| 1. |
- Arian, Fatemeh, et al.
(författare)
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Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms
- 2022
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Ingår i: Journal of digital imaging. - : Springer Nature. - 0897-1889 .- 1618-727X. ; 35:6, s. 1708-1718
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Tidskriftsartikel (refereegranskat)abstract
- The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had visible scars on short-axis LGE-CMR images and were candidates for CABG surgery were selected and enrolled in this study. MR imaging was performed preoperatively using a 1.5-T MRI scanner. All images were segmented by two expert radiologists (in consensus). Prior to extraction of radiomics features, all MR images were resampled to an isotropic voxel size of 1.8 × 1.8 × 1.8 mm3. Subsequently, intensities were quantized to 64 discretized gray levels and a total of 93 features were extracted. The applied algorithms included a smoothly clipped absolute deviation (SCAD)–penalized support vector machine (SVM) and the recursive partitioning (RP) algorithm as a robust classifier for binary classification in this high-dimensional and non-sparse data. All models were validated with repeated fivefold cross-validation and 10,000 bootstrapping resamples. Ten and seven features were selected with SCAD-penalized SVM and RP algorithm, respectively, for CABG responder/non-responder classification. Considering univariate analysis, the GLSZM gray-level non-uniformity-normalized feature achieved the best performance (AUC: 0.62, 95% CI: 0.53–0.76) with SCAD-penalized SVM. Regarding multivariable modeling, SCAD-penalized SVM obtained an AUC of 0.784 (95% CI: 0.64–0.92), whereas the RP algorithm achieved an AUC of 0.654 (95% CI: 0.50–0.82). In conclusion, different radiomics texture features alone or combined in multivariate analysis using machine learning algorithms provide prognostic information regarding myocardial function in patients after CABG.
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| 2. |
- Bivik Stadler, Caroline, 1986-, et al.
(författare)
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Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training
- 2021
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Ingår i: Journal of digital imaging. - : Springer-Verlag New York. - 0897-1889 .- 1618-727X. ; 34, s. 105-115
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) holds much promise for enabling highly desired imaging diagnostics improvements. One of the most limiting bottlenecks for the development of useful clinical-grade AI models is the lack of training data. One aspect is the large amount of cases needed and another is the necessity of high-quality ground truth annotation. The aim of the project was to establish and describe the construction of a database with substantial amounts of detail-annotated oncology imaging data from pathology and radiology. A specific objective was to be proactive, that is, to support undefined subsequent AI training across a wide range of tasks, such as detection, quantification, segmentation, and classification, which puts particular focus on the quality and generality of the annotations. The main outcome of this project was the database as such, with a collection of labeled image data from breast, ovary, skin, colon, skeleton, and liver. In addition, this effort also served as an exploration of best practices for further scalability of high-quality image collections, and a main contribution of the study was generic lessons learned regarding how to successfully organize efforts to construct medical imaging databases for AI training, summarized as eight guiding principles covering team, process, and execution aspects.
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| 3. |
- Cronin, Séan, et al.
(författare)
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A Qualitative Analysis of the Needs and Experiences of Hospital-based Clinicians when Accessing Medical Imaging
- 2021
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Ingår i: Journal of digital imaging. - : Springer Nature. - 0897-1889 .- 1618-727X. ; :34, s. 385-396
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Tidskriftsartikel (refereegranskat)abstract
- As digital imaging is now a common and essential tool in the clinical workflow, it is important to understand the experiences of clinicians with medical imaging systems in order to guide future development. The objective of this paper was to explore health professionals’ experiences, practices and preferences when using Picture Archiving and Communications Systems (PACS), to identify shortcomings in the existing technology and inform future developments. Semi-structured interviews are reported with 35 hospital-based healthcare professionals (3 interns, 11 senior health officers, 6 specialist registrars, 6 con- sultants, 2 clinical specialists, 5 radiographers, 1 sonographer, 1 radiation safety officer). Data collection took place between February 2019 and December 2020 and all data are analyzed thematically. A majority of clinicians report using PACS fre- quently (6+ times per day), both through dedicated PACS workstations, and through general-purpose desktop computers. Most clinicians report using basic features of PACS to view imaging and reports, and also to compare current with previous imaging, noting that they rarely use more advanced features, such as measuring. Usability is seen as a problem, including issues related to data privacy. More sustained training would help clinicians gain more value from PACS, particularly less experienced users. While the majority of clinicians report being unconcerned about sterility when accessing digital imaging, clinicians were open to the possibility of touchless operation using voice, and the ability to execute multiple commands with a single voice command would be welcomed.
