Results 131 to 140 of about 7,273 (258)
Tate modules as condensed modules
Abstract We prove that the category of countable Tate modules over an arbitrary discrete ring embeds fully faithfully into that of condensed modules. If the base ring is of finite type, we characterize the essential image as generated by the free module of infinite countable rank under direct sums, duals and retracts.
Valerio Melani +2 more
wiley +1 more source
Gromov-Hausdorff distances between quotient metric spaces
The Hausdorff distance measures how far apart two sets are in a common metric space. By contrast, the Gromov-Hausdorff distance provides a notion of distance between two abstract metric spaces.
Bruda, Glenn +9 more
core
Sections and projections of the outer and inner regularizations of a convex body
Abstract We establish new geometric inequalities comparing the volumes of sections and projections of a convex body, whose barycenter or Santaló point is at the origin, with those of its inner and outer regularizations. We also provide functional extensions of these inequalities to the setting of log‐concave functions. Our approach relies on the recent
Natalia Tziotziou
wiley +1 more source
Abstract Background Auto‐segmentation tools are essential in adaptive radiation therapy (ART). While evaluation typically relies on geometric metrics like Dice similarity coefficient (DSC), high scores do not always translate to clinical acceptability.
Jae Choon Lee +7 more
wiley +1 more source
Abstract Background Online adaptive radiotherapy (ART) relies on cone‐beam computed tomography (CBCT) imaging for daily treatment adaptation, but CBCT's physical limitations can compromise contour delineation and dose calculation accuracy. The relationship between image quality metrics and clinical ART workflow accuracy remains unclear.
Sunhwa Kim +5 more
wiley +1 more source
Lorentzian metric spaces and their Gromov–Hausdorff convergence
AbstractWe present an abstract approach to Lorentzian Gromov–Hausdorff distance and convergence, and an alternative approach to Lorentzian length spaces that does not use auxiliary “positive signature” metrics or other unobserved fields. We begin by defining a notion of (abstract) bounded Lorentzian metric space which is sufficiently general to ...
E. Minguzzi, S. Suhr
openaire +4 more sources
Abstract Background Accurate and consistent delineation of target and normal structures is essential for safe and effective radiotherapy. Compared with manual or atlas‐based methods, deep learning‐based auto‐contouring has demonstrated improved efficiency and reduced interobserver variability. However, its performance can vary across anatomical regions
Sara Endo +4 more
wiley +1 more source
Some Fixed Point Results for Multivalued Mappings in b−Multiplicative and b−Metric Space
The main outcome of this paper is to introduce the notion of Hausdorff b-multiplicative metric space and to present some fixed point results for multivalued mappings in this space.
Mazhar Mehmood +2 more
doaj
The Hausdorff metric andCˇebysˇev centres
Borwein, J., Keener, L.
openaire +2 more sources
A machine learning model utilizing choroid plexus (CP) radiomics effectively distinguishes Alzheimer's disease (AD) from mild cognitive impairment (MCI) and predicts MCI‐to‐AD progression risk. After integration with clinical features, the model exhibits strong predictive performance. The CP radiomics features correlate significantly with cognitive and
Feiyue Yin +13 more
wiley +1 more source

