We proposed an automated segmentation of suspicious clustered microcalcifications on digital mammograms. the algorithm consists three main processing steps for this purpose. In the first step, the improvement of the m...
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ISBN:
(纸本)0780384075
We proposed an automated segmentation of suspicious clustered microcalcifications on digital mammograms. the algorithm consists three main processing steps for this purpose. In the first step, the improvement of the microcalcifcations appearance by using the "a trous wavelet" transform which could enhance the high - frequency content of breast images were performed. In the second step, individual microcalcifications were segmented using wavelet histogram analysis on overlapping subplanes. then, the extracted histogram features for each subplane used as an input to a fuzzy rule-based classifier to identify subimages containing microcalcifications. In the third step, subtractive clustering was applied to assign individual mierocalcifications to the closest cluster. Finally, features of each cluster were used as input to another fuzzy rule-based classifier to identify suspicious clusters. the results of the applied algorithm for 47 images containing 16 benign and 31 malignant biopsy cases showed a sensitivity of 87% and the average of 0.5 false positive clusters per image.
We proposed an automated segmentation of suspicious clustered microcalcifications on digital mammograms. the algorithm consists three main processing steps for this purpose. In the first step, the improvement of the i...
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We proposed an automated segmentation of suspicious clustered microcalcifications on digital mammograms. the algorithm consists three main processing steps for this purpose. In the first step, the improvement of the in microcalcifications appearance by using the "a trous wavelet" transform which could enhance the high-frequency content of breast images were performed. In the second step, individual microcalcifications were segmented using wavelet histogram analysis on overlapping subplanes. then, the extracted histogram features for each subplane used as an input to a fuzzy rule-based classifier to identify subimages containing microcalcifications. In the third step, subtractive clustering was applied to assign individual microcalcifications to the closest cluster. Finally, features of each cluster were used as input to another fuzzy rule-based classifier to identify suspicious clusters. the results of the applied algorithm for 47 images containing 16 benign and 31 malignant biopsy cases showed a sensitivity of 87% and the average of U. 5 false positive clusters per image.
Almost all existing methodologies and automated tools for knowledge acquisition are somehow based on classical mathematical logic or its various classical conservative extensions. this paper proposes a new approach to...
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ISBN:
(纸本)3540408037
Almost all existing methodologies and automated tools for knowledge acquisition are somehow based on classical mathematical logic or its various classical conservative extensions. this paper proposes a new approach to knowledge acquisition problem: automated knowledge acquisition by relevant reasoning based on strong relevant logic. the paper points out why any of the classical mathematical logic, its various classical conservative extensions, and traditional relevant logics is not a suitable logical basis for knowledge acquisition, shows that strong relevant logic is a more hopeful candidate for the purpose, and establishes a conceptional foundation for automated knowledge acquisition by relevant reasoning based on strong relevant logic.
this paper presents an Arabic Morphological Analyzer and its implementation in clp(FD), a constraint logicprogramming language. the Morphological Analyzer (MA) represents a component of an architecture which can proc...
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ISBN:
(纸本)3540408037
this paper presents an Arabic Morphological Analyzer and its implementation in clp(FD), a constraint logicprogramming language. the Morphological Analyzer (MA) represents a component of an architecture which can process unrestricted text from a source such as Internet. the morphological analyzer uses a constraint-based model to represent the morphological rules for verbs and nouns, a matching algorithm to isolate the affixes and the root of a given word-form, and a linguistic knowledge base consisting in lists of markers. the morphological rules fall into two categories: the regular morphological rules of the Arabic grammar and the exception rules that represent the language exceptions. clp(FD) is particularly suitable for the implementation of our system thanks to its double reasoning: symbolic reasoning expresses the logic properties of the problem and facilitates the implementation of a the linguistic knowledge base, and heuristics, while constraint satisfaction reasoning on finite domains uses constraint propagation to keep the search space manageable.
A sound and complete sequent calculus for skeptical consequence in predicate default logic is presented. While skeptical consequence is decidable in the finite propositional case, the move to predicate or infinite the...
