Relative Contributions of Anatomical and Quantum Noise in Signal Detection and Perception of Tomographic Digital Breast Images

Kavuri, Amar; Das, Mini

doi:10.1109/tmi.2020.2991295

Cited by 8 publications

(8 citation statements)

References 39 publications

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“…Studies have shown that a large quantity of microvascular dilations appear in metastasis lymph nodes, but they belong to dysplasia, with more damaged vessel walls and narrow lumen; nonmetastasis lymph nodes are stimulated by regulatory factors, and there will also be obvious vascular proliferation, But its vascular tissue structure is complete [19][20][21][22]. Moreover, the internal structure of metastasis lymph nodes is abnormal due to tumor cells, and a large quantity of tumor cells destroy the structure of their small blood vessels, resulting in reduced blood supply [23][24][25]. Water widely exists in various tissues and organs and iodine contrast agents are mainly distributed in diseased blood vessels.…”

Section: Discussionmentioning

confidence: 99%

[Retracted] Correlation with Spectral CT Imaging Parameters and Occult Lymph Nodes Metastases in Sufferers with Isolated Lung Adenocarcinoma

Liu

Nie

2022

Contrast Media & Molecular Imaging

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For investigating the correlation with spectral CT imaging parameters and occult lymph nodes metastasis in sufferers with isolated lung adenocarcinoma. The clinic cases data of 352 sufferers with isolated lung adenocarcinoma from January 2019 to January 2022 were assembled. In line with whether the sufferers had occult lymph nodes metastasis, they were taken as a part in the metastasis group (n = 172) and the nonmetastasis group. All sufferers were scanned by spectral CT with a dual-phase contrast-enhanced method, and the recording of spectral CT imaging parameters in arteriovenous phase, iodine concentration (IC), water concentration (WC), the slope rate of the spectral HU curve (λHU), the normalized iodine concentration(NIC), the normalized water concentration(NWC), the normalized effective atomic number (Neff-Z)], and receiver operating characteristic (ROC) were employed to analyze the spectral CT imaging parameters of the arteriovenous phase. Evaluation of occult lymph nodes metastases in sufferers with isolated lung adenocarcinoma. The IC, NIC, λHU, and Neff-Z in the arteriovenous phase spectral CT imaging parameters of the metastasis group were obviously smaller than that of the nonmetastasis group, and the discrepancies were statistically obvious ( P < 0.05 ). The results of ROC curve analysis manifested that the area under the curve (AUC) of λHU, IC, NIC, and Neff-Z in the CT parameters of the arterial phase were 0. 840 (95%CI : 0. 796–0.883), 0.763 (95% CI : 0.708–0.818), 0.918 (95% CI : 0.888–0.948), 0.778 (95% CI : 0.731–0.826). The AUCs of λHU, IC, NIC, and Neff-Z in the venous phase spectral CT parameters were 0.909 (95% CI : 0.877–0.941), 0.837 (95% CI : 0.792–0.881), and 0.980 (95% CI : 0.968–0.968), respectively. 0.993), 0.792 (95% CI : 0.742∼0.842). Spectral CT imaging parameters have a certain value in evaluating occult lymph nodes metastasis in sufferers with isolated lung adenocarcinoma, which is helpful for doctors to judge the lymph nodes metastasis in sufferers with this disease before surgery.

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Section: Discussionmentioning

confidence: 99%

[Retracted] Correlation with Spectral CT Imaging Parameters and Occult Lymph Nodes Metastases in Sufferers with Isolated Lung Adenocarcinoma

Liu

Nie

2022

Contrast Media & Molecular Imaging

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“…The filter used in this study is a space-variant version applied on the DBT projections. The details of these can be also seen in our recent work 51,52 . As described above, we applied the filter to the noisy projections to generate a set of 1152 filtered images.…”

Section: Methods and Resultsmentioning

confidence: 64%

On the correlation between second order texture features and human observer detection performance in digital images

