Results 131 to 140 of about 6,998,080 (382)

Crosstalk between gut microbiota and tumor: tumors could cause gut dysbiosis and metabolic imbalance

Molecular Oncology, EarlyView.
In this research, we analyzed the relationship between gut microbiota and tumor. We discovered that both subcutaneous and metastatic tumors would alter the composition and metabolic function of gut microbiota. Meanwhile, fecal microbiota transplantation also indicated the anti‐tumor role of the gut microbiota, revealing the crosstalk between tumor and ...
Siyuan Zhang, Haimei Wen, Ying Chen, Jingya Ning, Di Hu, Yujiao Dong, Chenyu Yao, Bo Yuan, Shuanying Yang   +8 more
wiley   +1 more source

Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

Journal of digital imaging, 2019
Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we
M. H. Hesamian, W. Jia, Xiangjian He, Paul J. Kennedy   +3 more
semanticscholar   +1 more source

Plasma‐activated media selectively induces apoptotic death via an orchestrated oxidative stress pathway in high‐grade serous ovarian cancer cells

Molecular Oncology, Volume 19, Issue 4, Page 1170-1187, April 2025.
High‐grade serous ovarian cancer (HGSOC) is the most common and aggressive type of ovarian cancer with urgent need for new treatment strategies. This study evaluates plasma‐activated media (PAM) as a novel treatment for HGSOC, showing its ability to selectively induce oxidative stress and apoptosis in HGSOC cell lines, patient ascites cells and primary
Lorena T. Davies, Raja Ganesen, John Toubia, Sung‐Ha Hong, Sushil Kumar KC, Martin K. Oehler, Carmela Ricciardelli, Endre J. Szili, Nirmal Robinson, Melissa R. Pitman   +9 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

Salt & pepper noise impact on image coding based on image splitting

Communications, 2000
The paper deals with the influence of noise and two control parameters on a segmentation method for image coding. Dynamic min_max criterion and variance criterion were used as segmentation control parameters.
Milan Karpf, Boris Simak
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

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source

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

Lung image segmentation by generative adversarial networks [PDF]

arXiv, 2019
Lung image segmentation plays an important role in computer-aid pulmonary diseases diagnosis and treatment. This paper proposed a lung image segmentation method by generative adversarial networks. We employed a variety of generative adversarial networks and use its capability of image translation to perform image segmentation.
arxiv  

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