Medical image perception issues for pacs deployment

Krupiński, Elizabeth A.

doi:10.1016/s0037-198x(03)00047-6

Cited by 14 publications

(6 citation statements)

References 66 publications

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“…29,30 Some of the key display parameters that have guided the development of these displays are directly related to the perceptual requirements of radiologists, the digital nature of the images, the complex nature of anatomic structures, and lesions in the images. 31 …”

Section: Modalities Of Teleradiologymentioning

confidence: 99%

The Empirical Foundations of Teleradiology and Related Applications: A Review of the Evidence

Bashshur

Krupiński

Thrall

et al. 2016

Telemedicine and e-Health

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Introduction: Radiology was founded on a technological discovery by Wilhelm Roentgen in 1895. Teleradiology also had its roots in technology dating back to 1947 with the successful transmission of radiographic images through telephone lines. Diagnostic radiology has become the eye of medicine in terms of diagnosing and treating injury and disease. This article documents the empirical foundations of teleradiology. Methods: A selective review of the credible literature during the past decade (2005-2015) was conducted, using robust research design and adequate sample size as criteria for inclusion. Findings: The evidence regarding feasibility of teleradiology and related information technology applications has been well documented for several decades. The majority of studies focused on intermediate outcomes, as indicated by comparability between teleradiology and conventional radiology. A consistent trend of concordance between the two modalities was observed in terms of diagnostic accuracy and reliability. Additional benefits include reductions in patient transfer, rehospitalization, and length of stay.

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Section: Modalities Of Teleradiologymentioning

confidence: 99%

The Empirical Foundations of Teleradiology and Related Applications: A Review of the Evidence

Bashshur

Krupiński

Thrall

et al. 2016

Telemedicine and e-Health

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“…As the volume and complexity of medical imaging data continue to increase, radiologists are faced with progressive occupational fatigue, which takes on an additional component in the forms of eye strain and visual fatigue [12]. Radiologist eye strain and visual fatigue has been shown to adversely affect radiologist productivity and diagnostic accuracy by contributing to perceptual errors, performance errors, decreased reaction time, and even burn out [13].…”

Section: Unique Attributes Of Fatigue In Radiologymentioning

confidence: 99%

The Insidious Problem of Fatigue in Medical Imaging Practice

Reiner

Krupiński

2011

J Digit Imaging

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“…Visual clues are overlooked or misinterpreted [4][5][6]. The diagnostic process of radiologists can be improved by the use of computers [7][8][9][10][11].…”

mentioning

confidence: 99%

“…Many parameters are involved in the process of image acquisition, image processing and image display, and it is largely unknown how they should be optimised for human interpretation. Understanding the perceptual and cognitive processes involved in reading medical images will help to enhance the most useful properties of the images to improve diagnostic performance and reduce error rates [2,3,6,[14][15][16][17].…”

mentioning

confidence: 99%

Sparseness of the trabecular pattern on dental radiographs: visual assessment compared with semi-automated measurements

Geraets¹,

Lindh²,

Verheij³

2012

The British Journal of Radiology

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Objective: In diagnostic imaging; human perception is the most prominent, yet least studied, source of error. A better understanding of image perception will help to improve diagnostic performance. This study focuses on the perception of coarseness of trabecular patterns on dental radiographs. Comparison of human vision with machine vision should yield knowledge on human perception. Method: In a study on identifying osteoporotic patients, dental radiographs were made from 505 post-menopausal women aged 45-70 years. Intra-oral radiographs of the lower and upper jaws were made. Five observers graded the trabecular pattern as dense, sparse or mixed. The five gradings were combined into a single averaged observer score per jaw. The radiographs were scanned and a region of interest (ROI) was indicated on each. The ROIs were processed with image analysis software measuring 25 image features. Pearson correlation and multiple linear regression were used to compare the averaged observer score with the image features. Results: 14 image features correlated significantly with the observer judgement for both jaws. The strongest correlation was found for the average grey value in the ROI. Other features, describing that osteoporotic patients have fewer but bigger marrow spaces than controls, correlated less with the sparseness of the trabecular pattern than a rather crude measure for structure such as the average grey value. Conclusion: Human perception of the sparseness of trabecular patterns is based more on average grey values of the ROI than on geometric details within the ROI.

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Medical image perception issues for pacs deployment

Cited by 14 publications

References 66 publications

The Empirical Foundations of Teleradiology and Related Applications: A Review of the Evidence

The Empirical Foundations of Teleradiology and Related Applications: A Review of the Evidence

The Insidious Problem of Fatigue in Medical Imaging Practice

Sparseness of the trabecular pattern on dental radiographs: visual assessment compared with semi-automated measurements

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