopic LCD which has glass 3D filter attached to the
front side of it. Our newly devised system presented the real-time 3-D view of fundus to assistants with less dizziness
than cross-eyed stereoscopy. And the BIO showed good performance compared to conventional portable BIO (Spectra
Plus, Keeler Limited, Windsor, UK).
Hessian matrix is the square matrix of second partial derivatives of a scalar-valued function and is well known for object
recognition in computer vision and medical shape analysis. Previous curvature based polyp detection algorithms generate
myriad of false positives. Hessian-matrix based method, however, is more sensitive to local shape features, so easily
reduce false positives. Calculation of Hessian matrix on 3D CT data and Eigen decomposition of the matrix gives three
Eigen values and vectors at each voxel. Using these Eigen values, we can figure out which type of intensity structures
(blob, line, and sheet-like) is on the given voxel. We focus on detecting blob-like object automatically. In the inner
colonic wall structures, blob-like, line-like, and sheet-like objects represent polyps, folds and wall, respectively. In
addition, to improve the performance of the algorithm, Gaussian blurring factor and shape threshold parameters are
optimized. Before Hessian matrix calculation, smoothing the given region using Gaussian kernel with small deviation is
necessary to enhance local intensity structures. To optimize the parameters and validate this method, we have produced
anthropomorphic pig phantoms. Fourteen phantoms with 103 polyps (16 polyps <6mm, 87 >= 6mm) were used. CT scan
was performed with 1mm slice thickness. Our detection algorithm found 84 polyps (81.6%) correctly. Average number
of false positives is 7.9 at each CT scan. This results show that our algorithm is clinically applicable for polyp detection,
because of high sensitivity and relatively low false positive detections.
We developed the asymmetry analyzing system for facial palsy patient's rehabilitation progress study. Using PC
standard imaging device, captured 640*480 RGB image is converted into HSV space. A Lip-shape mask is extracted by
thresholding. By taking 5 regions consisted in one region on lip and four regions on face skin, reasonable thresholds are
determined by Fuzzy C-Means clustering. The extreme points on the lip shape mask are extracted to get the seeds for
tracking. Segmented seed points are tracking by Iterative Lucas-Kanade tracking method in pyramids at 30 fps and
recording simultaneously. To reduce the disk writing load on computer, we use asynchronous mode file writing, which is
going to transfer to and review by clinician. Tracking shows quite reliable results, but sometimes the tracked points are
following along the lip line because of the similar contrasts. Therefore, the first strategy to improve the reliability of
tracking is using the high contrast points, such as left and right maximal point of lip shape. The second is clustering some
points near the maximal points and eliminating outlying tracking points. The third is rechecking the lip shape using lip
segmentation when the operator confirms that subject's maximal lip moving. Left and right tracking points are compared
in forms of trajectory plot.
Introduction: Indocyanin green fundus angiographic images (ICGA) of the eyes is useful method in detecting and characterizing the choroidal neovascularization (CNV), which is the major cause of the blindness over 65 years of age. To investigate the quantitative analysis of the blood flow on ICGA, systematic approach for automatic registration of using mutual information and a quantitative analysis was developed. Methods: Intermittent sequential images of indocyanin green angiography were acquired by Heidelberg retinal angiography that uses the laser scanning system for the image acquisition. Misalignment of each image generated by the minute eye movement of the patients was corrected by the mutual information method because the distribution of the contrast media on image is changing throughout the time sequences. Several region of interest (ROI) were selected by a physician and the intensities of the selected region were plotted according to the time sequences. Results: The registration of ICGA time sequential images is required not only translate transform but also rotational transform. Signal intensities showed variation based on gamma-variate function depending on ROIs and capillary vessels show more variance of signal intensity than major vessels. CNV showed intermediate variance of signal intensity and prolonged transit time. Conclusion: The resulting registered images can be used not only for quantitative analysis, but also for perfusion analysis. Various investigative approached on CNV using this method will be helpful in the characterization of the lesion and follow-up.