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Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
Nanocrystals for Deep-Tissue In Vivo Luminescence Imaging in the Near-Infrared Region
In vivo imaging technologies have emerged as a powerful tool for both fundamental
research and clinical practice. In particular, luminescence imaging in the tissue-transparent …
research and clinical practice. In particular, luminescence imaging in the tissue-transparent …
A fully integrated wearable ultrasound system to monitor deep tissues in moving subjects
Recent advances in wearable ultrasound technologies have demonstrated the potential for
hands-free data acquisition, but technical barriers remain as these probes require wire …
hands-free data acquisition, but technical barriers remain as these probes require wire …
Transformers in medical imaging: A survey
Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …
successfully applied to several computer vision problems, achieving state-of-the-art results …
Ultrasound-based micro-/nanosystems for biomedical applications
Due to the intrinsic non-invasive nature, cost-effectiveness, high safety, and real-time
capabilities, besides diagnostic imaging, ultrasound as a typical mechanical wave has been …
capabilities, besides diagnostic imaging, ultrasound as a typical mechanical wave has been …
Deep learning for classification and localization of COVID-19 markers in point-of-care lung ultrasound
Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent
COVID-19 pandemic, some works have started to investigate DL-based solutions for the …
COVID-19 pandemic, some works have started to investigate DL-based solutions for the …
Advancements in deep learning for B-mode ultrasound segmentation: a comprehensive review
Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US
image segmentation is crucial in image analysis. Recently, deep learning-based methods …
image segmentation is crucial in image analysis. Recently, deep learning-based methods …
Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
A review on deep-learning algorithms for fetal ultrasound-image analysis
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …
fetal images. A number of survey papers in the field is today available, but most of them are …