7,221 research outputs found

    Hopfield Networks in Relevance and Redundancy Feature Selection Applied to Classification of Biomedical High-Resolution Micro-CT Images

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    We study filter–based feature selection methods for classification of biomedical images. For feature selection, we use two filters — a relevance filter which measures usefulness of individual features for target prediction, and a redundancy filter, which measures similarity between features. As selection method that combines relevance and redundancy we try out a Hopfield network. We experimentally compare selection methods, running unitary redundancy and relevance filters, against a greedy algorithm with redundancy thresholds [9], the min-redundancy max-relevance integration [8,23,36], and our Hopfield network selection. We conclude that on the whole, Hopfield selection was one of the most successful methods, outperforming min-redundancy max-relevance when\ud more features are selected

    Single-image Tomography: 3D Volumes from 2D Cranial X-Rays

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    As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we suggest firstly to learn a coarse, fixed-resolution volume which is then fused in a second step with the input x-ray into a high-resolution volume. To train and validate our approach we introduce a new dataset that comprises of close to half a million computer-simulated 2D x-ray images of 3D volumes scanned from 175 mammalian species. Applications of our approach include stereoscopic rendering of legacy x-ray images, re-rendering of x-rays including changes of illumination, view pose or geometry. Our evaluation includes comparison to previous tomography work, previous learning methods using our data, a user study and application to a set of real x-rays

    Regional diversity in the murine cortical vascular network is revealed by synchrotron X-ray tomography and is amplified with age

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    Cortical bone is permeated by a system of pores, occupied by the blood supply and osteocytes. With ageing, bone mass reduction and disruption of the microstructure are associated with reduced vascular supply. Insight into the regulation of the blood supply to the bone could enhance the understanding of bone strength determinants and fracture healing. Using synchrotron radiation-based computed tomography, the distribution of vascular canals and osteocyte lacunae was assessed in murine cortical bone and the influence of age on these parameters was investigated. The tibiofibular junction from 15-week- and 10-month-old female C57BL/6J mice were imaged post-mortem. Vascular canals and three-dimensional spatial relationships between osteocyte lacunae and bone surfaces were computed for both age groups. At 15 weeks, the posterior region of the tibiofibular junction had a higher vascular canal volume density than the anterior, lateral and medial regions. Intracortical vascular networks in anterior and posterior regions were also different, with connectedness in the posterior higher than the anterior at 15 weeks. By 10 months, cortices were thinner, with cortical area fraction and vascular density reduced, but only in the posterior cortex. This provided the first evidence of age-related effects on murine bone porosity due to the location of the intracortical vasculature. Targeting the vasculature to modulate bone porosity could provide an effective way to treat degenerative bone diseases, such as osteoporosis

    From Invisibility to Readability: Recovering the Ink of Herculaneum

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    The noninvasive digital restoration of ancient texts written in carbon black ink and hidden inside artifacts has proven elusive, even with advanced imaging techniques like x-ray-based micro-computed tomography (micro-CT). This paper identifies a crucial mistaken assumption: that micro-CT data fails to capture any information representing the presence of carbon ink. Instead, we show new experiments indicating a subtle but detectable signature from carbon ink in micro-CT. We demonstrate a new computational approach that captures, enhances, and makes visible the characteristic signature created by carbon ink in micro-CT. This previously unseen evidence of carbon inks, which can now successfully be made visible, is a discovery that can lead directly to the noninvasive digital recovery of the lost texts of Herculaneum

    Visualization methods for analysis of 3D multi-scale medical data

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    Imaging fetal anatomy.

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    Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development
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