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| 4. |
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| 5. |
- Dembrower, K, et al.
(författare)
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A Multi-million Mammography Image Dataset and Population-Based Screening Cohort for the Training and Evaluation of Deep Neural Networks-the Cohort of Screen-Aged Women (CSAW)
- 2020
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Ingår i: Journal of digital imaging. - : Springer Science and Business Media LLC. - 1618-727X .- 0897-1889. ; 33:2, s. 408-413
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Tidskriftsartikel (refereegranskat)abstract
- For AI researchers, access to a large and well-curated dataset is crucial. Working in the field of breast radiology, our aim was to develop a high-quality platform that can be used for evaluation of networks aiming to predict breast cancer risk, estimate mammographic sensitivity, and detect tumors. Our dataset, Cohort of Screen-Aged Women (CSAW), is a population-based cohort of all women 40 to 74 years of age invited to screening in the Stockholm region, Sweden, between 2008 and 2015. All women were invited to mammography screening every 18 to 24 months free of charge. Images were collected from the PACS of the three breast centers that completely cover the region. DICOM metadata were collected together with the images. Screening decisions and clinical outcome data were collected by linkage to the regional cancer center registers. Incident cancer cases, from one center, were pixel-level annotated by a radiologist. A separate subset for efficient evaluation of external networks was defined for the uptake area of one center. The collection and use of the dataset for the purpose of AI research has been approved by the Ethical Review Board. CSAW included 499,807 women invited to screening between 2008 and 2015 with a total of 1,182,733 completed screening examinations. Around 2 million mammography images have currently been collected, including all images for women who developed breast cancer. There were 10,582 women diagnosed with breast cancer; for 8463, it was their first breast cancer. Clinical data include biopsy-verified breast cancer diagnoses, histological origin, tumor size, lymph node status, Elston grade, and receptor status. One thousand eight hundred ninety-one images of 898 women had tumors pixel level annotated including any tumor signs in the prior negative screening mammogram. Our dataset has already been used for evaluation by several research groups. We have defined a high-volume platform for training and evaluation of deep neural networks in the domain of mammographic imaging.
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| 6. |
- Fridell, K, et al.
(författare)
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The impact of PACS on radiologists' work practice
- 2007
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Ingår i: Journal of digital imaging. - : Springer Science and Business Media LLC. - 0897-1889 .- 1618-727X. ; 20:4, s. 411-421
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Tidskriftsartikel (refereegranskat)
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| 7. |
- Geijer, H, et al.
(författare)
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Comparison of color LCD and medical-grade monochrome LCD displays in diagnostic radiology.
- 2007
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Ingår i: Journal of Digital Imaging. - : Springer Science and Business Media LLC. - 0897-1889 .- 1618-727X. ; 20:2, s. 114-121
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Tidskriftsartikel (refereegranskat)abstract
- Abstract In diagnostic radiology, medical-grade monochrome displays are usually recommended because of their higher luminance. Standard color displays can be used as a less expensive alternative, but have a lower luminance. The aim of the present study was to compare image quality for these two types of displays. Images of a CDRAD contrast-detail phantom were read by four radiologists using a 2-megapixel (MP) color display (143 cd/m2 maximum luminance) as well as 2-MP (295 cd/m2) and 3-MP monochrome displays. Thirty lumbar spine radiographs were also read by four radiologists using the color and the 2-MP monochrome display in a visual grading analysis (VGA). Very small differences were found between the displays when reading the CDRAD images. The VGA scores were −0.28 for the color and −0.25 for the monochrome display (p=0.24; NS). It thus seems possible to use color displays in diagnostic radiology provided that grayscale adjustment is used. Key words PACS - displays - digital imaging - luminance - image quality - monitor - medical imaging - liquid crystal display
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| 8. |
- Hassan, A., et al.
