A biologically-based algorithm for companding computerized tomography (CT) images

Cohen-Duwek, Hadar; Spitzer, Hedva; Weitzen, Rony; Apter, Sara

doi:10.1016/j.compbiomed.2011.03.015

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…They investigated the usefulness of the technique in a clinical setting and were able to show a significant reduction in interpretation time for the combined window setting, but overall accuracy was insufficient for replacement of the conventional window settings by the new combined window [5]. A new technique of companding CT-images was published in 2011 by Cohen-Duwek et al, with limited clinical data [6]. More recently, Mandell et al investigated feasibility of a ‘blended’ CT-window in patients with thoracic trauma [7].…”

Section: Discussionmentioning

confidence: 99%

“…This idea is not new. Postprocessing techniques such as histogram equalization [3], nonlinear CT windows [4], adaptive histogram equalization [5] companding [6] and blending [1, 7], have been investigated in the past. In contradistinction, the AIO-window is a newly developed image processing technique, derived from a commercial multiscale enhancement software for digital X-rays (MUSICA™, Agfa Medical Imaging).…”

Section: Introductionmentioning

confidence: 99%

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Lesion measurement on a combined “all-in-one” window for chest CT: effect on intra- and interobserver variability

et al. 2019

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PurposeA newly developed image processing technique fuses conventional windows into a single ‘All-In-One’ (AIO) window. This study aims to evaluate variability of CT measurement of lesions in thoracic oncology patients on this novel AIO-window.MethodsSix radiologists with different levels of expertise measured 368 lesions of various size, origin and sharpness. All lesions were measured twice on the AIO-window and twice on the conventional window settings. Intraclass correlation coefficients and Bland-Altman plots were used to assess intra- and interobserver variability.ResultsOverall intra-observer agreement for lesion diameters on the AIO-window and conventional window settings was 0.986 (95% Confidence interval (CI): 0.983–0.989) and 0.991 (95% CI 0.989–0.993) respectively. For interobserver agreement this was 0.982 (95% CI 0.979–0.985) (AIO) and 0.979 (95% CI 0.957–0.982) (conventional). For both the AIO and conventional windows, intra- and interobserver agreement were dependent on size, sharpness and reader experience. Measurement variability decreased with increasing lesion size. Regarding sharpness, inter- and intra-observer agreement ranged from 0.986–0.989 (AIO) and 0.985–0.992 (conventional) for well-defined lesions and from 0.978–0.983 (AIO) and 0.974–0.991 (conventional) for ill-defined lesions.ConclusionsLesion diameters were consistently smaller on the AIO-window compared to conventional window settings. Overall intra- and interobserver variability rates were similar for the AIO-window and conventional window settings. We conclude that the AIO-window offers a reliable and reproducible alternative for measurement of thoracic lesions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lesion measurement on a combined “all-in-one” window for chest CT: effect on intra- and interobserver variability

et al. 2019

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“…Specialized protocols are developed for diagnosing specific pathologies. However, the need for image post-processing in order to obtain better local contrast [6][7][8] dates back decades.…”

Section: Introductionmentioning

confidence: 99%

A Weighted Histogram-Based Tone Mapping Algorithm for CT Images

et al. 2018

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Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared to eight popular tone mapping operators.

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Comparison of detection of trauma-related injuries using combined “all-in-one” fused images and conventionally reconstructed images in acute trauma CT

et al. 2022

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A biologically-based algorithm for companding computerized tomography (CT) images

Cited by 9 publications

References 20 publications

Lesion measurement on a combined “all-in-one” window for chest CT: effect on intra- and interobserver variability

Lesion measurement on a combined “all-in-one” window for chest CT: effect on intra- and interobserver variability

A Weighted Histogram-Based Tone Mapping Algorithm for CT Images

Comparison of detection of trauma-related injuries using combined “all-in-one” fused images and conventionally reconstructed images in acute trauma CT

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