Results 91 to 100 of about 931,369 (334)

Multiplex single‐cell profiling of putative cancer stem cell markers ALDH1, SOX9, SOX2, CD44, CD133 and CD15 in endometrial cancer

Molecular Oncology, EarlyView.
Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien, Marta E. Hjelmeland, Hege F. Berg, Rose M. Gold, Kathrine Woie, Lars A. Akslen, Ingfrid S. Haldorsen, Camilla Krakstad   +7 more
wiley   +1 more source

An unsupervised strategy for biomedical image segmentation

Advances and Applications in Bioinformatics and Chemistry, 2010
Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN ...
Roberto Rodríguez, Rubén Hernández   +1 more
doaj  

IMAGE SEGMENTATION USING MULTIWAVELET TRANSFORM

Journal of Engineering, 2010
This paper presents region growing image segmentation method which unifies region and boundary information. Several studies shown that segmentation based on image features can improve the accuracy of the interpretation.
Manal Fadel Younis
doaj   +1 more source

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

Molecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Integrating Semi-supervised and Supervised Learning Methods for Label Fusion in Multi-Atlas Based Image Segmentation

Frontiers in Neuroinformatics, 2018
A novel label fusion method for multi-atlas based image segmentation method is developed by integrating semi-supervised and supervised machine learning techniques.
Qiang Zheng, Qiang Zheng, Qiang Zheng, Yihong Wu, Yong Fan   +4 more
doaj   +1 more source

Image segmentation by iterative parallel region growing with application to data compression and image analysis [PDF]

Image segmentation can be a key step in data compression and image analysis. However, the segmentation results produced by most previous approaches to region growing are suspect because they depend on the order in which portions of the image are ...
Tilton, James C.
core   +1 more source

Highly multiplexed digital PCR assay for simultaneous quantification of variant allele frequencies and copy number alterations of KRAS and GNAS in pancreatic cancer precursors

Molecular Oncology, EarlyView.
Combining melting curve analysis enhances the multiplexing capability of digital PCR. Here, we developed a 14‐plex assay to simultaneously measure single nucleotide mutations and amplifications of KRAS and GNAS, which are common driver genes in pancreatic cancer precursors. This assay accurately quantified variant allele frequencies in clinical samples
Junko Tanaka, Tatsuo Nakagawa, Yusuke Ono, Yoshio Kamura, Takeshi Ishida, Hidemasa Kawabata, Kenji Takahashi, Hiroki Sato, Andrew S. Liss, Yusuke Mizukami, Takahide Yokoi   +10 more
wiley   +1 more source

Semisupervised Soft Mumford-Shah Model for MRI Brain Image Segmentation

Applied Computational Intelligence and Soft Computing, 2016
One challenge of unsupervised MRI brain image segmentation is the central gray matter due to the faint contrast with respect to the surrounding white matter.
Hong-Yuan Wang, Fuhua Chen
doaj   +1 more source

MORPHOLOGICAL SEGMENTATION OF HYPERSPECTRAL IMAGES

Image Analysis & Stereology, 2011
The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain the markers and a vectorial gradient which gives the spatial information. Several alternative gradients are adapted
Noyel, Guillaume, Angulo, Jesus, Jeulin, Dominique   +2 more
openaire   +8 more sources

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source