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- | !!!Evaluation of Appearance Models of the Brain | + | !!!Netscape candidates |
- | !!Abstract | ||
- | Appearance models are an applicable approach to the | + | * jeremytoday (+3) - http://www.netscape.com/member/jeremytoday |
- | analysis of anatomical variability. They are able to | + | |
- | distinguish between groups, e.g. normal and diseased, | + | |
- | as a model encapsulates the properties of a group from | + | |
- | which it was derived. The construction of such models | + | |
- | is closely-related to the task of registration and they | + | |
- | require the correspondence, which registration is able | + | |
- | to obtain. | + | |
- | We developed a framework which evaluates appearance | + | * pagey (+2/-1) - http://www.netscape.com/member/pagey |
- | models, based on the statistics of large sets of | + | |
- | images. The framework is capable of distinguishing | + | |
- | between good models of the brain and worse ones. | + | |
- | Furthermore, it provides a method of validating models. | + | |
- | It does so by measuring how well a model and its data | + | |
- | fit together. | + | |
- | Two measures are defined which reflect on the quality | ||
- | of a model. The first of these -- specificity -- | ||
- | approximates the level to which data generated by the | ||
- | model fits data from which the model was constructed. | ||
- | The complementary measure -- generalisation -- is able | ||
- | to quantify 'distance' between data from which the | ||
- | model was constructed and model-generated data. | ||
- | Results show that as models degrade in quality, their | + | !!!Digg candidates |
- | specificity and generalisation ability rise, as | + | |
- | expected. The algorithms are used to compare models of | + | |
- | the brains, which were built automatically by | + | |
- | independent approaches of registration. This greatly | + | |
- | helps in identifying better model construction | + | |
- | algorithms, which are analogous to registration algorithms. | + | |
- | !!1 Introduction | ||
- | A powerful method for the modelling of anatomy was | + | * aidenag ( +4 ) - http://digg.com/users/aidenag |
- | introduced by Edwards et al. [Edwards] and it is known as | + | |
- | appearance models -- a natural successor to shape | + | |
- | models [Cootes]. This method requires a large enough set of | + | |
- | data, which is representative of a population and | + | |
- | ideally spans its full variability. Appearance models | + | |
- | are able to learn what characterises inter-subject | + | |
- | changes and determine the prominence of the main | + | |
- | characteristics. Hence, it is able to identify changes | + | |
- | and derive a model that encapsulates change -- all in a | + | |
- | data-driven manner. | + | |
- | Non-rigid image registration is ubiquitously used as | + | * curtissthompson ( + 3 ) - http://digg.com/users/curtissthompson |
- | the basis for analysis of medical images. The results | + | |
- | of registration can be used for structural analysis, | + | |
- | atlas matching, and analysis of change. Methods for | + | |
- | obtaining registration are are well-established and | + | |
- | quite uniform. The goal is achieved by warping pairs of | + | |
- | images so that they appear more similar. The similarity | + | |
- | leads to overlap, which allows corresponding structures | + | |
- | to be identified. This problem is complementary to that | + | |
- | of modelling groups of images. A statistical model of a | + | |
- | group of images needs dense correspondence to be | + | |
- | defined across the group; non-rigid registration | + | |
- | provides exactly that. | + | |
- | Since the emergence of appearance models, attempts have | + | * GregD (+2) - http://www.digg.com/users/gregd & http://www.treelimb.org |
- | been made to reproduce and improve it. To name a few | + | |
- | such efforts, Stegmann [Stegmann] built 4-dimensional cardiac | + | |
- | models and Reuckert et al. [Rueckert] derived statistical | + | |
- | deformation models from several registrations of the | + | |
- | brain. Models have been built in a variety of ways, but | + | |
- | what is yet lacked is the ability to compare them. It | + | |
- | becomes clear from experience that attempts to | + | |
- | distinguish between them by eyesight is hopeless. More | + | |
- | recently, appearance models were built automatically | + | |
- | using piece-wise affine registration [IPMI - YET TO | + | |
- | ADD]. Evaluation of models in this particular case | + | |
- | enables evaluation of registration algorithms. | + | |
- | The idea of evaluating models is not unexampled. Davies | + | !!!Newsvine candidates |
- | et al. [Davies] explored the evaluation of shape models and | + | |
- | ultimately developed a robust framework. This paper | + | * |
- | outlines a principled approach to the evaluation of | + | |
- | appearance models, which is a challenging task since | + | !!!Reddit candidates |
- | their complexity is very high. The approach is shown to | + | |
- | be reliable in evaluation of brain models (FOOTER: Examples from non-medical domains are beyond the remit | + | * Jeff (+5) - http://reddit.com/user/Fedquip/ |
- | of this paper, but they have been very successful.) and it is then used to learn about registration | + | |
- | algorithms, from which appearance models have been derived. | + | * Jeroen (+3) - http://reddit.com/user/BioGeek/ |
+ | |||
+ | |||
+ | !!!Blogger candidates | ||
+ | |||
+ | |||
+ | * Steven(insidesocialnews.blogspot.com) (+1/-1) | ||
+ | * Chris (http://www.windingroad.com/) (+2) | ||
+ | |||
+ | !!!Delicious candidates | ||
+ | |||
+ | * |