Results 101 to 110 of about 3,294 (223)

Comparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D‐CT in radiotherapy

Journal of Applied Clinical Medical Physics, Volume 27, Issue 10, October 2026.
Abstract Background Deformable image registration (DIR) is essential for thoracic four‐dimensional computed tomography (4D‐CT)‐based radiotherapy applications. Recently, deep learning‐based DIR methods such as VoxelMorph have been proposed; however, their performance relative to clinically used DIR algorithms remains unclear.
Mizuha Sakai, Megumi Nakao, Hideaki Hirashima, Masahiro Yoneyama, Noriko Kishi, Takashi Mizowaki, Mitsuhiro Nakamura   +6 more
wiley   +1 more source

Clinical evaluation and regression test of a commercial deep‐learning auto‐segmentation model

Journal of Applied Clinical Medical Physics, Volume 27, Issue 10, October 2026.
Abstract Background Commercial deep‐learning segmentation (DLS) tools are increasingly used in clinical practice. Software updates may alter segmentation performance, highlighting the need for systematic clinical evaluation before implementation. Purpose This study presents our experience in clinically evaluating and regression‐testing a RayStation DLS
Roya Barati, Jingwei Duan, Song Gao, Yao Zhao, Xinru Chen, Cenji Yu, Zhan Xu, Moghadaseh Khaleghibizaki, Fredrik Lofman, Jared Ohrt, Laurence Court, Peter Balter, Jinzhong Yang   +12 more
wiley   +1 more source

Correction: Biś, A., et al. Hausdorff Dimension and Topological Entropies of a Solenoid. Entropy 2020, 22, 506. [PDF]

Entropy (Basel), 2020
Biś A, Namiecińska A.
europepmc   +1 more source

Synchrotron‐Based Deep Learning Network of the Inner Ear: Development and Expert Validation

The Laryngoscope, Volume 136, Issue 10, Page 4209-4218, October 2026.
A deep learning network to automatically segment the inner ear from preoperative clinical scans was developed using synchrotron‐radiation phase contrast imaging (SR‐PCI). On an unseen test set, the network significantly outperformed seven expert otologists/radiologists, the mean expert segmentation, and a simultaneous truth and performance level ...
Ashley Micuda, Kyle Rioux, Luke Helpard, Munir Demir Bajin, Zahra Kassam, Sachin Pandey, Jaehyun Hwang, Griselda T. Romero‐Sanchez, Manas Sharma, Lorne S. Parnes, Hanif M. Ladak, Sumit K. Agrawal   +11 more
wiley   +1 more source

Hausdorff Dimension of Caloric Measure

American Journal of Mathematics
abstract: We examine caloric measures $\omega$ on general domains in $\RR^{n+1}=\RR^n\times\RR$ (space $\times$ time) from the perspective of geometric measure theory. On one hand, we give a direct proof of a consequence of a theorem of Taylor and Watson (1985) that the lower parabolic Hausdorff dimension of $\omega$ is at least $n$ and $\omega\ll ...
Badger, Matthew, Genschaw, Alyssa
openaire   +3 more sources

One‐Class Autoencoders for Porcelain Art Attribution: The Case of William Billingsley

Archaeometry, Volume 68, Issue 5, Page 1110-1122, October 2026.
ABSTRACT This comprehensive study explores the application of advanced machine learning techniques, specifically one‐class autoencoders, for the authentication and attribution of English porcelain artworks. Focusing primarily on the works of William Billingsley (1758–1828), one of England's most celebrated porcelain decorators, we demonstrate how ...
Hassan Ugail, Morgan Denyer, Rachel Denyer, Howell Edwards   +3 more
wiley   +1 more source

Hausdorff dimension of the Apollonian gasket

Inventiones mathematicae
Abstract The Apollonian gasket is a well-studied circle packing. Important properties of the packing, including the distribution of the circle radii, are governed by its Hausdorff dimension. No closed form is currently known for the Hausdorff dimension, and its computation is a special case of a more general and hard problem: effective ...
Polina Vytnova, Caroline Wormell
openaire   +2 more sources

From SAM 1 to SAM 3: Benchmarking Zero‐Shot Cross‐Domain Medical Image Segmentation

Expert Systems, Volume 43, Issue 10, October 2026.
ABSTRACT Segmentation models have demonstrated significant potential in medical image segmentation. However, there is currently a lack of systematic, cross‐generation comparative evaluations to assess whether the iterations from SAM1 to SAM 3 can effectively enhance the clinical applicability of zero‐shot segmentation. To address this issue, this paper
Shujun Lv, Bo Fang, Yongfei Wu, Kun Li, Qiankun Li, Junxin Chen   +5 more
wiley   +1 more source

Can Deep Learning Methods Differentiate Temporomandibular Joint Disorders From Healthy Joints? A 3D Artificial Intelligence Algorithm Study Based on CBCT Images

Journal of Oral Rehabilitation, Volume 53, Issue 10, Page 1932-1942, October 2026.
In this study, an integrated deep learning approach was developed for the evaluation of temporomandibular joint disorders using multicentre CBCT images. The mandibular condyle was first automatically segmented using the nnU‐Net v2 architecture. Subsequently, 3D‐CNN algorithms classified the condyles as healthy or unhealthy and further distinguished ...
İbrahim Şevki Bayrakdar, Sevda Kurt‐Bayrakdar, Alican Kuran, Özer Çelik, Kaan Orhan, Rohan Jagtap   +5 more
wiley   +1 more source

Complex continued fractions with restricted entries

Electronic Journal of Differential Equations, 1998
We study special infinite iterated function systems derived from complex continued fraction expansions with restricted entries. We focus our attention on the corresponding limit set whose Hausdorff dimension will be denoted by $h$. Our primary goal is to
Pawel Hanus, Mariusz Urbanski
doaj