Results 61 to 70 of about 151,110 (308)

Time after time – circadian clocks through the lens of oscillator theory

FEBS Letters, EarlyView.
Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo, Carolin Ector, Hanspeter Herzel   +2 more
wiley   +1 more source

A novel framework for segmentation of small targets in medical images

Scientific Reports
Medical image segmentation represents a pivotal and intricate procedure in the domain of medical image processing and analysis. With the progression of artificial intelligence in recent years, the utilization of deep learning techniques for medical image
Longxuan Zhao, Tao Wang, Yuanbin Chen, Xinlin Zhang, Hui Tang, Fuxin Lin, Chunwang Li, Qixuan Li, Tao Tan, Dezhi Kang, Tong Tong   +10 more
doaj   +1 more source

Leveraging image complexity in macro-level neural network design for medical image segmentation [PDF]

, 2022
Tariq M. Khan, Syed S. Naqvi, Erik Meijering   +2 more
openalex   +1 more source

In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS

FEBS Letters, EarlyView.
We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka, Yuxi Liu, Stefano Maggi, Debnath Ghosal, Jue Wang, Prashant P. Damke, Stephen D. Carter, Wei Zhao, Sukhithasri Vijayrajratnam, Joseph P. Vogel, Carrie L. Shaffer, Grant J. Jensen   +11 more
wiley   +1 more source

Medical image segmentation methods overview

Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2018
This article provides an overview of the modern medical image segmentation methods. The most popular methods such as multi-atlas based methods and deep learning approach are considered in more details.
Bohdan V. Chapaliuk, Yuriy P. Zaychenko
doaj   +1 more source

Integrated genomic and proteomic profiling reveals insights into chemoradiation resistance in cervical cancer

Molecular Oncology, EarlyView.
A comprehensive genomic and proteomic analysis of cervical cancer revealed STK11 and STX3 as a potential biomarkers of chemoradiation resistance. Our study demonstrated EGFR as a therapeutic target, paving the way for precision strategies to overcome treatment failure and the DNA repair pathway as a critical mechanism of resistance.
Janani Sambath, Irene A. George, Srikanth S. Manda, Prasanth Ariyannur, Ekta R. Dhawale, Raja Sekhar Kommu, Rajan Datar, Darshana Patil, Vinita Trivedi, Manisha Singh, Kumar Prabhash, Sewanti Limaye, Richa Chauhan, Prashant Kumar   +13 more
wiley   +1 more source

DA-TransUNet: integrating spatial and channel dual attention with transformer U-net for medical image segmentation

Frontiers in Bioengineering and Biotechnology
Accurate medical image segmentation is critical for disease quantification and treatment evaluation. While traditional U-Net architectures and their transformer-integrated variants excel in automated segmentation tasks. Existing models also struggle with
Guanqun Sun, Guanqun Sun, Yizhi Pan, Weikun Kong, Zichang Xu, Jianhua Ma, Teeradaj Racharak, Le-Minh Nguyen, Junyi Xin, Junyi Xin, Junyi Xin   +10 more
doaj   +1 more source

Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation [PDF]

, 2023
Haonan Wang, Xiaomeng Li
openalex   +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

Patient‐specific pharmacogenomics demonstrates xCT as predictive therapeutic target in colon cancer with possible implications in tumor connectivity

Molecular Oncology, EarlyView.
This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker, Keren Zohar, Martin Böttcher, Thomas Wartmann, Henry Freudenstein, Maximilian Doelling, Mihailo Andric, Wenjie Shi, Or Kakhlon, Katrin Hippe, Beatrix Jahnke, Dimitrios Mougiakakos, Franziska Baenke, Daniel Stange, Roland S. Croner, Michal Linial, Ulf D. Kahlert   +16 more
wiley   +1 more source