The ELISA (enzyme-linked immunosorbent assay) spot assay is a method widely used by immunologists to enumerate cytokine-producing cells within a specific cell population. The ELISA results are presented in an image containing numerous colored spots. We present a method to identify the spots in the image and report on important statistics regarding them. The proposed method employs color analysis in the CIE L*u*v* color space and matched filter technique. The system is trained to obtain a standard color for the spots and calculate the color differences between the spots and background in the L*u*v* space. Matched filters are then used to remove noise and enhance the spots in the color difference map. Intensity thresholding is applied to obtain a binary image in which the pixels in the spots have a grayscale of 1 while the grayscale of the other pixels is 0. A software system is implemented, based on this method, to help immunologists analyze the results obtained from the ELISA.
Accurate 3-D rectangular meshes construction of pipes is important and valuable for Engineering and Medicine to analyze the fluid mechanics. Hypertrophied prostate is suffered common by aged patient. Medicine trusts that the pathogenic reason can be interpreted using the statistics of analysis of fluid mechanics. We use serials of methods to construct the 3-D rectangular meshes of a patient urethra CT volumetric data given from medicine, and for mechanic engineering to gather statistics.
KEYWORDS: Tablets, Picture Archiving and Communication System, Databases, Local area networks, Personal digital assistants, Image resolution, Operating systems, Image retrieval, Telecommunications, Zoom lenses
A PACS mobile terminal has applications in ward round, emergency room and remote teleradiology consultation. Personal Digital Assistants (PDAs) have the highest mobility and are used for many medical applications. However, their roles are limited in the field of radiology due to small screen size. In this study, we built a wireless PACS terminal using a hand-held tablet-PC. A tablet PC (X-pilot, LEO systems, Taiwan) running the WinCE operating systems was used as our mobile PACS terminal. This device is equipped with 800×600 resolution 10.4 inch TFT monitor. The network connection between the tablet PC and the server was linked via wireless LAN (IEEE 802.11b).
Accurate analysis of insect brain structures in digital confocal microscopic images is valuable and important to biology research needs. The first step is to segment meaningful structures from images. Active contour model, known as snakes, is widely used for segmentation of medical images. A new class of active contour model called gradient vector flow snake has been introduced in 1998 to overcome some critical problems encountered in the traditional snake. In this paper, we use gradient vector flow snake to segment the mushroom body and the central body from the confocal microscopic insect brain images. First, an edge map is created from images by some edge filters. Second, a gradient vector flow field is calculated from the edge map using a computational diffusion process. Finally, a traditional snake deformation process starts until it reaches a stable configuration. User interface is also provided here, allowing users to edit the snake during deformation process, if desired. Using the gradient vector flow snake as the main segmentation method and assist with user interface, we can properly segment the confocal microscopic insect brain image for most of the cases. The identified mushroom and central body can then be used as the preliminary results toward a 3-D reconstruction process for further biology researches.
Accurate reconstruction of the human brain in MRI-T1 images is valuable and important to clinical needs. In this paper, the morphology and snake techniques are proposed to reconstruct a human brain model. First step in our method is to preprocess the volumetric image to remove skull, muscle, fat, and other non-brain tissue. We use a method of 3-d region growing. It has the advantage over thresholding that the resulting objects will be spatially connected, since brain has the connected property. Second, we use clustering method, and than use them to produce an initial estimate of the cortical surface. Third, we propose a novel active contour algorithm to move the snake toward the cortex. Thus we can use the snake to segment the brain. We use a wavelet method to model the external force that significantly increases the capture range of a traditional snake. Afterwards, we render the volumetric image to display the brain from multiple views. Both simulated data and patient data have been use to test the proposed techniques. The proposed method combines various techniques of 3-D morphology, clustering, active contour, wavelet, and volume rendering to accurately, robustly, and automatically reconstruct brain from MRI-T1 images.
A method was developed for extraction coronary arteries from a contiguous sequence of angiographic images. Since coronary artery in the image usually has poor local contrast and has ribs, spine, and other tissues in the background. We remove the background using the information of temporal continuity. A set of multi-size matched filters process to enhance vessels from poor local contrast. The wavelet transformation based method is then employed to remove noise to enhance the image quality. We also design a stencil mask to remove the stationary tissues further.
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