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Enhancing obstetric and gynecology ultrasound images by adaptation of the speckle reducing anisotropic diffusion filter

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ARTIFICIAL INTELLIGENCE IN MEDICINE 2008年第3期43卷 223-242页

作者： Munteanu, Cristian Morales, Francisco Cabrera Fernandez, Javier Gonzalez Rosa, Agostinho Deniz, Luis Gomez Univ Tecn Lisboa Inst Super Tecn Inst Sistemas & Robot P-1049001 Lisbon Portugal Hosp Univ Mat Infantil Las Palmas Gran Canaria Spain Univ Las Palmas Gran Canaria Ctr Tecnol Med Las Palmas Gran Canaria Spain

Objective: So far there is no ideal speckle reduction filtering technique that is capable of enhancing and reducing the level of noise in medical ultrasound (US) images, white efficiently responding to medical experts' validation criteria which quite often include a subjective component. This paper presents an interactive tool. called evolutionary speckle reducing anisotropic diffusion filter (EVOSRAD) that performs adaptive speckle filtering on ultrasound B-mode still images. The medical expert runs the algorithm interactively, having a permanent control over the output, and guiding the filtering process towards obtaining enhanced images that agree to his/her subjective quality criteria. Methods and material: We employ an interactive evolutionary algorithm (IGA) to adapt on-tine the parameters of a speckle reducing anisotropic diffusion (SRAD) filter. For a given input US image, the algorithm evolves the parameters of the SRAD filter according to subjective criteria of the medical expert who runs the interactive algorithm. The method and its validation are applied to a test bed comprising both real and simulated obstetrics and gynecology (OB/GYN) ultrasound images. Results: The potential of the method is analyzed in comparison to other speckle reduction fitters: the original SRAD filter, the anisotropic diffusion, offset and median fitters. Results obtained show the good potential of the method on several classes of OB/GYN ultrasound images, as well as on a synthetic image simulating a real fetal US image. Quality criteria for the evaluation and validation of the method include subjective scoring given by the medical expert who runs the interactive method, as well as objective global and local quality criteria. Conclusions: The method presented allows the medical expert to design its own filters according to the degree of medical expertise as well as to particular and often subjective assessment criteria. A filter is designed for a given class of ultrasound images

关键词： ultrasound speckle anisotropic diffusion interactive genetic algorithm

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A comparison of three fitness prediction strategies for interactive genetic algorithms

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2007年第2期23卷 605-616页

作者： Wang, Leuo-Hong Aletheia Univ Dept Informat Management Evoutionary Computat Lab Tamsui 251 Taiwan

The human fatigue problem is one of the most significant problems encountered by interactive genetic algorithms (IGA). Different strategies have been proposed to address this problem, such as easing evaluation methods, accelerating IGA convergence via speedup algorithms, and fitness prediction. This paper studies the performance of fitness prediction strategies. Three prediction schemes, the neural network (NN), the Bayesian learning algorithm (BLA), and a novel prediction method based on algorithmic probability (ALP), are examined. Numerical simulations are performed in order to compare the performances of these three schemes.

关键词： interactive genetic algorithm human fatigue problem fitness prediction algorithmic probability product design

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Large Population Size IGAs with Individuals' Fitness Not Assigned by User

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4th International Conference on Intelligent Computing

作者： Yuan, Jie Gong, Dunwei China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221008 Peoples R China

ISBN: (纸本)9783540859833

User fatigue problem in traditional interactive genetic algorithms restricts its population size. It is necessary to maintain a large population size to optimize complicated problems. We present a large population size interactive genetic algorithm with individuals' fitness not assigned by user in this paper. The algorithm divides the population into several clusters, and the maximum number of clusters is changeable with the evolution and distribution of the population. The user only evaluates a center individual in each cluster and others' fitness is estimated based on these ones. In addition, to assign a center individual's fitness, we record the time when the user evaluates it satisfactory or unsatisfactory according to his/her sensitiveness, and its fitness is automatically calculated based on the time. Finally, we apply the proposed algorithm to the one-max problem, and compare it with traditional interactive genetic algorithms. The experimental results validate its efficiency.

关键词： Optimization genetic algorithm interactive genetic algorithm cluster user fatigue

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Human mosaic creation through agents and interactive genetic algorithms applied to videogames movements

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EvoWorkshops 2007

作者： Sanjuan, Oscar Garcia, Gloria Saez, Yago Luque, Cristobal Univ Salamanca Paseo Juan XXIII No 3 Madrid 28044 Spain UnivCarlos III de Madrid Madrid Spain

ISBN: (纸本)9783540718048

In this essay the construction of an interactive genetic algorithm and agents based application will be described. This construction is driven to plan the development of a human mosaic, starting from an initial design and an adjustment of several parameters. In addition, the same idea of generation will be show as suitable to be applied to character group movements inside a videogame. The software developed is enclosed, as far as the "creative" part of the solution is concerned, inside the evolutionary computation paradigm;while into agent orientation regarding characters coordination.

关键词： genetic algorithm software agents interactive genetic algorithm videogames human mosaics group movements

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Emotional image and musical information retrieval with interactive genetic algorithm

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PROCEEDINGS OF THE IEEE 2004年第4期92卷 702-711页

作者： Cho, SB Yonsei Univ Dept Comp Sci Seoul 120749 South Korea

Several techniques in artificial intelligence have shown a great potential to develop useful human-computer interfaces, but it is still quite far from realizing a system of matching the human performance, especially in terms of emotion, intuition and inspiration. To overcome this shortcoming, we present a promising technique called interactive genetic algorithm (IGA), which performs optimization with human evaluation, and with which the user can obtain what he has in mind through repeated interaction. To project the usefulness of the IGA to develop emotional human-computer interfaces, we have applied it to the problems of image and music information retrieval. Several experiments show that our approach allows us to design and search digital media not only explicitly expressed, but also abstract images such as "cheerful impression," and "gloomy impression. " It is expected that the same approach can be applied to many other problems in musical information retrieval and manipulation based on intuition and inspiration.

