The Chan-Vese segmentation algorithm is robust and has been used to segment different kind of images. This algorithm re- lies on global properties of an image (gray level intensities in regions, length of contours, area of regions), hence it is more suitable in cases when the edge information is not very predominant. The results are good qualitatively for noisy im- ages and images with complicated topologies. Reviewing the state of the art techniques for segmentation we see that this method is used extensively in segmentation of regions in med- ical images. Images with low-contrast do not have well de- fined homogeneous regions, performance may be degraded in these scenarios since the method assumes homogeneous in- tensities in the foreground and background. Level-sets being non-parametric, include a regularization term such as penalty on curve/length/surface area or curvature. These regulariza- tion terms do not contain any information about the shape of the region of interest. The Chan-Vese algorithm may be slow for some applications. Depending on the type and size of the image and the number of iterations needed, the segmentation can be slow, hence, GPU implementations of the algorithm, reduction of the segmentation problem to an ordinary differ- ential equation rather than a nonlinear PDE [13] can be used to speed up the algorithm. in 3D. Presently the model contour segment parts are selected and grouped into bundles manually. It is important to auto- mate the step to learn part bundles. Timing performance of the algorithm is not discussed in the paper.
4. FUTURE WORK
4.1. Active Contours Without Edges
4.1.1. Parameter Selection and Initialization of the Level Set
Function
This method is semi-automated. It requires user interaction for tuning the parameters and initializing the level set. To ob- tain qualitatively good segmentations the parameters need to be tuned for every image. Machine learning algorithms can be used to learn parameter values for homogeneous images from a training set of images. Unfortunately, real images are not homogeneous, there may be variations in the image due to varying lighting conditions. Methods devised to tune these parameters automatically would benefit the segmentation pro- cess. Careful initialization of the level set is necessary, since it has a direct correlation with the time taken for convergence.
Atlas-based initializations can also be used to segment struc- tures from medical images.
4.1.2. Improve efficiency
Accuracy and precision can be improved by incorporating prior information about the target to be segmented. For in- creasing computational efficiency multiscale processing and parallelizations are viable solutions.
3.2. Shape Guided Contour Grouping with Particle Fil- ters The contour grouping algorithm was applied to the ETHZ shape classes. The ETHZ shape classes have significant intra- class variations, scale changes, and illumination changes. Re- sults were shown in the presence of a lot of clutter in the
In A Thousand Plateaus, Deleuze and Guattari, to some extent following Gabriel Tarde, famously claim that 'every politics is simultaneously a macropolitics and a micropolitics' (Deleuze & Guattari 1987, 213). This point is, of course, inscribed in their complex philosophical oeuvre, but, in my opinion, several remarks on it would suffice to prove its relevance for the present research. For Deleuze and Guattari, the social nowadays is characterized by two types of segmentation, namely, supple and rigid. The most perfect example of rigid segmentation is the modern hierarchically organized state, while supple segmentation can be related to all kinds of "microscopic relations" which already existed in the primitive societies. These two type of segmentation cannot be separated from each other and are necessarily entangled. As they go on to argue, 'every society, and every individual, are thus plied by both segmentarities simultaneously: one molar, the other molecular' (Deleuze & Guattari 1987, 213). So, for instance, the proletariat is, so to speak, a molar unit which belongs to the macropolitical dimension. But it is crucial that any class emerges from within the molecular masses. As Deleuze and Guattari argue, 'the
During World War II, after the Japanese bombing of Pearl Harbor, Japanese Americans in the western United States were forced into internment camps because the government felt as though the Japanese were dangerous if they were not relocated. These camps were usually in poor condition and in deserted areas of the nation. The Japanese were forced to make the best of their situation and thus the adults farmed the land and tried to maximize leisure while children attempted to enjoy childhood. The picture of the internee majorettes, taken by internee and photographer Toyo Miyatake, shows sixteen girls standing on bleachers while posing in front of the majestic Sierra Nevada mountain range and desolate Manzanar background. Their faces show mixed expressions of happiness, sadness and indifference, and their attire is elegant and American in style. With the image of these smiling girls in front of the desolate background, Miyatake captures an optimistic mood in times of despair. Though this photograph is a representation of the Manzanar internment camp and, as with most representations, leaves much unsaid, the majorette outfits and smiling faces give a great deal of insight on the cooperative attitudes of Japanese Americans and their youth's desire to be Americanized in this time.
Sequential single-source, multi-scan imaging is our simplest and oldest form of spectral imaging. An example of this method is to, “…simply acquire two scans-one at a low kVp and one at a high kVp setting.”(Steidley 2008). A benefit to this method is it requires nothing other than a standard CT scanner, giving no added cost to the facility. As always there are disadvantages with everything, we find quite a significant one with this method. Lentz states, “…it presents significa...
those parts unable to work at a normal function are what creates the flashbacks that the
Retinal vessel segmentation is important for the diagnosis of numerous eye diseases and plays an important role in automatic retinal disease screening systems. Automatic segmentation of retinal vessels and characterization of morphological attributes such as width, length, tortuosity, branching pattern and angle are utilized for the diagnosis of different cardiovascular and ophthalmologic diseases. Manual segmentation of retinal blood vessels is a long and tedious task which also requires training and skill. It is commonly accepted by the medical community that automatic quantification of retinal vessels is the first step in the development of a computer-assisted diagnostic system for ophthalmic disorders. A large number of algorithms for retinal vasculature segmentation have been proposed. The algorithms can be classified as pattern recognition techniques, matched filtering, vessel tracking, mathematical morphology, multiscale approaches, and model based approaches. The first paper on retinal blood vessel segmentation appeared in 1989 by Chaudhuri et al. [21]...
