269 research outputs found
Vessel Tree Reconstruction with Divergence Prior
Accurate structure analysis of high-resolution 3D biomedical images of vessels is a challenging issue and in demand for medical diagnosis nowadays. Previous curvature regularization based methods [10, 31] give promising results. However, their mathematical models are not designed for bifurcations and generate significant artifacts in such areas. To address the issue, we propose a new geometric regularization principle for reconstructing vector fields based on prior knowledge about their divergence. In our work, we focus on vector fields modeling blood flow pattern that should be divergent in arteries and convergent in veins. We show that this previously ignored regularization constraint can significantly improve the quality of vessel tree reconstruction particularly around bifurcations where non-zero divergence is concentrated. Our divergence prior is critical for resolving (binary) sign ambiguity in flow orientations produced by standard vessel filters, e:g: Frangi. Our vessel tree centerline reconstruction combines divergence constraints with robust curvature regularization. Our unsupervised method can reconstruct complete vessel trees with near-capillary details on both synthetic and real 3D volumes. Also, our method reduces angular reconstruction errors at bifurcations by a factor of two
Collision Cross-entropy for Soft Class Labels and Deep Clustering
We propose "collision cross-entropy" as a robust alternative to Shannon's
cross-entropy (CE) loss when class labels are represented by soft categorical
distributions y. In general, soft labels can naturally represent ambiguous
targets in classification. They are particularly relevant for self-labeled
clustering methods, where latent pseudo-labels are jointly estimated with the
model parameters and uncertainty is prevalent. In case of soft labels,
Shannon's CE teaches the model predictions to reproduce the uncertainty in each
training example, which inhibits the model's ability to learn and generalize
from these examples. As an alternative loss, we propose the negative log of
"collision probability" that maximizes the chance of equality between two
random variables, predicted class and unknown true class. We show that it has
the properties of a generalized CE. The proposed collision CE agrees with
Shannon's CE for one-hot labels, but the training from soft labels differs. For
example, unlike Shannon's CE, data points where y is a uniform distribution
have zero contribution to the training. Collision CE significantly improves
classification supervised by soft uncertain targets. Unlike Shannon's,
collision CE is symmetric for y and network predictions, which is particularly
relevant when both distributions are estimated in the context of self-labeled
clustering. Focusing on discriminative deep clustering where self-labeling and
entropy-based losses are dominant, we show that the use of collision CE
improves the state-of-the-art. We also derive an efficient EM algorithm that
significantly speeds up the pseudo-label estimation with collision CE
The Catalyzing Factors of Official Documents Exchange via Microblogging in Public Sectors: A Case Study based on the T-O-E Framework
Since Government transparency and information open has got more attention by both academia and practitioners with the development of information technologies (IT) and Internet, The popularity of Web 2.0 application provides the government some new opportunities and challenges. Official documents exchange via microblogging (ODEM) in the Bureau of Justice, Haining is a practice case of government information open in the new media. For analyzing the determinants from academic perspective and exploring the managerial value of the case, the paper report an exploratory case study based on the technology-organization-environment (TOE) framework. After several field interviews and rigorous data coding by following the case study methodology, we find that top managerâs support, personnelâs IT accomplishment, and regional economic and social environment are the key determinants of the emergence of ODEM, as well as the organizational structure and operational flow is not change immediately in this case. The limitation and future goals of the study are also discussed in the paper
UNDERSTANDING THE IMPACT OF INTERNET MEDIA ON PATIENT-CLINICIAN TRUST: MODEL DEVELOPMENT AND RESEARCH DESIGN
Patient-clinician trust is one of the major concerns regarding the relationship between the public and the healthcare industry. The development of Internet technology, especially Web 2.0 applications, provides us with a greater ability to exchange information and provide feedback. To describe and measure the impact of ICT-based new media on patient-clinician trust, this paper develops a theoretical model that builds on previous literature in both the healthcare and IS research areas. The paper also aims to explain the differing impacts of online reports (Web 1.0) and online comments (Web 2.0), along with the differing impacts of positive and negative comments. Expected contributions and an agenda for future empirical experiment are also discussed in the paper
Automatic Cloud Detection Method Based on Generative Adversarial Networks in Remote Sensing Images
Absence of remote earthquake triggering within the Coso and Salton Sea geothermal production fields
Geothermal areas are long recognized to be susceptible to remote earthquake triggering, probably due to the high seismicity rates and presence of geothermal fluids. However, anthropogenic injection and extraction activity may alter the stress state and fluid flow within the geothermal fields. Here we examine the remote triggering phenomena in the Coso geothermal field and its surrounding areas to assess possible anthropogenic effects. We find that triggered earthquakes are absent within the geothermal field but occur in the surrounding areas. Similar observation is also found in the Salton Sea geothermal field. We hypothesize that continuous geothermal operation has eliminated any significant differential pore pressure between fractures inside the geothermal field through flushing geothermal precipitations and sediments out of clogged fractures. To test this hypothesis, we analyze the pore-pressure-driven earthquake swarms, and they are found to occur outside or on the periphery of the geothermal production field. Therefore, our results suggest that the geothermal operation has changed the subsurface fracture network, and differential pore pressure is the primary controlling factor of remote triggering in geothermal fields
Superfast Liquid Transfer Strategy Through Sliding on a Liquid Membrane Inspired from Scorpion Setae
Although diversified biological structures have evolved fog collection abilities, the typical speeds of the condensed water droplets on these surfaces are too slow to have practical utility. The main challenge focuses on the elimination of the interfacial hydrodynamic resistance without external energy support. Here, an unusual strategy for superfast selfâsupport transfer condensed droplets is supported by sliding on seta of desert scorpion. It can be rapidly wetted by the fog droplets owing to its conical shape with linear gradient channels. A loss of interfacial resistance by this hydrodynamically lubricating water membrane could significantly accelerate the movement of the droplets, thus making its velocity increasing by one order of magnitude, or even more. Inspired by this novel strategy, the novel bioinspired materials are fabricated with the similar gradient channel structures and droplet transportation mode, which can make the condensed droplets spontaneously slide on the lowâfriction liquid membrane. The fundamental understanding of superfast fog capture and the sliding dynamics of condensed droplets in this system could inspire to develop novel materials or various systems to transfer liquid fast and efficiently without external energy support.An unusual strategy for superfast transferring condensed droplets by sliding on liquid membrane of desert scorpion seta is reported. A loss of interfacial resistance could significantly accelerate the droplets by this hydrodynamically lubricating liquid membrane. Then, the bioinspired materials with similar droplet transportation mode are fabricated, which will inspire to develop novel materials to transport liquid without external energy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146306/1/admi201800802-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146306/2/admi201800802.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146306/3/admi201800802_am.pd
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