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1.
Artigo em Inglês | MEDLINE | ID: mdl-19163614

RESUMO

In this paper, we describe the design and implementation of a Graphical User Interface (GUI) for Cassandra, a computer application for Virtual Ligand Screening (VLS). The GUI was designed using Trolltech QT4 and Perl, and serves the purpose of making the execution of Cassandra more user-friendly. Through this GUI, users can manage multiple concurrent, interactive data paths both on a single machine and on a High Performance Computing Cluster (HPCC). The GUI successfully decreased the complexity and steep learning curve of using Cassandra, and the average time to execute a VLS project. As result, we reduced the time necessary to train new users, increased the number of users, increased the overall efficiency of Cassandra, and optimized data handling and analysis.


Assuntos
Biologia Computacional/métodos , Ligantes , Reconhecimento Automatizado de Padrão/métodos , Algoritmos , Análise por Conglomerados , Gráficos por Computador , Computadores , Linguagens de Programação , Reprodutibilidade dos Testes , Software , Interface Usuário-Computador
2.
Conf Proc IEEE Eng Med Biol Soc ; 2005: 3129-32, 2005.
Artigo em Inglês | MEDLINE | ID: mdl-17282907

RESUMO

In this paper, a wavelet domain method for speckle noise filtering is presented. It uses non-decimated wavelet transform and Generalized Cross Validation thresholding technique. The spatial correlation of ultrasound speckle noise is broken by multiresolution analysis. Level dependent thresholding removes noise in the wavelet domain based on automatic estimation of noise energy in each subband. The efficacy of this filter is demonstrated on both simulated and real medical ultrasound images. The result is shown to be promising and outperforms other de-noising approaches. A single adjustable parameter can be used by medical experts to balance the relevant image feature preservation and the speckle noise suppression. Lifting scheme as a way of constructing new biorthogonal wavelets based on existing wavelet as well as a way of performing wavelet transform is studied in this research to improve the performance of wavelet de-noising.

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