Results 61 to 70 of about 17,459,905 (291)
Deep learning for medical image segmentation: State-of-the-art advancements and challenges
Informatics in Medicine UnlockedImage segmentation, a crucial process of dividing images into distinct parts or objects, has witnessed remarkable advancements with the emergence of deep learning (DL) techniques. The use of layers in deep neural networks, like object form recognition in
Md. Eshmam Rayed +5 more
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Medical Image Segmentation for Mobile Electronic Patient Charts Using Numerical Modeling of IoT
Journal of Applied Mathematics, 2014 Internet of Things (IoT) brings telemedicine a new chance. This enables the specialist to consult the patient’s condition despite the fact that they are in different places.
Seung-Hoon Chae +3 more
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PENERAPAN CITRA TERKOMPRESI PADA SEGMENTASI CITRA MENGGUNAKAN ALGORITMA K-MEANS
JUTEI (Jurnal Terapan Teknologi Informasi), 2018 In the development of an image not only as a documentation of events. One area that requires image processing is in the field of medicine is radiology. In radiology there is a medical image required by doctors and researchers to be processed for patient ...
Angga Wijaya Kusuma, Rossy Lydia Ellyana
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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
CapsNet for medical image segmentation
Deep Learning for Medical Image Analysis, Elsevier/Academic Press (accepted)
Minh Q. Tran +5 more
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Interactive Segmentation for Medical Images Using Spatial Modeling Mamba
InformationInteractive segmentation methods utilize user-provided positive and negative clicks to guide the model in accurately segmenting target objects. Compared to fully automatic medical image segmentation, these methods can achieve higher segmentation accuracy
Yuxin Tang +3 more
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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
FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
Medical Image Segmentation by Water Flow
, 2007 We present a new image segmentation technique based on the paradigm of water flow and apply it to medical images. The force field analogy is used to implement the major water flow attributes like water pressure, surface tension and adhesion so that the ...
Nixon, Mark, Liu, Xin
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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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