335 research outputs found
Approches tomographiques structurelles pour l'analyse du milieu urbain par tomographie SAR THR : TomoSAR
SAR tomography consists in exploiting multiple images from the same area acquired from a slightly different angle to retrieve the 3-D distribution of the complex reflectivity on the ground. As the transmitted waves are coherent, the desired spatial information (along with the vertical axis) is coded in the phase of the pixels. Many methods have been proposed to retrieve this information in the past years. However, the natural redundancies of the scene are generally not exploited to improve the tomographic estimation step. This Ph.D. presents new approaches to regularize the estimated reflectivity density obtained through SAR tomography by exploiting the urban geometrical structures.La tomographie SAR exploite plusieurs acquisitions d'une mĂȘme zone acquises d'un point de vue lĂ©gerement diffĂ©rent pour reconstruire la densitĂ© complexe de rĂ©flectivitĂ© au sol. Cette technique d'imagerie s'appuyant sur l'Ă©mission et la rĂ©ception d'ondes Ă©lectromagnĂ©tiques cohĂ©rentes, les donnĂ©es analysĂ©es sont complexes et l'information spatiale manquante (selon la verticale) est codĂ©e dans la phase. De nombreuse mĂ©thodes ont pu ĂȘtre proposĂ©es pour retrouver cette information. L'utilisation des redondances naturelles Ă certains milieux n'est toutefois gĂ©nĂ©ralement pas exploitĂ©e pour amĂ©liorer l'estimation tomographique. Cette thĂšse propose d'utiliser l'information structurelle propre aux structures urbaines pour rĂ©gulariser les densitĂ©s de rĂ©flecteurs obtenues par cette technique
Finding Nano-\"Otzi: Semi-Supervised Volume Visualization for Cryo-Electron Tomography
Cryo-Electron Tomography (cryo-ET) is a new 3D imaging technique with
unprecedented potential for resolving submicron structural detail. Existing
volume visualization methods, however, cannot cope with its very low
signal-to-noise ratio. In order to design more powerful transfer functions, we
propose to leverage soft segmentation as an explicit component of visualization
for noisy volumes. Our technical realization is based on semi-supervised
learning where we combine the advantages of two segmentation algorithms. A
first weak segmentation algorithm provides good results for propagating sparse
user provided labels to other voxels in the same volume. This weak segmentation
algorithm is used to generate dense pseudo labels. A second powerful
deep-learning based segmentation algorithm can learn from these pseudo labels
to generalize the segmentation to other unseen volumes, a task that the weak
segmentation algorithm fails at completely. The proposed volume visualization
uses the deep-learning based segmentation as a component for segmentation-aware
transfer function design. Appropriate ramp parameters can be suggested
automatically through histogram analysis. Finally, our visualization uses
gradient-free ambient occlusion shading to further suppress visual presence of
noise, and to give structural detail desired prominence. The cryo-ET data
studied throughout our technical experiments is based on the highest-quality
tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact
in target sciences for visual data analysis of very noisy volumes that cannot
be visualized with existing techniques
Models of breast lesions based on three-dimensional X-ray breast images
This paper presents a method for creation of computational models of breast lesions with irregular shapes from patient Digital Breast Tomosynthesis (DBT) images or breast cadavers and whole-body Computed Tomography (CT) images. The approach includes six basic steps: (a) normalization of the intensity of the tomographic images; (b) image noise reduction; (c) binarization of the lesion area, (d) application of morphological operations to further decrease the level of artefacts; (e) application of a region growing technique to segment the lesion; and (f) creation of a final 3D lesion model. The algorithm is semi-automatic as the initial selection of the region of the lesion and the seeds for the region growing are done interactively. A software tool, performing all of the required steps, was developed in MATLAB. The method was tested and evaluated by analysing anonymized sets of DBT patient images diagnosed with lesions. Experienced radiologists evaluated the segmentation of the tumours in the slices and the obtained 3D lesion shapes. They concluded for a quite satisfactory delineation of the lesions. In addition, for three DBT cases, a delineation of the tumours was performed independently by the radiologists. In all cases the abnormality volumes segmented by the proposed algorithm were smaller than those outlined by the experts. The calculated Dice similarity coefficients for algorithm-radiologist and radiologist-radiologist showed similar values. Another selected tumour case was introduced into a computational breast model to recursively assess the algorithm. The relative volume difference between the ground-truth tumour volume and the one obtained by applying the algorithm on the synthetic volume from the virtual DBT study is 5% which demonstrates the satisfactory performance of the proposed segmentation algorithm. The software tool we developed was used to create models of different breast abnormalities, which were then stored in a database for use by researchers working in this field
Active shape models with focus on overlapping problems applied to plant detection and soil pore analysis
[no abstract
Quantifying Morphology and Diffusion Properties of Mesoporous Carbon from High-Fidelity 3D Reconstructions
A reliable quantitative analysis in electron tomography, which depends on the segmentation of the three-dimensional reconstruction, is challenging because of constraints during tilt-series acquisition (missing wedge) and reconstruction artifacts introduced by reconstruction algorithms such as the Simultaneous Iterative Reconstruction Technique (SIRT) and Discrete Algebraic Reconstruction Technique (DART). We have carefully evaluated the fidelity of segmented reconstructions analyzing a disordered mesoporous carbon used as support in catalysis. Using experimental scanning transmission electron microscopy (STEM) tomography data as well as realistic phantoms, we have quantitatively analyzed the effect on the morphological description as well as on diffusion properties (based on a random-walk particle-tracking simulation) to understand the role of porosity in catalysis. The morphological description of the pore structure can be obtained reliably both using SIRT and DART reconstructions even in the presence of a limited missing wedge. However, the measured pore volume is sensitive to the threshold settings, which are difficult to define globally for SIRT reconstructions. This leads to noticeable variations of the diffusion coefficients in the case of SIRT reconstructions, whereas DART reconstructions resulted in more reliable data. In addition, the anisotropy of the determined diffusion properties was evaluated, which was significant in the presence of a limited missing wedge for SIRT and strongly reduced for DART
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