关键词： emotion interactive genetic algorithm musical information retrieval subjective test

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Emotional image and musical information retrieval with interactive genetic algorithm

Emotional image and musical information retrieval with inter...

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International Workshop on Human Supervision and Control in Engineering and Music

作者： Cho, SB Yonsei Univ Dept Comp Sci Seoul 120749 South Korea

关键词： emotion interactive genetic algorithm musical information retrieval subjective test

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interactive Evolution of XUL User Interfaces 07

Interactive Evolution of XUL User Interfaces

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Annual Conference of genetic and Evolutionary Computation Conference

作者： Quiroz, Juan C. Louis, Sushil J. Dascalu, Sergiu M. Univ Nevada Evolutionary Comp Syst Lab Reno NV 89557 USA

ISBN: (纸本)9781595936974

We attack the problem of user fatigue by using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algorithm combines a set of computable user interface design metrics with subjective user input, to guide the evolution of interfaces. Our goal is to provide user interface designers with a tool that can be used to explore innovation and creativity in the design space of user interfaces and make it easier for end-users to further customize their user interface without programming knowledge. User interface specifications are encoded as individuals in an interactive genetic algorithm's population and their fitness is computed front a weighted combination of user interface design guidelines and user input. This paper shows that we can reduce human fatigue in interactive genetic algorithms (the number of choices needing to be made by the designer), by 1) only asking the user to pick two user interfaces from among ten shown on the display and 2) by asking the user to make the choice once every t. generations.

关键词： interactive genetic algorithm User fatigue User Interface design

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Face image retrieval method based on improved IGA and SVM

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3rd International Conference on Intelligent Computing

作者： Shi, Shuo Li, Jiu-Zhong Lin, Li Guangdong Ind Tech Coll Guangzhou 510300 Peoples R China RTV Univ Nan chuan Coll Chongqing 408400 Peoples R China

ISBN: (纸本)9783540741701

Face image retrieval has particularity under the situation that the target is unknown. If the image that match some features or fit to the one in memory wants to be find out in the human image database, the request solution must be global optimum, and does not lose the optimal one. In this paper the interactive genetic algorithm (IGA) incorporating with adjust function and support vector machine (SVM) is put forward to keep optimum solution from lose, speed the convergence, alleviate user fatigue, improve and raise retrieval performance.

关键词： adjust function interactive genetic algorithm support vector machine image retrieval

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Multiple fuzzy state-value functions for human evaluation through interactive trajectory planning of a partner robot

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SOFT COMPUTING 2006年第10期10卷 891-901页

作者： Kubota, Naoyuki Nojima, Yusuke Kojima, Fumio Fukuda, Toshio Tokyo Metropolitan Univ Dept Syst Design Japan Sci & Technol Agcy PREST Tokyo 1920397 Japan Osaka Prefecture Univ Dept Comp Sci & Intelligent Syst Osaka 5998531 Japan Kobe Univ Grad Sch Dept Mech & Syst Engn Nada Ku Kobe Hyogo 6578501 Japan Nagoya Univ Grad Sch Dept Micro Syst Engn Chigusa Ku Nagoya Aichi 4648603 Japan

The purpose of this study is to develop partner robots that can obtain and accumulate human-friendly behaviors. To achieve this purpose, the entire architecture of the robot is designed, based on a concept of structured learning which emphasizes the importance of interactive learning of several modules through interaction with its environment. This paper deals with a trajectory planning method for generating hand-to-hand behaviors of a partner robot by using multiple fuzzy state-value functions, a self-organizing map, and an interactive genetic algorithm. A trajectory for the behavior is generated by an interactive genetic algorithm using human evaluation. In order to reduce human load, human evaluation is estimated by using the fuzzy state-value function. Furthermore, to cope with various situations, a self-organizing map is used for clustering a given task dependent on a human hand position. And then, a fuzzy state-value function is assigned to each output unit of the self-organizing map. The robot can easily obtain and accumulate human-friendly trajectories using a fuzzy state-value function and a knowledge database corresponding to the unit selected in the self-organizing map. Finally, multiple fuzzy state-value functions can estimate a human evaluation model for the hand-to-hand behaviors. Several experimental results show the effectiveness of the proposed method.

关键词： fuzzy modeling partner robot trajectory generation interactive genetic algorithm self-organizing map

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Semi interactive method for data mining

Semi interactive method for data mining

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8th International Conference on Enterprise Information Systems (ICEIS 2006)

作者： Boudjeloud-Assala, Lydia Poulet, Francois ESIEA Pole ECD F-53000 Laval France

ISBN: (纸本)9728865422

Usual visualization techniques for multidimensional data sets, such as parallel coordinates and scatter-plot matrices, do not scale well to high numbers of dimensions. A common approach to solve this problem is dimensionality selection. We present new semi-interactive method for dimensionality selection to select pertinent dimension subsets without losing information. Our cooperative approach uses automatic algorithms, interactive algorithms and visualization methods: an evolutionary algorithm is used to obtain optimal dimension subsets which represent the original data set without losing information for unsupervised tasks (clustering or outlier detection) using a new validity criterion. A visualization method is used to present the user interactive evolutionary algorithm results and let him actively participate in evolutionary algorithm search with more efficiency resulting in a faster evolutionary algorithm convergence. We have implemented our approach and applied it to real data set to confirm it is effective for supporting the user in the exploration of high dimensional data sets and evaluate the visual data representation.

关键词： data mining interactive genetic algorithm high dimensional data data visualization

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