(författare)
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High Efficiency Video Coding (HEVC)–Based Surgical Telementoring System Using Shallow Convolutional Neural Network
- 2019
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Ingår i: Journal of digital imaging. - : Springer Science and Business Media LLC. - 0897-1889 .- 1618-727X. ; 32:6, s. 1027-1043
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Tidskriftsartikel (refereegranskat)abstract
- Surgical telementoring systems have gained lots of interest, especially in remote locations. However, bandwidth constraint has been the primary bottleneck for efficient telementoring systems. This study aims to establish an efficient surgical telementoring system, where the qualified surgeon (mentor) provides real-time guidance and technical assistance for surgical procedures to the on-spot physician (surgeon). High Efficiency Video Coding (HEVC/H.265)–based video compression has shown promising results for telementoring applications. However, there is a trade-off between the bandwidth resources required for video transmission and quality of video received by the remote surgeon. In order to efficiently compress and transmit real-time surgical videos, a hybrid lossless-lossy approach is proposed where surgical incision region is coded in high quality whereas the background region is coded in low quality based on distance from the surgical incision region. For surgical incision region extraction, state-of-the-art deep learning (DL) architectures for semantic segmentation can be used. However, the computational complexity of these architectures is high resulting in large training and inference times. For telementoring systems, encoding time is crucial; therefore, very deep architectures are not suitable for surgical incision extraction. In this study, we propose a shallow convolutional neural network (S-CNN)–based segmentation approach that consists of encoder network only for surgical region extraction. The segmentation performance of S-CNN is compared with one of the state-of-the-art image segmentation networks (SegNet), and results demonstrate the effectiveness of the proposed network. The proposed telementoring system is efficient and explicitly considers the physiological nature of the human visual system to encode the video by providing good overall visual impact in the location of surgery. The results of the proposed S-CNN-based segmentation demonstrated a pixel accuracy of 97% and a mean intersection over union accuracy of 79%. Similarly, HEVC experimental results showed that the proposed surgical region–based encoding scheme achieved an average bitrate reduction of 88.8% at high-quality settings in comparison with default full-frame HEVC encoding. The average gain in encoding performance (signal-to-noise) of the proposed algorithm is 11.5 dB in the surgical region. The bitrate saving and visual quality of the proposed optimal bit allocation scheme are compared with the mean shift segmentation–based coding scheme for fair comparison. The results show that the proposed scheme maintains high visual quality in surgical incision region along with achieving good bitrate saving. Based on comparison and results, the proposed encoding algorithm can be considered as an efficient and effective solution for surgical telementoring systems for low-bandwidth networks.
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| 9. |
- Lidén, Mats, et al.
(författare)
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Alternative user interface devices for improved navigation of CT datasets
- 2011
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Ingår i: Journal of digital imaging. - : Springer. - 0897-1889 .- 1618-727X. ; 24:1, s. 126-134
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Tidskriftsartikel (refereegranskat)abstract
- The workflow in radiology departments has changed dramatically with the transition to digital PACS, especially with the shift from tile mode to stack mode display of volumetric images. With the increasing number of images in routinely captured datasets, the standard user interface devices (UIDs) become inadequate. One basic approach to improve the navigation of the stack mode datasets is to take advantage of alternative UIDs developed for other domains, such as the computer game industry. We evaluated three UIDs both in clinical practice and in a task-based experiment. After using the devices in the daily image interpretation work, the readers reported that both of the tested alternative UIDs were better in terms of ergonomics compared to the standard mouse and that both alternatives were more efficient when reviewing large CT datasets. In the task-based experiment, one of the tested devices was faster than the standard mouse, while the other alternative was not significantly faster. One of the tested alternative devices showed a larger number of traversed images during the task. The results indicate that alternative user interface devices can improve the navigation of stack mode datasets and that radiologists should consider the potential benefits of alternatives to the standard mouse.
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| 10. |
- Lidén, Mats, 1976-, et al.
