Results 81 to 90 of about 5,768,655 (280)

U-Net V2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation

2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)
In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical image segmentation. It aims to augment the infusion of semantic information into low-level features while simultaneously refining high-level features with finer details.
Yaopeng Peng, Milan Sonka, Danny Z. Chen
openaire   +3 more sources

U-NetCTS: U-Net deep neural network for fully automatic segmentation of 3D CT DICOM volume

, 2022
The accurate segmentation of computed tomography (CT) scan volume is an essential step in radiomic analysis as well as in developing advanced surgical planning techniques with numerous medical applications.
O. Dorgham, Dorgham, O, Mirjalili, S, A. Hyari, Al-Najdawi, N, M.H. Ryalat, S. Mirjalili, Hyari, A, M. Abu Naser, Naser, MA, Ryalat, MH, N. Al-Najdawi   +11 more
core   +1 more source

Bone and Soft Tissue Neoplasms in Infants Versus Older Children: A Report From the Cancer in Young People in Canada Program

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background and Aims Infant bone and soft tissue neoplasms present distinct clinical challenges and lack large‐scale data to inform treatment decisions. This study aims to characterize bone and soft tissue neoplasms in infants in Canada and to compare their outcomes with those of older pediatric patients.
Samuel Sassine, Hallie Coltin, Maria Kondyli, Monia Marzouki, Nicolas Prud'homme, Nida Usmani, Rebecca J. Deyell, Lesleigh Abbott, Tony H. Truong, Sapna Oberoi, Ketan Kulkarni, Josée Brossard, Lynette Bowes, Paul Gibson, Sarah McKillop, Roona Sinha, Lillian Sung, Catherine Vezina, Laura Wheaton, Alexandra P. Zorzi, Marie‐Claude Pelland‐Marcotte, Thai Hoa Tran   +21 more
wiley   +1 more source

KAN–U-Net: An Enhanced KAN-Fused U-Net for Medical Image Segmentation

IET Software
The U-Net model has demonstrated strong performance in the field of medical image segmentation. Moreover, several enhanced and improved versions of this model have emerged by incorporating transformer or MLP modules.
Cheng Zhu, Weiping Zhu, Jin Liu, Wei Li, Yongqiang Tang, Xiao Liu, Xin Wang   +6 more
doaj   +1 more source

Impact of Initial Treatment Setting on Survival in Relapsed Pediatric and AYA Bone Sarcomas: A Secondary Analysis of a Prospective Clinical Trial

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Outcomes in relapsed or refractory pediatric and AYA bone sarcomas remain poor, and the impact of early referral to specialized sarcoma centers on survival is unclear. Early centralization of care may improve local and systemic treatment quality, but evidence in this population is limited.
Justyna Antoniuk‐Majchrzak, Katarzyna Bilska, Tomasz Koziński, Jadwiga Węcławek‐Tompol, Dorota Sega‐Pondel, Radosław Chaber, Wanda Badowska, Katarzyna Rosłan, Hanna Koseła‐Paterczyk, Anna Raciborska   +9 more
wiley   +1 more source

DKA-U-Net: Dynamic-Kernel Attention U-Net for Brain Tumor Segmentation From MRI

IEEE Access
The precise delineation of tumor boundaries and the accurate segmentation of small tumor subregions are two pivotal factors influencing the performance of brain tumor segmentation from MRI.
Junjie Zhu, Heng Liu
doaj   +1 more source

Feeding, Fear, and Acceptance: Caregivers’ Experiences of Nutritional Support During Childhood Cancer Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose To explore caregivers' experiences and perceptions of the nutritional challenges faced by children and adolescents undergoing cancer treatment, including oral intake and the use of nutritional support. Methods This was a qualitative study based on focus groups with parents and caregivers at a Brazilian pediatric oncology hospital ...
Danyelle Apparecida Balsamão Marques, Mariana dos Santos Murra, Welinton Hirai, Ana Laura Balduino do Nascimento, Karla Emilia de Sá Rodrigues, Wilson Elias de Oliveira Junior   +5 more
wiley   +1 more source

Dense-U-net network structure.

A brain tumor magnetic resonance image processing algorithm can help doctors to diagnose and treat the patient’s condition, which has important application significance in clinical medicine. This paper proposes a network model based on the combination of
Xiaoli Yang (314226), Zhenwei Li (834360), Lipei Liu (15278939), Xiaoqin Wu (470428), Yuxin Xia (1650367)   +4 more
core   +1 more source

Serum Myonectin Levels Are Positively Associated With Physical Function and Lower Frailty‐Related Limitation in Maintenance Hemodialysis Patients: A Cross‐Sectional Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Maintenance hemodialysis (MHD) patients frequently suffer from frailty, characterized by reduced physical function and poor prognosis. Myokines, such as myonectin, secreted by muscle, are emerging regulators of systemic health. This study investigated the relationship between serum myonectin, adipokines (adiponectin, omentin), and ...
Kenichi Kono, Yoshifumi Moriyama, Koji Ohashi, Naoya Otaka, Minako Tatsumi, Toyoaki Murohara, Noriyuki Ouchi, Satoru Oshima   +7 more
wiley   +1 more source

Enhanced glaucoma detection using U-Net and U-Net+ architectures using deep learning techniques

Photodiagnosis and Photodynamic Therapy
This study compares multiple image processing and deep learning methods to demonstrate an enhanced approach to glaucoma diagnosis. The approach focuses on noise reduction using median filtering and optic disc segmentation utilizing the U-Net and U-Net ...
B.P. Pradeep kumar, Pramod K.B. Rangaiah, Robin Augustine   +2 more
doaj   +1 more source