These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

139 related articles for article (PubMed ID: 36850877)

  • 21. Cubemap-Based Perception-Driven Blind Quality Assessment for 360-degree Images.
    Jiang H; Jiang G; Yu M; Zhang Y; Yang Y; Peng Z; Chen F; Zhang Q
    IEEE Trans Image Process; 2021; 30():2364-2377. PubMed ID: 33481711
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Comparison-Based Image Quality Assessment for Selecting Image Restoration Parameters.
    Liang H; Weller DS
    IEEE Trans Image Process; 2016 Nov; 25(11):5118-5130. PubMed ID: 27552759
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Universal blind image quality assessment metrics via natural scene statistics and multiple kernel learning.
    Gao X; Gao F; Tao D; Li X
    IEEE Trans Neural Netw Learn Syst; 2013 Dec; 24(12):2013-26. PubMed ID: 24805219
    [TBL] [Abstract][Full Text] [Related]  

  • 24. VSI: a visual saliency-induced index for perceptual image quality assessment.
    Zhang L; Shen Y; Li H
    IEEE Trans Image Process; 2014 Oct; 23(10):4270-81. PubMed ID: 25122572
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A novel algorithm for comprehensive quality assessment of clinical magnetic resonance images based on natural scene statistics in spatial domain.
    Ikushima Y; Tokurei S; Tarewaki H; Morishita J; Yabuuchi H
    Magn Reson Imaging; 2022 Oct; 92():203-211. PubMed ID: 35842195
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Blind image quality assessment: from natural scene statistics to perceptual quality.
    Moorthy AK; Bovik AC
    IEEE Trans Image Process; 2011 Dec; 20(12):3350-64. PubMed ID: 21521667
    [TBL] [Abstract][Full Text] [Related]  

  • 27. [CT image quality assessment based on prior information of pre-restored images].
    Gao Q; Zhu M; Li D; Bian Z; Ma J
    Nan Fang Yi Ke Da Xue Xue Bao; 2021 Feb; 41(2):230-237. PubMed ID: 33624596
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A ParaBoost Method to Image Quality Assessment.
    Liu TJ; Liu KH; Lin JY; Lin W; Kuo CJ
    IEEE Trans Neural Netw Learn Syst; 2017 Jan; 28(1):107-121. PubMed ID: 26685266
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Predicting the Quality of Images Compressed after Distortion in Two Steps.
    Yu X; Bampis CG; Gupta P; Bovik AC
    IEEE Trans Image Process; 2019 Jun; ():. PubMed ID: 31226076
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Blind Deep S3D Image Quality Evaluation via Local to Global Feature Aggregation.
    Heeseok Oh ; Sewoong Ahn ; Jongyoo Kim ; Sanghoon Lee
    IEEE Trans Image Process; 2017 Oct; 26(10):4923-4936. PubMed ID: 28708557
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Dynamic Receptive Field Generation for Full-Reference Image Quality Assessment.
    Kim W; Nguyen AD; Lee S; Bovik AC
    IEEE Trans Image Process; 2020 Jan; ():. PubMed ID: 31995494
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A feature-enriched completely blind image quality evaluator.
    Lin Zhang ; Lei Zhang ; Bovik AC
    IEEE Trans Image Process; 2015 Aug; 24(8):2579-91. PubMed ID: 25915960
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Oriented correlation models of distorted natural images with application to natural stereopair quality evaluation.
    Su CC; Cormack LK; Bovik AC
    IEEE Trans Image Process; 2015 May; 24(5):1685-99. PubMed ID: 25751864
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Confusing Image Quality Assessment: Toward Better Augmented Reality Experience.
    Duan H; Min X; Zhu Y; Zhai G; Yang X; Le Callet P
    IEEE Trans Image Process; 2022; 31():7206-7221. PubMed ID: 36367913
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Degraded Reference Image Quality Assessment.
    Athar S; Wang Z
    IEEE Trans Image Process; 2023 Jan; PP():. PubMed ID: 37018642
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Automatic no-reference image quality assessment.
    Li H; Hu W; Xu ZN
    Springerplus; 2016; 5(1):1097. PubMed ID: 27468398
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Modified-BRISQUE as no reference image quality assessment for structural MR images.
    Chow LS; Rajagopal H
    Magn Reson Imaging; 2017 Nov; 43():74-87. PubMed ID: 28716679
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Interobserver variability in quality assessment of magnetic resonance images.
    Obuchowicz R; Oszust M; Piorkowski A
    BMC Med Imaging; 2020 Sep; 20(1):109. PubMed ID: 32962651
    [TBL] [Abstract][Full Text] [Related]  

  • 39. ESIM: Edge Similarity for Screen Content Image Quality Assessment.
    Ni Z; Ma L; Zeng H; Chen J; Cai C; Ma KK
    IEEE Trans Image Process; 2017 Oct; 26(10):4818-4831. PubMed ID: 28644808
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A Perceptually Weighted Rank Correlation Indicator for Objective Image Quality Assessment.
    Wu Q; Li H; Meng F; Ngan KN
    IEEE Trans Image Process; 2018 Jan; ():. PubMed ID: 29994353
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.