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Texture Lung Sparse

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https://www.readbyqxmd.com/read/27740476/a-3-d-riesz-covariance-texture-model-for-prediction-of-nodule-recurrence-in-lung-ct
#1
Pol Cirujeda, Yashin Dicente Cid, Henning Muller, Daniel Rubin, Todd A Aguilera, Billy W Loo, Maximilian Diehn, Xavier Binefa, Adrien Depeursinge
This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter- variations of the feature space dimensions. When compared to the classical use of the average for feature aggregation, feature covariances preserve spatial co-variations between features...
July 18, 2016: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/27429433/a-3-d-riesz-covariance-texture-model-for-prediction-of-nodule-recurrence-in-lung-ct
#2
Pol Cirujeda, Yashin Cid, Henning Muller, Daniel Rubin, Todd Aguilera, Billy Loo, Maximilian Diehn, Xavier Binefa, Adrien Depeursinge
This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter- variations of the feature space dimensions. When compared to the classical use of the average for feature aggregation, feature covariances preserve spatial co-variations between features...
July 18, 2016: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/24886031/automatic-pulmonary-fissure-detection-and-lobe-segmentation-in-ct-chest-images
#3
Shouliang Qi, Han J W van Triest, Yong Yue, Mingjie Xu, Yan Kang
BACKGROUND: Multi-detector Computed Tomography has become an invaluable tool for the diagnosis of chronic respiratory diseases. Based on CT images, the automatic algorithm to detect the fissures and divide the lung into five lobes will help regionally quantify, amongst others, the lung density, texture, airway and, blood vessel structures, ventilation and perfusion. METHODS: Sagittal adaptive fissure scanning based on the sparseness of the vessels and bronchi is employed to localize the potential fissure region...
May 7, 2014: Biomedical Engineering Online
https://www.readbyqxmd.com/read/24595347/total-variation-stokes-strategy-for-sparse-view-x-ray-ct-image-reconstruction
#4
Yan Liu, Zhengrong Liang, Jianhua Ma, Hongbing Lu, Ke Wang, Hao Zhang, William Moore
Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and/or other constraints, a piecewise-smooth X-ray computed tomography image can be reconstructed from sparse-view projection data. However, due to the piecewise constant assumption for the TV model, the reconstructed images are frequently reported to suffer from the blocky or patchy artifacts. To eliminate this drawback, we present a total variation-stokes-projection onto convex sets (TVS-POCS) reconstruction method in this paper...
March 2014: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/23674412/multimodal-sparse-representation-based-classification-for-lung-needle-biopsy-images
#5
Yinghuan Shi, Yang Gao, Yubin Yang, Ying Zhang, Dong Wang
Lung needle biopsy image classification is a critical task for computer-aided lung cancer diagnosis. In this study, a novel method, multimodal sparse representation-based classification (mSRC), is proposed for classifying lung needle biopsy images. In the data acquisition procedure of our method, the cell nuclei are automatically segmented from the images captured by needle biopsy specimens. Then, features of three modalities (shape, color, and texture) are extracted from the segmented cell nuclei. After this procedure, mSRC goes through a training phase and a testing phase...
October 2013: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/23340591/feature-based-image-patch-approximation-for-lung-tissue-classification
#6
Yang Song, Weidong Cai, Yun Zhou, David Dagan Feng
In this paper, we propose a new classification method for five categories of lung tissues in high-resolution computed tomography (HRCT) images, with feature-based image patch approximation. We design two new feature descriptors for higher feature descriptiveness, namely the rotation-invariant Gabor-local binary patterns (RGLBP) texture descriptor and multi-coordinate histogram of oriented gradients (MCHOG) gradient descriptor. Together with intensity features, each image patch is then labeled based on its feature approximation from reference image patches...
April 2013: IEEE Transactions on Medical Imaging
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