AIMC Topic: Image Processing, Computer-Assisted

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[Deep learning approach for automatic segmentation of auricular acupoint divisions].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The automatic segmentation of auricular acupoint divisions is the basis for realizing intelligent auricular acupoint therapy. However, due to the large number of ear acupuncture areas and the lack of clear boundary, existing solutions face challenges...

Artificial Intelligence: A Game-Changer for Mental Health Care.

Cyberpsychology, behavior and social networking
Starting from the escalating global burden of mental health disorders, exacerbated by the COVID-19 pandemic, the article examines the potential of artificial intelligence (AI) to revolutionize mental health care. With nearly one in five adults facing...

MyoV: a deep learning-based tool for the automated quantification of muscle fibers.

Briefings in bioinformatics
Accurate approaches for quantifying muscle fibers are essential in biomedical research and meat production. In this study, we address the limitations of existing approaches for hematoxylin and eosin-stained muscle fibers by manually and semiautomatic...

Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN.

Mathematical biosciences and engineering : MBE
An automatic recognizing system of white blood cells can assist hematologists in the diagnosis of many diseases, where accuracy and efficiency are paramount for computer-based systems. In this paper, we presented a new image processing system to reco...

Artificial intelligence-based image analysis in clinical testing: lessons from cervical cancer screening.

Journal of the National Cancer Institute
Novel screening and diagnostic tests based on artificial intelligence (AI) image recognition algorithms are proliferating. Some initial reports claim outstanding accuracy followed by disappointing lack of confirmation, including our own early work on...

[Mitigating metal artifacts from cobalt-chromium alloy crowns in cone-beam CT images through deep learning techniques].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
To develop and evaluate metal artifact removal systems (MARS) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images. A full-mouth standard model (60 mm×75 ...

Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a noninvasive tool for skin barrier assessment.

GigaScience
BACKGROUND: Corneocyte surface nanoscale topography (nanotexture) has recently emerged as a potential biomarker for inflammatory skin diseases, such as atopic dermatitis (AD). This assessment method involves quantifying circular nano-size objects (CN...

"UDE DIATOMS in the Wild 2024": a new image dataset of freshwater diatoms for training deep learning models.

GigaScience
BACKGROUND: Diatoms are microalgae with finely ornamented microscopic silica shells. Their taxonomic identification by light microscopy is routinely used as part of community ecological research as well as ecological status assessment of aquatic ecos...

Artificial intelligence generated content (AIGC) in medicine: A narrative review.

Mathematical biosciences and engineering : MBE
Recently, artificial intelligence generated content (AIGC) has been receiving increased attention and is growing exponentially. AIGC is generated based on the intentional information extracted from human-provided instructions by generative artificial...