2.3 VESSEL SEGMENTATION
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]...
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
One day as I was shopping in Patterson’s at the mall here in Bemidji I noticed somethin that I have seen quite a lot of as I have been living in this town of racial diversity. I seemed to notice when I walked in the store with my mom we got the expected "Hello, can I help you find something?". We said "No, we are just looking." and went on our way through the store. A couple of minutes later some Natives came in the store and the guy who was working acted much different. He kind of looked at them with a disgusted look and followed them about the store without really saying anything. If he did it was something like "What size are you looking for?", no hellos or any chance of using the word help. I watched how he kind of looked at them with a sick grin on his face resembling a smirk of disgust. My mom also saw this same thing happen a couple of days earlier but didn’t say anything until we left the store.
However, iris recognition also has disadvantages. Some parts of the iris are generally occluded by the eyelid and eyelash. The pupil and iris boundaries are not always circles and their centres are not c...
Technology is very important tool for advancement of human life. We can utilize technology to help us in everyday life but it can also do the opposite than what it supposed to use for. Laptops and phones has become very important part of our life in past decades. Now we can easily get hold of our love ones and deliver important news within seconds and share our experiences with online social sites with family and friends. All these media tools are used to unite us with our world but we are also being disconnected within ourselves. It seems like our brain are losing its capacity of remembering things what we use to know on top of our head. For instance, before cellphones were invented everyone remembered their friend’s phone number but now hardly
Sticks and stones may break my bones, but names will never hurt me, is a familiar was saying taught to children at a young age to teach them to be strong, to avoid sheltering and build independence. However, that is untrue, over time these names are known as labels that can stick to a person and begin to build, define, and shape a person’s sense of self. These labels are created by a society that can stick to a person and categorizing people and is used to explain deviance. The purpose of this paper is to present the strengths, limitations of labeling theory, and to identify the impact this concept has on the structure of society and a person’s sense of self and image.
...nt, and remain still for approximately 15 seconds while the scan is completed. A retinal scan uses a unique light source, which is projected onto the retina to highlight the blood vessels which then a image is recorded and then analyzed. One major benefit of a retina scan is that it cannot be faked as it is currently impossible to replicate a human retina.
The piece of art I have chosen to write about is called “Parc Monceau” by French Impressionist Claude Monet. This particular piece was one of six various views and angles of the Parc Monceau collection, and was painted in Paris, 1878. The original piece is located in the Metropolitan Muse-um of Art in New York, USA. Monet captured the fleeting effects of time of day, atmosphere and season upon colour and light. His artwork broke colour into individual elements, and completely lacked black and grey tones.
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.
To the programming community the algorithms described in this chapter and their methods are known as feature selection algorithms. This theoretical subject has been examined by researchers for decades and a large number of methods have been proposed. The terms attribute and feature are interchangeable and refer to the predictor values throughout this chapter, and for the remainder of the thesis. In this theoretical way of thinking, dimensionality reduction techniques are typically made up of two basic components, [21], [3], [9].
Scaling is a part of geometric transformation. Scaling transformation is used to change the size of an object either to shrink or enlarge (Yuwaldi, 2000). Object scaling is normally used in computer graphics. For example, the user can enlarge or shrink the drawn object according to certain specifications. In the medical field, scaling techniques are used by experts during the pre-surgery process. For manual template method, the surgeon must face two different expansion image i.e scale of the X-ray and the implant (template) scale (Siti Fairuz, 2009). The surgeon takes longer time to identify the appropriate implant size due to different resolution in the patient’s X-rays (Fang et al, 2006). This research is conducted with the purpose to show techniques and algorithms that can solve the problem of scaling in the medical field that involves the use of medical images and digital implants.
Attention is a deeper process than simply noticing incoming stimuli, it involves a number of processes including filtering perceptions, balancing multiple perceptions and attaching emotional significance to the perceptions (Ratey, 2001). There are two forms of attention, passive and active. Passive attention is the involuntary processes which are directed by the environment and external events e.g. a loud noise. Active attention is the voluntary process which is guided by alertness and concentration e.g. curiosity (Gaddes, 1994). It is a cognitive ability to select and focus on certain factors and the ability to inhibit an action while previewing alternative actions. This is also known as preattentive as the process happens without any conscious awareness (Neisser, 1967). An example of this would be during a conversation, if an individual’s name is mentioned their attention is instantly diverted. Active attention is described as a complex process that includes alertness and arousal, this allows for the planning and monitoring of thoughts and actions. Attention is often described as the first step in the learning process, this is because if something is not attended to then there is no ability to understand or learn it. There is much research into the conceptual framework for this including the process and what happens to students when breakdowns in this process occur (Levine, 1998). Attention is often linked with alertness as the basic mental tone, where each of these factors have a role. Alertness is a state of conscious awareness, which includes a spectrum of alertness through to unconsciousness. An individual’s level of consciousness will vary th...
The main goal of image segmentation is to make simpler or to change the representation of an image into different that is more suitable or useful and easily to modify or can perform operation easily. Segmentation is an important process in many image processing and computer vision application. In computer vision, segmentation is a method of divide the whole digital image into several regions.
Machine learning is the concept of artificial intelligence learning on its own through large amounts of data inputted by people. Modern society is embedded with this intriguing technology. This exciting technology has allowed people, and businesses’, to access information with the tip of their finger. Machine learning is virtually utilized everywhere: homes, businesses, and schools. As a result, machine learning has created a sense of ease toward people’s daily interactions.
This paper proposed an efficient and new approach for vein pattern authentication using connected neighbors of minutiae. The dynamic ROI extraction algorithm retrieves maximum possible features from the hand which is not possible with static ROI algorithm. The use of minutiae neighbor information in the proposed algorithm reduced the false
Automatic segmentation of medical images is a difficult task as medical images are complex in nature and rarely have any simple linear feature. Further, the output of segmentation algorithm is affected due to