Quantitative Evaluation of Encrustations in Double-J Ureteral Stents With Micro-computed Tomography and Semantic Segmentation

Abstract Accurate evaluations of stent encrustation patterns, such as volume distribution, from different patient groups are valuable for clinical management and the development of better stents. This study compared stent encrustation patterns from stone and kidney transplant patients. Twenty-three double-J ureteral stents were collected at a single center from patients with stone disease or underwent kidney transplantation. Encrustations on stent samples were quantified by means of micro‑computed tomography and semantic segmentation using Convolutional Neural Network models. Luminal encrustation volume per stent unit was derived to represent encrustation level, which did not differ between patient groups in the first six weeks. However, stone patients showed higher encrustation levels over prolonged indwelling times (p = 0.036). Along the stent shaft body, the stone group showed higher encrustation levels near the ureteropelvic junction compared to the ureterovesical junction (p = 0.013), whereas the transplant group showed no such difference. Possible explanations were discussed regarding vesicoureteral refluxes. In both patient groups, stent pigtails were more susceptible to encrustations, and no difference between renal and bladder pigtail was identified. Our results suggest that excessively long stents with superfluous pigtails should be avoided.

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Semantic segmentation of the micro-structure of strain-hardening cement-based composites (SHCC) by applying deep learning on micro-computed tomography scans

Cement and Concrete Composites ◽

10.1016/j.cemconcomp.2020.103551 ◽

2020 ◽

Vol 108 ◽

pp. 103551 ◽

Cited By ~ 4

Author(s):

Renata Lorenzoni ◽

Iurie Curosu ◽

Sidnei Paciornik ◽

Viktor Mechtcherine ◽

Martin Oppermann ◽

...

Keyword(s):

Computed Tomography ◽

Deep Learning ◽

Strain Hardening ◽

Semantic Segmentation ◽

Micro Computed Tomography ◽

Micro Structure ◽

Computed Tomography Scans

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A randomized clinical trial evaluating the short-term results of ureteral stent encrustation in urolithiasis patients undergoing ureteroscopy: micro-computed tomography evaluation

Scientific Reports ◽

10.1038/s41598-021-89808-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Takashi Yoshida ◽

Kuniko Takemoto ◽

Yoshiko Sakata ◽

Tomoaki Matsuzaki ◽

Yuya Koito ◽

...

Keyword(s):

Computed Tomography ◽

Adverse Events ◽

Similar Efficacy ◽

Ureteral Stent ◽

Ureteral Stents ◽

Micro Computed Tomography ◽

Short Term ◽

Urine Ph ◽

Distal Loop ◽

The Difference

AbstractAlthough many ureteral stents are commercially available, the actuality of encrustation is yet to be elucidated in humans. This study compared the Tria Ureteral Stent with PercuShield and the Polaris Ultra Ureteral Stent with HydroPlus Coating for short-term encrustation formation. Eighty-four patients, who required ureteral stent placement after ureteroscopy, were randomized into two stent groups. After stent removal on postoperative day 14, the encrustation volume on the stent surface was measured by micro-computed tomography. The primary outcome was the inner luminal encrustation volume. Secondary outcomes were encrustation volume on the outer or total surfaces and occurrence of adverse events. Clinical factors related to encrustation were also assessed as a post-hoc analysis. Finally, of the 82 patients analyzed, 75 (91.5%) had encrustation in the inner lumen of the stent. The difference in median inner encrustation volume between the Tria and Polaris Ultra stents was comparable (0.56 vs. 0.37 mm3, P = 0.183). There was no difference observed in the encrustation volume on the outer/total surfaces and stent-related adverse events. In both ureteral stents, the shaft body showed significant inner luminal encrustation compared to the proximal or distal loop (all, P < 0.05). Dyslipidemia (P = 0.027), elevated urine pH (P = 0.046), and crystalluria (P = 0.010) were associated with encrustation formation. The Tria and Polaris Ultra stents had similar efficacy for preventing encrustation in the short-term. Further studies are required to compare their long-term patency.