Nisbett

Kavuri

Das

2020

Sci Rep

Self Cite

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image texture, the relative spatial arrangement of intensity values in an image, encodes valuable information about the scene. As it stands, much of this potential information remains untapped. Understanding how to decipher textural details would afford another method of extracting knowledge of the physical world from images. In this work, we attempt to bridge the gap in research between quantitative texture analysis and the visual perception of textures. the impact of changes in image texture on human observer's ability to perform signal detection and localization tasks in complex digital images is not understood. We examine this critical question by studying task-based human observer performance in detecting and localizing signals in tomographic breast images. We have also investigated how these changes impact the formation of second-order image texture. We used digital breast tomosynthesis (DBT) an FDA approved tomographic X-ray breast imaging method as the modality of choice to show our preliminary results. our human observer studies involve localization ROC (LROC) studies for low contrast mass detection in DBT. Simulated images are used as they offer the benefit of known ground truth. Our results prove that changes in system geometry or processing leads to changes in image texture magnitudes. We show that the variations in several well-known texture features estimated in digital images correlate with human observer detection-localization performance for signals embedded in them. This insight can allow efficient and practical techniques to identify the best imaging system design and algorithms or filtering tools by examining the changes in these texture features. This concept linking texture feature estimates and task based image quality assessment can be extended to several other imaging modalities and applications as well. it can also offer feedback in system and algorithm designs with a goal to improve perceptual benefits. Broader impact can be in wide array of areas including imaging system design, image processing, data science, machine learning, computer vision, perceptual and vision science. our results also point to the caution that must be exercised in using these texture features as image-based radiomic features or as predictive markers for risk assessment as they are sensitive to system or image processing changes.

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“…The first method for assessing the effect of correlated noise on the quality of digital mammography was to calculate objective image quality metrics commonly used in the literature. [10][11][12][13][14][15] We chose the Structural Similarity Index Measure (SSIM), cross-correlation component of the multiscale SSIM (R*), 12 Peak Signal-to-Noise Ratio (PSNR), Quality Index based on Local Variance (QILV), Normalized Anisotropic Quality Index (NAQI), 10 Mean Normalized Squared Error (MNSE) 11 and Cumulative Probability of Blur Detection (CPBD) 15 to evaluate both sets, since these spatial metrics are widely applied to evaluate medical images. 10 We also calculated the Haar wavelet-based Perceptual Similarity Index (HaarPSI), 13 as a wavelet-based metric.…”

Section: Objective Quality Assessmentmentioning

confidence: 99%

“…For a frequency-based analysis, we measured the power spectrum (PS) to compare the sets in terms of spectral similarity, since the PS can describe the strength of variations in an image at different spatial frequencies. 14 The above metrics were calculated on the raw data (DICOM 'for processing' tag), within the segmented breast, and the resulting index for each objective metric was calculated from the average of the evaluated image set.…”

Section: Objective Quality Assessmentmentioning

confidence: 99%

Assessing the impact of correlated noise in digital mammography: a virtual clinical trial

Soares¹,

Brandão

Borges³

et al. 2023

Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment

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In digital mammography, the physics of the acquisition system and post-processing algorithms can cause image noise to be spatially correlated. Noise correlation is characterized by non-constant noise power spectral density and can negatively affect image quality. Although the literature explores ways to quantify the frequency dependence of noise in digital mammography, there is still a lack of studies that explore the effect of this phenomenon on clinical tasks. Thus, the aim of this work is to evaluate the impact of noise correlation on the quality of digital mammography and the detectability of lesions using a virtual clinical trial (VCT) tool. Considering the radiographic factors of a standard full-dose acquisition, VCT was used to generate two sets of images: one containing mammograms corrupted with correlated noise and the other with uncorrelated (white) noise. Clusters of five to seven microcalcifications of different sizes and shapes were computationally inserted into the images at regions of dense tissue. We then designed a human observer study to investigate performance on a clinical task of locating microcalcifications on digital mammography from both image sets. In addition, nine objective image quality metrics were calculated on mammograms. The results obtained with four medical physicists showed that the average performance in localization was 72% for images with correlated noise and 95% with uncorrelated noise. Thus, our results suggest that correlated noise promotes a greater reduction in the conspicuity of subtle microcalcifications than uncorrelated noise. Furthermore, only four of the nine objective quality metrics calculated in this work were consistent with the results of the human observer study, highlighting the importance of using appropriate metrics to assess the quality of corrupted images with correlated noise. The source code for our framework is publicly available at

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Relative Contributions of Anatomical and Quantum Noise in Signal Detection and Perception of Tomographic Digital Breast Images

Cited by 8 publications

References 39 publications

[Retracted] Correlation with Spectral CT Imaging Parameters and Occult Lymph Nodes Metastases in Sufferers with Isolated Lung Adenocarcinoma

[Retracted] Correlation with Spectral CT Imaging Parameters and Occult Lymph Nodes Metastases in Sufferers with Isolated Lung Adenocarcinoma

On the correlation between second order texture features and human observer detection performance in digital images

Assessing the impact of correlated noise in digital mammography: a virtual clinical trial

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