For this comparison, the structural similarity (SSIM), normalized mean square error (NMSE), and Fr茅chet inception distance (FID) were calculated between the outputs of the networks and fully sampled images. The statistical significance of the performance was evaluated by assessing the interclass ...
5a), the raw data showed increasing depth-dependent degradation in resolution and contrast, which confounded our ability to discern distinct nuclei or cell boundaries on the ‘far’ side of the volume. In comparison, the multi-step procedure offered striking improvements in resolution and contrast ...
Comparison of state of art saliency methods [Cheng15]. There has been a series of benchmarking studies for the performance (accuracy and speed) of the saliency operators. The most recent [Borji15] noted the continuing progress improving both factors, and that operators designed specifically for ...
Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images—A Comparison of CycleGAN and UNIT. (2018). Nie, D. et al. Medical image synthesis with context-aware generative adversarial networks. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intel...
The objective quality assessment proved that the proposed model produces a high-quality reconstructed image with the SSIM of (89−99.8%) for the noise-like shares and (71.6−90%) for the meaningful shares. The proposed technique achieved a speedup of 800× in comparison with the sequential...
Multi-contrast magnetic resonance (MR) imaging offers diverse diagnostic information by displaying different contrast types. As shown inFig. 1, (a) clearly shows anatomical morphology, while (c) highlights the area of inflammation. Although (b) and (d) differ in visual contrast, both share simil...
(b) Simulated comparison results of five CGH methods, including superposition within phase hologram (superposition), iterative Fourier transform algorithm (IFTA), non-convex optimization (NOVO), superposition within binary hologram (random), and binary-SGD (B-SGD). The binary holographic methods only...
For quantitative comparison, we took CT slice images reconstructed from projections without geometric transformation as references, and employed mean Structural SIMilarity (SSIM) index [19] and Mutual Information(MI) [20] to assess the image quality of above results by measuring the similarity between...
Measurement in medicine: the analysis of method comparison studies J. R. Stat. Soc. Ser. D (1983) J.L. Ba et al. Layer normalization (2016) D. Bahdanau et al. Neural machine translation by jointly learning to align and translate 3rd International Conference on Learning Representations (2015...
Seven representative multimodal image fusion methods are selected for performance comparison: the dual-tree complex wavelet transform- (DTCWT-) based method [3], the curvelet transform- (CVT-) based method [4], the non-subsampled contourlet transform- (NSCT-) based method [5], the sparse repr...