15 research outputs found

    Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier

    Get PDF
    This paper proposes a novel lung nodule classification method for low-dose CT images. The method includes two stages. First, Local Difference Pattern (LDP) is proposed to encode the feature representation, which is extracted by comparing intensity difference along circular regions centered at the lung nodule. Then, the single-center classifier is trained based on LDP. Due to the diversity of feature distribution for different class, the training images are further clustered into multiple cores and the multicenter classifier is constructed. The two classifiers are combined to make the final decision. Experimental results on public dataset show the superior performance of LDP and the combined classifier

    Shifting representations:Adventures in cross-modality domain adaptation for medical image analysis

    Get PDF

    Shifting representations:Adventures in cross-modality domain adaptation for medical image analysis

    Get PDF

    Spectral Feature Selection for Data Mining

    Get PDF
    This timely introduction to spectral feature selection illustrates the potential of this powerful dimensionality reduction technique in high-dimensional data processing. It presents the theoretical foundations of spectral feature selection, its connections to other algorithms, and its use in handling both large-scale data sets and small sample problems. Readers learn how to use spectral feature selection to solve challenging problems in real-life applications and discover how general feature selection and extraction are connected to spectral feature selection. Source code for the algorithms is available online

    Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

    Get PDF
    Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute
    corecore