Results 51 to 60 of about 8,230,666 (286)

Multichannel seismic impedance inversion based on Attention U-Net

Frontiers in Earth Science, 2023
Recently, seismic inversion has made extensive use of supervised learning methods. The traditional deep learning inversion network can utilize the temporal correlation in the vertical direction.
Juan Ning, Shu Li, Shu Li, Zong Wei, Xi Yang   +4 more
doaj   +1 more source

Comparison of Kidney Segmentation Under Attention U-Net Architectures

, 2021
One of the most prominent machine learning advantages in the medical industry is the early detection of disease. Automatic kidney detection is of great importance for rapid diagnosis and treatment, where related diseases occupy over 73,750 new cases in ...
Marcia Hon (11359961), Vasileios Alevizos (11359218)   +1 more
core   +1 more source

Infant Embryonal CNS Tumors: Molecular Insights and Treatment Considerations for Contemporary Pediatric Neuro‐Oncology

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Embryonal tumors comprise the majority of malignant central nervous system (CNS) neoplasms diagnosed in children under 3 years of age. Compared with their counterparts in older children, these tumors exhibit distinct molecular biology and a more aggressive clinical phenotype, while their management is complicated by the heightened ...
Sudarshawn Damodharan, Mariah Wright‐Nadkarni, Mohamed S. Abdelbaki, Girish Dhall   +3 more
wiley   +1 more source

Composite Attention Residual U-Net for Rib Fracture Detection

Entropy, 2023
Computed tomography (CT) images play a vital role in diagnosing rib fractures and determining the severity of chest trauma. However, quickly and accurately identifying rib fractures in a large number of CT images is an arduous task for radiologists.
Xiaoming Wang, Yongxiong Wang
doaj   +1 more source

Ewing Sarcoma in Infants and Children Under 2 Years of Age: A French Retrospective Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Ewing sarcoma, the second most common primary bone cancer in children, requires intensive treatment that may lead to significant long‐term sequelae, particularly in infants. We retrospectively analyzed data from 1621 French patients treated between 1988 and 2015 within the EW88/93/97 or EE99 trials, focusing on 17 infants diagnosed before 24 ...
Elodie Verdier, Nathalie Cozic, Marie‐Dominique Tabone, Gaelle Pierron, Perrine Marec‐Berard, Sarah Winter, Gabriel Revon‐Rivière, Cyril Lervat, Dominique Plantaz, Marie‐Pierre Castex, Gregory Guimard, Estelle Thebaud, Stephanie Proust, Laure Saumet, Natacha Entz‐Werle, Sophie Taque, Cécile Vérité, Marta Jimenez, Nathalie Gaspar   +18 more
wiley   +1 more source

Provider and Parent Perspectives on Prioritizing the “Asking and Monitoring” Pediatric Cancer Psychosocial Standards of Care

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background The Standards for Psychosocial Care for Children with Cancer and Their Families (“Standards”) are evidence‐based guidelines for psychosocial care in pediatric oncology. Care related to the three “Asking and Monitoring” Standards—Assessment of Psychosocial Needs, Assessment of Financial Needs, and Monitoring Neurocognitive Problems ...
Julia B. Tager, Natalie Koskela‐Staples, Emily M. Pariseau, Michele Scialla, Kimberly Buff, Lori Wiener, Victoria Sardi Brown, Anne E. Kazak, Kimberly S. Canter   +8 more
wiley   +1 more source

Attention Mechanisms in U-Net Variants for Brain MRI Segmentation: A Narrative Review of Spatial, Channel, and Transformer-Based Approaches [PDF]

InfoScience Trends
Accurately delineating brain tumors in magnetic resonance imaging (MRI) scans is a critical step in clinical diagnostics, radiotherapy planning, and evaluating therapeutic outcomes.
Ali khodadadi, Mohammad Shakoor
doaj   +1 more source

EAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT

CoRR, 2021
Purpose: This paper proposes a new network framework called EAR-U-Net, which leverages EfficientNetB4, attention gate, and residual learning techniques to achieve automatic and accurate liver segmentation. Methods: The proposed method is based on the U-Net framework. First, we use EfficientNetB4 as the encoder to extract more feature information during
Jinke Wang, Xiangyang Zhang, Peiqing Lv, Lubiao Zhou, Haiying Wang 0008   +4 more
openaire   +2 more sources

A Situational Assessment of the Diagnostic Landscape and Organizational Readiness to Implement Next‐Generation Sequencing at Two Childhood Cancer Treatment Centers in Ghana

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Next‐generation sequencing (NGS) has emerged as a promising approach to improve diagnostic accuracy, but its feasibility in low‐ and middle‐income countries remains unknown. This study characterized the diagnostic landscape and assessed organizational readiness for NGS implementation at two childhood cancer treatment centers in Accra ...
Melissa Carvalho, Emmanuella Amoako, Nihad Salifu, Lily Gloria Tagoe, Yaw Bediako, Michelle Hermiston, Catherine Segbefia   +6 more
wiley   +1 more source

A Method of Steel Bar Image Segmentation Based on Multi-Attention U-Net

IEEE Access, 2021
Due to it is difficulty to segment the steel bar image in a complex background and with external interference. In this paper, we propose a multi-attention U-Net to segment the steel bar image.
Jie Shi, Kunpeng Wu, Chaolin Yang, Nenghui Deng   +3 more
doaj   +1 more source