Results 201 to 210 of about 1,366,129 (269)
Role of artificial intelligence in medical image analysis. [PDF]
Wang L +13 more
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Segment anything model guided dual-mask framework for anatomically faithful medical image translation. [PDF]
Lee H, Jo Y, Hong I, Kim J, Park S.
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A hybrid CNN-Transformer network integrating multiscale spatially detailed features for medical image segmentation. [PDF]
Li B, Zhou W, Li H.
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Development and evaluation of a multistage transfer learning framework for robust medical image analysis. [PDF]
Ayana G +4 more
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A progressive fusion network for endoscopic medical image segmentation. [PDF]
Fu L, Li Z, Xu C, Chen Y.
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Segmentation of medical images
Image and Vision Computing, 1993Abstract Segmentation and labelling remains the weakest step in many medical vision applications. This paper illustrates an approach based on generic modules which are designed to solve typical problems encountered in various applications, and which are controllable through adaptation of their parameters.
Rudi Deklerck +2 more
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Media images and medical images
Social Science & Medicine (1967), 1975Abstract The study sought to examine the image of women portrayed in drug advertisements and how that image contrasts with the portrayal of men. Special attention was given to advertisements for mood-modifying drugs since women are the majority of users of such drugs. Content analysis was performed on nearly 500 drug advertisements in a sample drawn
Andrea Mant, Dorothy Broom Darroch
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AIP Conference Proceedings, 2012
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact
Siddiqi, A. H. +3 more
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The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact
Siddiqi, A. H. +3 more
openaire +3 more sources