The second stage of memory processing is storage. Aronson et al. (2013) defines storage as the process by which people store the information they just acquired. Unfortunately, memories are affected by incoming information through alteration or reconstruction. This phenomenon is referred to as recon...
Rita Dove’s Museum utilizes juxtapositions as a means to create a revision of history, to remove the ekphrasis fear mentioned in W. Mitchell’s essay “Ekphrasis and the Other” in Picture Theory. Dove, establishes a new history by blurring the lines of otherness, focusing more so on humanism, rather than female, and African American being something that is over come with otherness. In fact, as the article “Ekphrasis in the book: Rita Dove’s African American museum” mentions, “Dove’s long interest in ekphrasis both explicitly and implicitly in her use of it to dismantle otherness, to reach across the gaps between poet, image and audience.” Throughout Dove’s work she undoes the otherness reestablishing a connection between the histories then and presently, along with the self and other now, which can be seen in “Fiammetta Breaks Her Peace” and “Anti-Father.”
Dubey, R.B., et al. “The Current CAD and PACS Technologies in Medical Imaging.” International Journal of Applied Engineering Research 4.8 (2009): 1439-1456. Academic Search Complete. Web. 20 Feb. 2011.
'He was afraid and said, "How awesome is this place! This is none other than the house of God, and this is the gate of heaven.'
The technologies used by the researchers range from functional magnetic resonance imaging (fMRI) that measures the changes in the different parts of the brain, to Steady state topography (SST) an...
Controversies, petitions and experiments. Along with many questions and arguments imposed on the topics of photo manipulation, many controversies, petitions and debates have been raised. Many “Photoshop Fails” and overuse of photo-editing in photography competitions have created many controversies and the ethics of photo manipulation are widely questioned and discussed.
Children with autism spectrum disorder (ASD) often require systematic and intensive interventions in order to develop appropriate social and academic behaviors. One intervention that has been used with some success on improving a variety of behaviors is video modeling (Acar & Diken, 2012; Wang, Cui, & Parrila, 2011; Wilson, 2013). Video modeling involves the process of creating a video of a person or persons exhibiting a desired behavior and subsequently showing the video in a planned, systematic manner to the individual in need of intervention with the intent to measure imitation of the desired behavior by the viewer (McCoy & Hermansen, 2007). This intervention has
Images of human anatomy have been around for more than 500 years now. From the sketches created by Leonardo da Vinci, to the modern day Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan, images have played a great role in medicine. Evolution in medical imaging brought together people from various disciplines such as Biology, Physics, Chemistry and Mathematics, a collaboration which has further contributed to healthcare as a whole. Modern day imaging improves medical workflows by facilitating a non-invasive insight into human body, accurate and timely diagnostics, and persistence of an analysis.
Segmentation, targeting and positioning of automotive industry consists of three stages; in automotive industry determine which kinds of customers exists in the market, apply segmentation by optimizing company goods or services for the particular segment and select the customers which is suitable to serve. Segmentation involves finding out different kinds of customers with various needs. In automotive industry, some customers demand speed and performance, while on the other hand they also want safety (Borden, 2006). So in this situation the company can’t be able to think about all the customers and only one condition is fulfilled by the company. There are many other kinds of variables in segmentation; demographic refers to personal figures such as income, gender, education, location, etc. Another basis for segmentation is behavior. Some customers are brand loyal and they remain in touch with their preferred brands even after they have many other options available in the market. After segmenting, companies decide to target one or more segments. After that the industry has to check how big is the segment, and how customer can expect it to grow (Chikweche and Fletcher, 2012). For example, BMW has a great reputation for fast, consistent quality; the customers didn’t know that BMW offers many others after sales services. Positioning takes place after segmentation and targeting, positioning involves implementing our targeting. Many automotive companies had chosen to position itself as a maker of eco-friendly vehicles. Therefore, for promotion of eco-friendly vehicles, automotive industries spend a lot in advertisement.
Image shape matching is prime concern in object recognition and identification methods. An image matching is a means of determining the resemblance of one image with the other image. Images are matched based on their shape and texture and it finds variety of applications ranging from image retrieval, object recognition, remote sensing, image classification, image analysis and so on. In general, image matching techniques are classified into structure- based [1] [2] and feature-based [3][4] methods. Structure-based methods compare the shape/ structure and the size of the images, whereas the feature- based methods examine the image features like color and texture in addition to size and shape. Therefore, the image shape and size are the most