Results 111 to 120 of about 933,512 (366)

A Novel Framework for Accurate Segmentation of Brain Tumor Using Multiple Kernel Fuzzy Clustering Algorithm

open access: yesApplied Medical Informatics, 2020
Magnetic Resonance Imaging (MRI) is one of the prominent imaging techniques for assessment of brain tumor progression. Intensity inhomogeneity, partial volume effect (PVE) and diverse nature of tumor render a challenging task for automatic segmentation ...
Praylin Selva Blessy SELVARAJ ASSLEY   +1 more
doaj  

Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer

open access: yesMolecular Oncology, EarlyView.
This study employed targeted metabolomic profiling to identify 302 distinct metabolites present in platelet‐rich plasma (PRP), revealing aberrant metabolic profiles amongst individuals diagnosed with colorectal cancer (CRC). Compared to carcinoembryonic antigen (CEA) and cancer antigen 19‐9 (CA199), our metabolite panel showed improved sensitivity ...
Zuojian Hu   +7 more
wiley   +1 more source

A New Approach for Realistic 3D Reconstruction of Planar Surfaces from Laser Scanning Data and Imagery Collected Onboard Modern Low-Cost Aerial Mapping Systems

open access: yesRemote Sensing, 2017
Over the past few years, accurate 3D surface reconstruction using remotely-sensed data has been recognized as a prerequisite for different mapping, modelling, and monitoring applications.
Zahra Lari, Naser El-Sheimy, Ayman Habib
doaj   +1 more source

Hemodynamics of anterior communicating artery aneurysms using combined imaging of the anterior circulation

open access: yesCurrent Directions in Biomedical Engineering, 2021
Intracranial aneurysms at the anterior communicating artery (AcomA) are associated with a higher rupture risk and a more challenging therapy since they are supplied with blood from both sides of the anterior vasculature.
Saalfeld Sylvia   +3 more
doaj   +1 more source

Learning Panoptic Segmentation from Instance Contours [PDF]

open access: yesarXiv, 2020
Panoptic Segmentation aims to provide an understanding of background (stuff) and instances of objects (things) at a pixel level. It combines the separate tasks of semantic segmentation (pixel level classification) and instance segmentation to build a single unified scene understanding task.
arxiv  

TRPM4 contributes to cell death in prostate cancer tumor spheroids, and to extravasation and metastasis in a zebrafish xenograft model system

open access: yesMolecular Oncology, EarlyView.
Transient receptor potential melastatin‐4 (TRPM4) is overexpressed in prostate cancer (PCa). Knockout of TRPM4 resulted in reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids.
Florian Bochen   +6 more
wiley   +1 more source

Profiling visitors at the strawberry festival at the Redberry farm in George, South Africa. [PDF]

open access: yesAfrican Journal of Hospitality, Tourism and Leisure, 2018
The identification and appropriate understanding of customers by tourism marketers and event organisers is significant for market segmentation.
Dr T. Ramukumba
doaj  

Image-based Blood Flow Analysis of Popliteal Artery Aneurysms – an Interdisciplinary Pilot Study

open access: yesCurrent Directions in Biomedical Engineering, 2021
Although popliteal artery aneurysms (PAAs) are the most frequent aneurysms in the lower peripheral arteries, research has not covered the potential of blood flow analysis of these pathologies yet.
Saalfeld Sylvia   +4 more
doaj   +1 more source

SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model [PDF]

open access: yesarXiv, 2023
Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system. Users need to be informed/alerted whenever an AI system generates unreliable/incorrect predictions. With the introduction of the Segment Anything Model (SAM), a general foundation segmentation model, new research opportunities emerged in ...
arxiv  

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

open access: yesIEEE Transactions on Medical Imaging, 2001
The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images.
Yongyue Zhang   +2 more
semanticscholar   +1 more source

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