Results 51 to 60 of about 169,019 (308)

Clinical and Biological Features of Response in Resistant Neuroblastoma to 131I‐Metaiodobenzylguanidine Radiotherapy in the Anti‐GD2 Immunotherapy Era

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background 131I‐metaiodobenzylguanidine (131I‐MIBG) radiotherapy is a key treatment for relapsed and refractory (R/R) neuroblastoma (NB). Patients with R/R disease treated in the modern era are increasingly exposed to anti‐GD2 immunotherapy, which exerts selective pressure and may modify both tumor cell state and microenvironment.
Benjamin J. Lerman, Katherine K. Matthay, Fabienne Hollinger, Catriona Black, Ann A. Lazar, Miguel Pampaloni, Steven G. DuBois, Kieuhoa T. Vo   +7 more
wiley   +1 more source

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

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

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

Therapeutic Apheresis for Intravenous Methylprednisolone‐Refractory Neuromyelitis Optica Spectrum Disorder: Clinical and Radiological Outcomes in a Single‐Center Case Series

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing autoimmune disease of the central nervous system. High‐dose intravenous methylprednisolone (IVMP) is the standard first‐line therapy for acute attacks, although some patients remain refractory.
Wataru Horiguchi, Daisuke Katagiri, Takeyuki Watadani, Shunichi Matsuda, Hiroshi Kaneko, Noritoshi Arai   +5 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

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 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

The (Glg)ABCs of cyanobacteria: modelling of glycogen synthesis and functional divergence of glycogen synthases in Synechocystis sp. PCC 6803

FEBS Letters, EarlyView.
We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee, Dimitrios Bekiari, Sofia Doello, Karl Forchhammer   +3 more
wiley   +1 more source

A review of medical ocular image segmentation

Virtual Reality & Intelligent Hardware
Deep learning has been extensively applied to medical image segmentation, resulting in significant advancements in the field of deep neural networks for medical image segmentation since the notable success of U-Net in 2015.
Lai WEI, Menghan HU
doaj   +1 more source