Results 121 to 130 of about 791,315 (305)

Spinal Cord Infarction Versus Idiopathic Transverse Myelitis: Clinical, Radiological, and Functional Insights From a Retrospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Spinal cord infarction (SCI) is a rare but devastating myelopathy, characterized by a high disability rate and an unfavorable prognosis. It has often been underdiagnosed and misdiagnosed as idiopathic transverse myelitis (ITM). This study aimed to describe the clinical features, radiological biomarkers, treatments, and functional ...
Zeqiang Ji, Jianlong Zhang, Yiming Shi, Shiyu Shan, Yang Du, Guangshuo Li, Ying Jin, Yani Zhang, Chuanying Wang, Yijun Lin, Yuhao Guo, Decai Tian, Xingquan Zhao, Tian Song   +13 more
wiley   +1 more source

STMSF: Swin Transformer with Multi-Scale Fusion for Remote Sensing Scene Classification

Remote Sensing
Emerging vision transformers (ViTs) are more powerful in modeling long-range dependences of features than conventional deep convolution neural networks (CNNs). Thus, they outperform CNNs in several computer vision tasks.
Yingtao Duan, Chao Song, Yifan Zhang, Puyu Cheng, Shaohui Mei   +4 more
doaj   +1 more source

Diffusion Spectrum Imaging Maps Early Axonal Loss and a Unique Progressive Signal in Neuronal Intranuclear Inclusion Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To delineate specific in vivo white matter pathology in neuronal intranuclear inclusion disease (NIID) using diffusion spectrum imaging (DSI) and define its clinical relevance. Methods DSI was performed on 42 NIID patients and 38 matched controls.
Kaiyan Jiang, Yixiu Pei, Xiaobao Hu, Ying Xiong, Fang Wang, Yanyan Yu, Min Zhu, Dandan Tan, Meihong Zhou, Daojun Hong, Fuqing Zhou   +10 more
wiley   +1 more source

Foreground Detection with Deeply Learned Multi-Scale Spatial-Temporal Features

, 2018
Foreground detection, which extracts moving objects from videos, is an important and fundamental problem of video analysis. Classic methods often build background models based on some hand-craft features.
Zujun Yu, Yao Wang, Liqiang Zhu
core   +1 more source

Multi-scale Feature Imitation for Unsupervised Anomaly Localization

The unsupervised anomaly localization task faces the challenge of missing anomaly sample training, detecting multiple types of anomalies, and dealing with the proportion of the area of multiple anomalies. A separate teacher-student feature imitation network structure and a multi-scale processing strategy combining an image and feature pyramid are ...
Chao Hu, Shengxin Lai
openaire   +2 more sources

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-scale K-Means

, 2014
Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) algorithm to distinguish epileptic EEG
Zhu, Guohun, Guohun Zhu, Li, Yan, Shuaifang Wang, Wang, Shuaifang, Peng Wen, Wen, Peng (Paul), Yan Li   +7 more
core   +1 more source

Multi-scale aware turbulence network for underwater object recognition

Frontiers in Marine Science
Underwater imagery is subject to distortion, and the presence of turbulence in the fluid medium poses difficulties in accurately discerning objects.
Meng Zhou, Lei Cai, Jishen Jia, Yuhe Gao
doaj   +1 more source

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett, Abigail Dubois, Melanie Leguizamon, Alexander Song, Paula Trujillo, Colin D. McKnight, Ciaran M. Considine, Manus J. Donahue, Daniel O. Claassen   +8 more
wiley   +1 more source

Multi-resolution 3D CNN for learning multi-scale spatial features in CAD models

, 2021
Learning multi-scale spatial features from 3D spatial geometric representations of objects such as point clouds, 3D CAD models, surfaces, and RGB-D data can potentially improve object recognition accuracy.
Ghadai, Sambit, Lee, Xian Yeow, Balu, Aditya, Krishnamurthy, Adarsh, Sarkar, Soumik   +4 more
core