Assessment of the diagnostic quality of the digital display monitors at the dental clinics of a university hospital

Hameed, Muhammad Hasan; Umer, Fahad; Khan, Farhan Raza; Pirani, Saleem; Yusuf, Mohammad

doi:10.1016/j.imu.2018.02.002

Cited by 3 publications

(2 citation statements)

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“…The ubiquity of advancements in imaging has brought significant attention of medical specialists due to the role of the quality of displayed content in diagnosis [ 1 , 2 , 3 ]. The quality of Magnetic Resonance (MR) images depends on used hardware parts, software techniques, as well as human errors involving patient noncompliance or operator mistakes [ 4 , 5 , 6 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Magnetic Resonance Image Quality Assessment by Using Non-Maximum Suppression and Entropy Analysis

Obuchowicz

Oszust

Bielecka

et al. 2020

Entropy

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An investigation of diseases using magnetic resonance (MR) imaging requires automatic image quality assessment methods able to exclude low-quality scans. Such methods can be also employed for an optimization of parameters of imaging systems or evaluation of image processing algorithms. Therefore, in this paper, a novel blind image quality assessment (BIQA) method for the evaluation of MR images is introduced. It is observed that the result of filtering using non-maximum suppression (NMS) strongly depends on the perceptual quality of an input image. Hence, in the method, the image is first processed by the NMS with various levels of acceptable local intensity difference. Then, the quality is efficiently expressed by the entropy of a sequence of extrema numbers obtained with the thresholded NMS. The proposed BIQA approach is compared with ten state-of-the-art techniques on a dataset containing MR images and subjective scores provided by 31 experienced radiologists. The Pearson, Spearman, Kendall correlation coefficients and root mean square error for the method assessing images in the dataset were 0.6741, 0.3540, 0.2428, and 0.5375, respectively. The extensive experimental evaluation of the BIQA methods reveals that the introduced measure outperforms related techniques by a large margin as it correlates better with human scores.

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Section: Introductionmentioning

confidence: 99%

Magnetic Resonance Image Quality Assessment by Using Non-Maximum Suppression and Entropy Analysis

Obuchowicz

Oszust

Bielecka

et al. 2020

Entropy

View full text Add to dashboard Cite

show abstract

“…Monitors used in radiology for diagnosis should have a good overall grayscale presentation and a high luminance profile. This is especially important for the detection of subtle radiolucencies or radiopacities, such as in the detection of caries and periapical lesions ( 5 ). Despite these recommendations, a recent study evaluated the influence of different computer displays, horizontal viewing angles, and ambient lighting conditions in the diagnosis of non-cavitated proximal caries lesions and revealed that none of these factors influenced this diagnostic task ( 6 ).…”

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confidence: 99%