Results 91 to 100 of about 2,269,164 (264)

Medical Image Retrieval Approach by Texture Features Fusion Based on Hausdorff Distance

, 2018
Medical images play an important role in the hospital diagnosis and treatment, which include a lot of valuable medical information. Manually annotated viewing is obviously not effective in managing large amounts of medical imaging data.
Sun Xiaoming, Zhang Ning, Wu Haibin, Yu Xiaoyang, Wu Xue, Yu Shuang   +5 more
semanticscholar   +1 more source

Market Allocations Under Conflation of Goods

International Economic Review, EarlyView.
ABSTRACT We study competitive equilibria in exchange economies when a continuum of goods is conflated into a finite set of commodities. The design of conflation choices affects the allocation of scarce resources among agents, by constraining trading opportunities and shifting competitive pressures.
Niccolò Urbinati, Marco LiCalzi
wiley   +1 more source

Isodiametric inequality in Carnot groups

, 2010
The classical isodiametric inequality in the Euclidean space says that balls maximize the volume among all sets with a given diameter. We consider in this paper the case of Carnot groups.
Rigot, Severine
core   +4 more sources

Deep learning assisted high‐resolution microscopy image processing for phase segmentation in functional composite materials

Journal of Microscopy, EarlyView.
Abstract In the domain of battery research, the processing of high‐resolution microscopy images is a challenging task, as it involves dealing with complex images and requires a prior understanding of the components involved. The utilisation of deep learning methodologies for image analysis has attracted considerable interest in recent years, with ...
Ganesh Raghavendran, Bing Han, Fortune Adekogbe, Shuang Bai, Bingyu Lu, William Wu, Minghao Zhang, Ying Shirley Meng   +7 more
wiley   +1 more source

Realizations of Gromov-Hausdorff Distance

, 2016
6 ...
Ivanov, Alexander, Iliadis, Stavros, Tuzhilin, Alexey   +2 more
openaire   +2 more sources

Catching the head, tail, and everything in between: a streaming algorithm for the degree distribution

, 2015
The degree distribution is one of the most fundamental graph properties of interest for real-world graphs. It has been widely observed in numerous domains that graphs typically have a tailed or scale-free degree distribution.
McGregor, Andrew, Seshadhri, C., Simpson, Olivia   +2 more
core   +1 more source

Attractors for an Energy‐Damped Viscoelastic Plate Equation

Mathematical Methods in the Applied Sciences, Volume 48, Issue 14, Page 13864-13881, 30 September 2025.
ABSTRACT In this paper, we consider a class of non‐autonomous beam/plate equations with an integro‐differential damping given by a possibly degenerate memory and an energy damping given by a nonlocal ε$$ \varepsilon $$‐perturbed coefficient. For each ε>0$$ \varepsilon >0 $$, we show that the dynamical system generated by the weak solutions of the ...
V. Narciso, M. J. D. Nascimento, M. L. Pelicer, I. A. S. Picolli   +3 more
wiley   +1 more source

An improved two-dimensional variational mode decomposition algorithm and its application in oil pipeline image

Systems Science & Control Engineering, 2020
In this paper, an image denoising algorithm is presented based on the two-dimensional variational mode decomposition (2D-VMD) and the Hausdorff distance (HD).
Hongyu Gao, Liyuan Ma, Hongli Dong, Jingyi Lu, Gongfa Li   +4 more
doaj   +1 more source

A self‐gated 4D‐MRI sequence for internal target volume delineation in liver: Phantom and pre‐clinical validation [PDF]

J Appl Clin Med Phys
Abstract Background The poor soft tissue resolution of four‐dimensional computed tomography (4D‐CT) limits its utility in delineating liver cancer target volumes. Purpose To compare the consistency between four‐dimensional magnetic resonance imaging (4D‐MRI) using T1‐weighted (T1w) radial stack‐of‐stars (SOS) gradient echo (GRE) sequences and 4D‐CT in ...
Chen S, Liu M, Xue S, Zeng Y, Pang B, Zhang Q, Hou X, Yang H, Guan Z, Quan H, Ruan C, Yang Z.   +11 more
europepmc   +2 more sources

Impact of deep learning model uncertainty on manual corrections to MRI‐based auto‐segmentation in prostate cancer radiotherapy

Journal of Applied Clinical Medical Physics, Volume 26, Issue 9, September 2025.
Abstract Background Deep learning (DL)‐based organ segmentation is increasingly used in radiotherapy. While methods exist to generate voxel‐wise uncertainty maps from DL‐based auto‐segmentation models, these maps are rarely presented to clinicians. Purpose This study aimed to evaluate the impact of DL‐generated uncertainty maps on experienced radiation
Viktor Rogowski, Angelica Svalkvist, Matteo Maspero, Tomas Janssen, Federica Carmen Maruccio, Jenny Gorgisyan, Jonas Scherman, Ida Häggström, Victor Wåhlstrand, Adalsteinn Gunnlaugsson, Martin P Nilsson, Mathieu Moreau, Nándor Vass, Niclas Pettersson, Christian Jamtheim Gustafsson   +14 more
wiley   +1 more source