Results 71 to 80 of about 16,791,752 (293)
AutoSegNet: An Automated Neural Network for Image Segmentation
IEEE Access, 2020 Neural Architecture Search (NAS) has drawn significant attention as a tool for automatically constructing deep neural networks. The generated neural networks are mainly applied for image classification, and natural language processing. However, there are
Zhimin Xu +4 more
doaj +1 more source
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
FEBS Letters, EarlyView.Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
A novel framework for segmentation of small targets in medical images
Scientific ReportsMedical 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 +10 more
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Research on Medical Image Segmentation Based on SAM and Its Future Prospects
BioengineeringThe rapid advancement of prompt-based models in natural language processing and image generation has revolutionized the field of image segmentation.
Kangxu Fan +5 more
doaj +1 more source
An Efficient Rapid Region Growing Algorithm for Medical Image Segmentation
, 2023 Medical imaging is an important diagnostic tool, so that medical personnel can more easily understand the patient's condition. Therefore, this study will combine medical knowledge and computer science to detect and capture the various features.
Chen*, Chii-Jen
core +1 more source
Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation
FEBS Letters, EarlyView.Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang +2 more
wiley +1 more source
Lost in the Vaso‐Occlusion: A Patient's Abdominal Pain Returns With a Vengeance
Pediatric Blood &Cancer, EarlyView.
Dunia Hatabah +5 more
wiley +1 more source
Liver organoids: modelling complexity in homeostasis and disease
FEBS Letters, EarlyView.Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
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
Correction Learning for Medical Image Segmentation [PDF]
IEEE Access, 2019 Breast tumor segmentation is useful to diagnose breast cancer. However, challenges, such as intensity inhomogeneity and shadowing artifacts arise in this task. To address these two issues, this paper proposes a robust ultrasound image segmentation method based on correction learning. At first, a novel idea of correction learning is introduced.
Guang Zhang +7 more
openaire +3 more sources