Results 51 to 60 of about 170,175 (308)

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

Distance Regularized Level Set Evolution for Medical Image Segmentation [PDF]

, 2013
Medical image is an important tool because it can be used for surgical planning and simulation, radiotherapy planning, and tracking the progress of disease. To analyze the medical image, it must partitioned into different segment using image segmentation
Pranowo, Pranowo, Rianto , Indra
core  

Feasibility and Safety of Somato‐Cognitive Coordination Therapy for Cerebellar Ataxia Following Pediatric Brain Tumor Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Cerebellar ataxia after pediatric brain tumor treatment can cause persistent gait, balance, and speech impairment, yet no established rehabilitation strategy exists. Somato‐cognitive coordination therapy (SCCT) is a virtual reality–guided intervention designed to promote sensorimotor integration through visually constrained reaching
Masanobu Takeuchi, Takashi Matsuzawa, Jun Yamanishi, Masahiro Yoshitomi, Junji Ikeda, Shin‐Ichi Tsujimoto, Yasuteru Yamaguchi, Norio Shiba, Dhroov Pathare, Ayumi Kato, Masahiko Hara   +10 more
wiley   +1 more source

A review of the evolution and challenges of few-shot medical image semantic segmentation [PDF]

PeerJ Computer Science
Image segmentation, as a fundamental task in computer vision, aims to achieve pixel-level delineation between target regions and background. In the field of medical image analysis, traditional segmentation methods heavily rely on large-scale, high ...
Hong Zhao, Qingfeng Chen, Yao Meng, Wanjun Hu, Chenglin Yu, Zhenshan Gao, Zhaobin Chang   +6 more
doaj   +2 more sources

Multiresolution Aggregation Transformer UNet Based on Multiscale Input and Coordinate Attention for Medical Image Segmentation

Sensors, 2022
The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods
Shaolong Chen, Changzhen Qiu, Weiping Yang, Zhiyong Zhang   +3 more
doaj   +1 more source

A Hybrid Technique for Medical Image Segmentation [PDF]

Journal of Biomedicine and Biotechnology, 2012
Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR) image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter.
Nyma, Alamgir, Kang, Myeongsu, Kwon, Yung-Keun, Kim, Cheol-Hong, Kim, Jong-Myon   +4 more
openaire   +2 more sources

Sustained Therapeutic Efficacy of Intravenous Plasminogen Concentrate in Pediatric Patients With Type 1 Plasminogen Deficiency: An Analysis of Dosing Parameters and Clinical Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Type 1 plasminogen deficiency (PLGD‐1) is an ultra‐rare autosomal recessive disorder caused by variants in the PLG gene and affects approximately 1.6 individuals per million. The condition is characterized by decreased plasminogen levels and impaired function, resulting in fibrin‐rich lesions on mucous membranes throughout the body.
Charles Nakar, Karen Thibaudeau, Mary Mathias, Heather McDaniel, Madlen Reschke, Klaus Tenbrock, Joseph M. Parker, Amy Shapiro   +7 more
wiley   +1 more source

Enhancing MR image segmentation with realistic adversarial data augmentation [PDF]

, 2022
The success of neural networks on medical image segmentation tasks typically relies on large labeled datasets for model training. However, acquiring and manually labeling a large medical image set is resource-intensive, expensive, and sometimes ...
Wang, Shuo, Tarroni, Giacomo, Ouyang, Cheng, Chen, Liang, Wang, S., Bai, W., Qiu, Huaqi, Li, Z., Li, Zeju, Bai, Wenjia, Qin, Chen, Chen, Chen, Rueckert, D., Ouyang, C., Chen, L., Tarroni, G., Rueckert, Daniel, Qin, C., Qiu, H., Chen, C.   +19 more
core   +1 more source

Guidelines for Pediatric Radiotherapy Simulation: A Report From the Children's Oncology Group Radiation Oncology Discipline

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei, Stephen Mihalcik, Sujith Baliga, Young Kwok, Dana Casey, Eric Ehler, Christiane Burton, John C. Breneman, Daphne A. Haas‐Kogan, Suzanne L. Wolden, Arnold C. Paulino, Nadia N. Laack, Natia Esiashvili, Sarah Milgrom, Christine Hill‐Kayser, Thomas J. Fitzgerald, John A. Kalapurakal, Chia‐Ho Hua   +17 more
wiley   +1 more source

Segmenting medical images with limited data

Neural Networks
While computer vision has proven valuable for medical image segmentation, its application faces challenges such as limited dataset sizes and the complexity of effectively leveraging unlabeled images. To address these challenges, we present a novel semi-supervised, consistency-based approach termed the data-efficient medical segmenter (DEMS).
Zhaoshan Liu, Qiujie Lv, Chau Hung Lee, Lei Shen   +3 more
openaire   +3 more sources