Results 51 to 60 of about 13,515,348 (328)
, 2018 Uncertainty estimation methods are expected to improve the understanding and quality of computer-assisted methods used in medical applications (e.g., neurosurgical interventions, radiotherapy planning), where automated medical image segmentation is ...
Blatti-Moreno, Marcela +6 more
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Lumbar Disc Herniation Automatic Detection in Magnetic Resonance Imaging Based on Deep Learning
Frontiers in Bioengineering and Biotechnology, 2021 Background: Lumbar disc herniation (LDH) is among the most common causes of lower back pain and sciatica. The causes of LDH have not been fully elucidated but most likely involve a complex combination of mechanical and biological processes.
Jen-Yung Tsai +10 more
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Convolutional Sparse Kernel Network for Unsupervised Medical Image Analysis
, 2019 The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems.
Ahn, Euijoon +4 more
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EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation [PDF]
Computer Vision and Pattern RecognitionAn efficient and effective decoding mechanism is crucial in medical image segmentation, especially in scenarios with limited computational resources. However, these decoding mechanisms usually come with high computational costs.
M. Rahman, Mustafa Munir, R. Marculescu
semanticscholar +1 more source
A Cloud Solution for Securing Medical Image Storage
Journal of Information and Organizational Sciences, 2020 Cloud computing is an easy-to-use, affordable solution to manage and analyze medical data. Therefore, this paradigm has gained wide acceptance in the healthcare sector as a cost-efficient way for a successful Electronic Medical Records (EMR ...
Mbarek Marwan +3 more
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Predicting Cervical Cancer Outcomes: Statistics, Images, and Machine Learning
Frontiers in Artificial Intelligence, 2021 Cervical cancer is a very common and severe disease in women worldwide. Accurate prediction of its clinical outcomes will help adjust or optimize the treatment of cervical cancer and benefit the patients.
Wei Luo
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Gabor Barcodes for Medical Image Retrieval
, 2016 In recent years, advances in medical imaging have led to the emergence of massive databases, containing images from a diverse range of modalities. This has significantly heightened the need for automated annotation of the images on one side, and fast and
Banijamali, Ershad +2 more
core +1 more source
Scientific Reports, 2017 In this paper, we present an original multiple atlases level set framework (MALSF) for automatic, accurate and robust thalamus segmentation in magnetic resonance images (MRI). The contributions of the MALSF method are twofold.
Minghui Zhang +3 more
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Cache-Enabled Device to Device Networks With Contention-Based Multimedia Delivery
IEEE Access, 2017 This paper studies the performance of large-scale cache-enabled device-to-device (D2D) networks with homogeneous Poisson point process distributed mobile helpers(MHs) and user equipments (UEs). The MHs are assumed to have caching capabilities and able to
Xiaoshi Song +5 more
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Regression to Classification: Ordinal Prediction of Calcified Vessels Using Customized ResNet50
IEEE Access, 2023 A substantial percentage of women die from cardiovascular disease (CVD). Computed tomography (CT) scan helps predict/monitor CVD-related diseases. However, previous studies found relation to assessing the risk of CVD by estimating severity of breast ...
Hosna Asma-Ull, Il Dong Yun, Bo La Yun
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