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A method of searching and marking artifacts in images applying detection and segmentation algorithms

Analysis and data processing systems ◽

10.17212/2782-2001-2021-4-7-18 ◽

2021 ◽

pp. 7-18

Author(s):

Andrey M. Kitenko ◽

Keyword(s):

Neural Networks ◽

Network Models ◽

Semantic Segmentation ◽

Document Processing ◽

Neural Network Models ◽

Convolutional Network ◽

Human Errors ◽

Search And Selection ◽

Stress Fatigue ◽

Selection Of

The paper explores the possibility of using neural networks to single out target artifacts on different types of documents. Numerous types of neural networks are often used for document processing, from text analysis to the allocation of certain areas where the desired information may be contained. However, to date, there are no perfect document processing systems that can work autonomously, compensating for human errors that may appear in the process of work due to stress, fatigue and many other reasons. In this work, the emphasis is on the search and selection of target artifacts in drawings, in conditions of a small amount of initial data. The proposed method of searching and highlighting artifacts in the image consists of two main parts, detection and semantic segmentation of the detected area. The method is based on training with a teacher on marked-up data for two convolutional neural networks. The first convolutional network is used to detect an area with an artifact, in this example YoloV4 was taken as the basis. For semantic segmentation, the U-Net architecture is used, where the basis is the pre-trained Efficientnetb0. By combining these neural networks, good results were achieved, even for the selection of certain handwritten texts, without using the specifics of building neural network models for text recognition. This method can be used to search for and highlight artifacts in large datasets, while the artifacts themselves may be different in shape, color and type, and they may be located in different places of the image, have or not have intersection with other objects.

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A Few-shot segmentation method for prohibited item inspection

Journal of X-Ray Science and Technology ◽

10.3233/xst-210846 ◽

2021 ◽

pp. 1-13

Author(s):

Zhenyue Zhu ◽

Shujing Lyu ◽

Yue Lu

Keyword(s):

Spatial Information ◽

Graph Matching ◽

Rapid Development ◽

Automatic Segmentation ◽

Network Models ◽

Semantic Segmentation ◽

Training Data ◽

Neural Network Models ◽

Query Image ◽

Network Methods

BACKGROUND: With the rapid development of deep learning, several neural network models have been proposed for automatic segmentation of prohibited items. These methods usually based on a substantial amount of labelled training data. However, for some prohibited items of rarely appearing, it is difficult to obtain enough labelled samples. Furthermore, the category of prohibited items varies in different scenarios and security levels, and new items may appear from time to time. OBJECTIVE: In order to predict prohibited items with only a few annotated samples and inspect prohibited items of new categories without the requirement of retraining, we introduce an Attention-Based Graph Matching Network. METHODS: This model applies a few-shot semantic segmentation network to address the issue of prohibited item inspection. First, a pair of graphs are modelled between a query image and several support images. Then, after the pair of graphs are entered into two Graph Attention Units with similarity weights and equal weights, the attentive matching results will be obtained. According to the matching results, the prohibited items can be segmented from the query image. RESULTS: Experiment results and comparison using the Xray-PI dataset and SIXray dataset show that our model outperforms several other state-of-the-art learning models. CONCLUSIONS: This study demonstrates that the similarity loss function and the space restriction module proposed by our model can effectively remove noise and supplement spatial information, which makes the segmentation of the prohibited items on X-ray images more accurate.

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Multi-scale, micro-computed tomography-based pore network models to simulate drainage in heterogeneous rocks

Advances in Water Resources ◽

10.1016/j.advwatres.2015.02.003 ◽

2015 ◽

Vol 78 ◽

pp. 36-49 ◽

Cited By ~ 96

Author(s):

Tom Bultreys ◽

Luc Van Hoorebeke ◽

Veerle Cnudde

Keyword(s):

Computed Tomography ◽

Network Models ◽

Pore Network ◽

Micro Computed Tomography ◽

Multi Scale ◽

Heterogeneous Rocks

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Geometrical and Topological Analysis of Pore Space in Sandstones Based on X-ray Computed Tomography

Energies ◽

10.3390/en13153774 ◽

2020 ◽

Vol 13 (15) ◽

pp. 3774 ◽

Cited By ~ 1

Author(s):

Linxian Gong ◽

Lei Nie ◽

Yan Xu

Keyword(s):