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ISBN:
(纸本)3540404945
A sound and complete sequent calculus for skeptical consequence in predicate default logic is presented. While skeptical consequence is decidable in the finite propositional case, the move to predicate or infinite theories increases the complexity of skeptical reasoning to being Π11-complete. this implies the need for sequent rules with countably many premises, and such rules are employed.
In this paper, we show how automated support can be provided for identifying refactoring opportunities, e.g., when an application's design should be refactored and which refactoring(s) in particular should be appl...
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ISBN:
(纸本)0769519024
In this paper, we show how automated support can be provided for identifying refactoring opportunities, e.g., when an application's design should be refactored and which refactoring(s) in particular should be applied. Such support is achieved by using the technique of logic meta programming to detect so-called bad smells and by defining a framework that uses this information to propose adequate refactorings. We report on some initial but promising experiments that were applied using the proposed techniques.
the dependency pair approach is one of the most powerful techniques for termination and innermost termination proofs of term rewrite systems (TRSs). For any TRS, it generates inequality constraints that have to be sat...
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ISBN:
(数字)9783540398134
ISBN:
(纸本)3540201017
the dependency pair approach is one of the most powerful techniques for termination and innermost termination proofs of term rewrite systems (TRSs). For any TRS, it generates inequality constraints that have to be satisfied by weakly monotonic well-founded orders. We improve the dependency pair approach by considerably reducing the number of constraints produced for (innermost) termination proofs. Moreover, we extend transformation techniques to manipulate dependency pairs which simplify (innermost) termination proofs significantly. In order to fully automate the dependency pair approach, we show how transformation techniques and the search for suitable orders can be mechanized efficiently. We implemented our results in the automated termination prover AProVE and evaluated them on large collections of examples.
the paper describes a method for inducing first-order rules with fuzzy predicates from a database. First, the paper makes a distinction between fuzzy rules allowing for some tolerance with respect to the interpretativ...
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ISBN:
(纸本)3540404945
the paper describes a method for inducing first-order rules with fuzzy predicates from a database. First, the paper makes a distinction between fuzzy rules allowing for some tolerance with respect to the interpretative scope of the predicates, and fuzzy rules aiming at expressing a set of ordinary rules in a global way. Moreover the paper only considers the induction of Horn-like implicative-based fuzzy rules. Specific confidence degrees are associated with each kind of fuzzy rules in the inductive process. this technique is illustrated on an experimental application. the interest of learning various types of fuzzy first-order logic expressions is emphasized.
Congruence closure algorithms for deduction in ground equational theories are ubiquitous in many (semi-)decision procedures used for verification and automated deduction. they axe also frequently used in practical con...
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ISBN:
(数字)9783540398134
ISBN:
(纸本)3540201017
Congruence closure algorithms for deduction in ground equational theories are ubiquitous in many (semi-)decision procedures used for verification and automated deduction. they axe also frequently used in practical contexts where some interpreted function symbols are present. In particular, for the verification of pipelined microprocessors, in many cases it suffices to be able to deal with integer offsets, that is, instead of only having ground terms t built over free symbols, all (sub)terms can be of the form t + k for arbitrary integer values k. In this paper we first give a different very simple and clean formulation for the standard congruence closure algorithm which we believe is of interest on itself. It builds on ideas from the abstract algorithms of [Kap97,BT00], but it is easily shown to run in the best known time, O(n log n), like the classical algorithms [DST80,NO80,Sho84]. After that, we show how this algorithm can be smoothly extended to deal with integer offsets without increasing this asymptotic complexity.
this paper investigates the relationship between automata-and tableau-based inference procedures for Description logics. To be more precise, we develop an abstract notion of what a tableau-based algorithm is, and then...
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ISBN:
(数字)9783540398134
ISBN:
(纸本)3540201017
this paper investigates the relationship between automata-and tableau-based inference procedures for Description logics. To be more precise, we develop an abstract notion of what a tableau-based algorithm is, and then show, on this abstract level, how tableau-based algorithms can be converted into automata-based algorithms. In particular, this allows us to characterize a large class of tableau-based algorithms that imply an ExpTime upper-bound for reasoning in the description logics for which such an algorithm exists.
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