Results 31 to 40 of about 12,432,034 (314)
Deep Learning in Medical Imaging [PDF]
Neurospine, 2019 The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learnable data, ANN
Mingyu Kim +6 more
doaj +1 more source
Heliyon, 2018 Purpose: A new magnetic resonance imaging (MRI) based scoring system for temporomandibular joint (TMJ) internal derangement was developed to predict disease severity and the likelihood of invasive treatment.
Roman M. Kowalchuk +4 more
doaj +1 more source
Medical Imaging and Image Processing
Technologies, 2023 Medical imaging (MI) [...]
Yudong Zhang, Zhengchao Dong
doaj +1 more source
Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session. [PDF]
, 2017 At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues.
Geis, J Raymond +2 more
core +1 more source
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises [PDF]
Proceedings of the IEEE, 2020 Since its renaissance, deep learning (DL) has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propelling us into the so-called artificial intelligence (AI) era.
S. K. Zhou +8 more
semanticscholar +1 more source
Heliyon, 2018 Purpose: To calculate the frequencies of incidental extraspinal findings and incidentally detected congenital anomalies or anatomical differences in the lumbar spine on magnetic resonance imaging (MRI) scans of intervertebral discs. Materials and methods:
Mogahid M.A. Zidan +7 more
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Fundamental issues in antenna design for microwave medical imaging applications [PDF]
, 2010 This paper surveys the development of microwave medical imaging and the fundamental challenges associated with microwave antennas design for medical imaging applications. Different microwave antennas used in medical imaging applications such as monopoles,
Busawon, Krishna +3 more
core +1 more source
Iterative annotation to ease neural network training: Specialized machine learning in medical image analysis [PDF]
, 2018 Neural networks promise to bring robust, quantitative analysis to medical fields, but adoption is limited by the technicalities of training these networks.
Ginley, Brandon +9 more
core +2 more sources
Archives of Medicine and Health Sciences, 2017 Nowadays, millions of studies perform daily around the world. Medical imaging developed throughout for >100 years. It is used to visualize the different body structure and the functional activities.
Yousif Mohamed Y. Abdallah
doaj +1 more source
Radiomics in medical imaging—“how-to” guide and critical reflection
Insights into Imaging, 2020 Radiomics is a quantitative approach to medical imaging, which aims at enhancing the existing data available to clinicians by means of advanced mathematical analysis.
J. V. van Timmeren +4 more
semanticscholar +1 more source