Computed Tomography ◽

Fluid Flow ◽

Pore Space ◽

Topological Analysis ◽

Network Models ◽

High Porosity ◽

Micro Computed Tomography ◽

X Ray ◽

And Topology ◽

Low Porosity

The pore geometry and topology properties of pore space in rocks are significant for a better understanding of the complex hydrologic and elastic properties. However, geometry and topology information about the sandstone pore structures is not fully available. In this study, we obtained the topological and geometrical pore parameters from a representative elementary volume (REV) for fluid flow in sandstone samples. For comparison, eight types of sandstones with various porosities were studied based on the X-ray micro-computed tomography technique. In this study, the REV size was selected based on the parameters from the respective pore network models (PNM), not just the porosity. Our analysis indicates that despite different porosity, all the sandstone samples have highly triangular-shaped pores and a high degree of pore structural isotropy. The high porosity group sandstones exhibit wider ranges of pore sizes than the low porosity group sandstones. Compared to the high porosity group sandstones, the low porosity group sandstones samples showing a higher global aspect ratio, indicating some pores exist in the form of bottlenecks. The pore topological properties of different sandstones show a high dependence of the porosity. The high porosity group sandstones obtain large coordination numbers, large connectivity densities and low tortuosities. The results from this study will help better understand the complex pore structure and the fluid flow in sandstone.

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Identification of Fibrotic Thickening as Early Marker of Aortic Valve Stenosis Using X-Ray Micro Computed Tomography and Optical Coherence Tomography

The Thoracic and Cardiovascular Surgeon ◽

10.1055/s-0036-1571661 ◽

2016 ◽

Vol 64 (S 01) ◽

Author(s):

A. Jannasch ◽

C. Schnabel ◽

M. Santini ◽

S. Fest-Santini ◽

M. Lorenzi ◽

...

Keyword(s):

Computed Tomography ◽

Optical Coherence Tomography ◽

Aortic Valve ◽

Aortic Valve Stenosis ◽

Optical Coherence ◽

Micro Computed Tomography ◽

X Ray ◽

Early Marker

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Cortical and trabecular bone parameters from HR-Pqct images at the Tibia: a local comparison with synchrotron radiation micro-computed tomography

Bone Abstracts ◽

10.1530/boneabs.1.pp316 ◽

2013 ◽

Author(s):

Agnes Ostertag ◽

Francoise Peyrin ◽

Sylvie Fernandez ◽

Jean-Denis Laredo ◽

Vernejoul Marie-Christine De ◽

...

Keyword(s):

Computed Tomography ◽

Synchrotron Radiation ◽

Trabecular Bone ◽

Micro Computed Tomography ◽

Bone Parameters ◽

Local Comparison

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Morphology and Affinities of Ampelocissites Seeds (Vitaceae: Ampelopsis clade) from the Paleogene of Texas, USA

Systematic Botany ◽

10.1600/036364420x15935294613400 ◽

2020 ◽

Vol 45 (3) ◽

pp. 478-482

Author(s):

Steven R. Manchester

Keyword(s):

Computed Tomography ◽

Cross Sections ◽

Seed Coat ◽

Ct Scanning ◽

Seed Morphology ◽

Early Eocene ◽

Micro Computed Tomography ◽

X Ray ◽

Fossil Seeds ◽

Fossil Genus

Abstract—The type material on which the fossil genus name Ampelocissites was established in 1929 has been reexamined with the aid of X-ray micro-computed tomography (μ-CT) scanning and compared with seeds of extant taxa to assess the relationships of these fossils within the grape family, Vitaceae. The specimens were collected from a sandstone of late Paleocene or early Eocene age. Although originally inferred by Berry to be intermediate in morphology between Ampelocissus and Vitis, the newly revealed details of seed morphology indicate that these seeds represent instead the Ampelopsis clade. Digital cross sections show that the seed coat maintains its thickness over the external surfaces, but diminishes quickly in the ventral infolds. This feature, along with the elliptical chalaza and lack of an apical groove, indicate that Ampelocissites lytlensis Berry probably represents Ampelopsis or Nekemias (rather than Ampelocissus or Vitis) and that the generic name Ampelocissites may be useful for fossil seeds with morphology consistent with the Ampelopsis clade that lack sufficient characters to specify placement within one of these extant genera.

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