(författare)
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Multi-Reader-Multi-Split Annotation of Emphysema in Computed Tomography
- 2020
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Ingår i: Journal of digital imaging. - : Springer. - 0897-1889 .- 1618-727X. ; 33:5, s. 1185-1193
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Tidskriftsartikel (refereegranskat)abstract
- Emphysema is visible on computed tomography (CT) as low-density lesions representing the destruction of the pulmonary alveoli. To train a machine learning model on the emphysema extent in CT images, labeled image data is needed. The provision of these labels requires trained readers, who are a limited resource. The purpose of the study was to test the reading time, inter-observer reliability and validity of the multi-reader-multi-split method for acquiring CT image labels from radiologists. The approximately 500 slices of each stack of lung CT images were split into 1-cm chunks, with 17 thin axial slices per chunk. The chunks were randomly distributed to 26 readers, radiologists and radiology residents. Each chunk was given a quick score concerning emphysema type and severity in the left and right lung separately. A cohort of 102 subjects, with varying degrees of visible emphysema in the lung CT images, was selected from the SCAPIS pilot, performed in 2012 in Gothenburg, Sweden. In total, the readers created 9050 labels for 2881 chunks. Image labels were compared with regional annotations already provided at the SCAPIS pilot inclusion. The median reading time per chunk was 15 s. The inter-observer Krippendorff's alpha was 0.40 and 0.53 for emphysema type and score, respectively, and higher in the apical part than in the basal part of the lungs. The multi-split emphysema scores were generally consistent with regional annotations. In conclusion, the multi-reader-multi-split method provided reasonably valid image labels, with an estimation of the inter-observer reliability.
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| 11. |
- Lundström, Claes, et al.
(författare)
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Mapping the Landscape of Care Providers Quality Assurance Approaches for AI in Diagnostic Imaging
- 2023
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Ingår i: Journal of digital imaging. - : Springer. - 0897-1889 .- 1618-727X. ; 36, s. 379-387
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Forskningsöversikt (refereegranskat)abstract
- The discussion on artificial intelligence (AI) solutions in diagnostic imaging has matured in recent years. The potential value of AI adoption is well established, as are the potential risks associated. Much focus has, rightfully, been on regulatory certification of AI products, with the strong incentive of being an enabling step for the commercial actors. It is, however, becoming evident that regulatory approval is not enough to ensure safe and effective AI usage in the local setting. In other words, care providers need to develop and implement quality assurance (QA) approaches for AI solutions in diagnostic imaging. The domain of AI-specific QA is still in an early development phase. We contribute to this development by describing the current landscape of QA-for-AI approaches in medical imaging, with focus on radiology and pathology. We map the potential quality threats and review the existing QA approaches in relation to those threats. We propose a practical categorization of QA approaches, based on key characteristics corresponding to means, situation, and purpose. The review highlights the heterogeneity of methods and practices relevant for this domain and points to targets for future research efforts.
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| 12. |
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| 13. |
- Norrman, Eva, et al.
(författare)
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A clinical evaluation of the image quality computer program, CoCIQ
- 2005
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Ingår i: Journal of digital imaging. - : Springer Science and Business Media LLC. - 0897-1889 .- 1618-727X. ; 18:2, s. 138-144
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Tidskriftsartikel (refereegranskat)abstract
- To provide an objective way of measuring image quality, a computer program was designed that automatically analyzes the test images of a contrast-detail (CD) phantom. The program gives a quantified measurement of image quality by calculating an Image Quality Figure (IQF). The aim of this work was to evaluate the program and adjust it to clinical situations in order to find the detectable level where the program gives a reliable figure of the contrast resolution. The program was applied on a large variety of images with lumbar spine and urographic parameters, from very low to very high image qualities. It was shown that the computer program produces IQFs with small variations and there were a strong linear statistical relation between the computerized evaluation and the evaluation performed by human observers (R2 = 0.98). This method offers a fast and easy way of conducting image quality evaluations.
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| 14. |
- Qaiser, Mahmood, 1981, et al.
(författare)
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Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization
- 2015
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Ingår i: Journal of Digital Imaging. - : Springer Science and Business Media LLC. - 1618-727X .- 0897-1889. ; 28:4, s. 499-514
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present and evaluate an automatic unsupervised segmentation method, hierarchical segmenta- tion approach (HSA)–Bayesian-based adaptive mean shift (BAMS), for use in the construction of a patient-specific head conductivity model for electroencephalography (EEG) source localization. It is based on a HSA and BAMS for segmenting the tissues from multi-modal magnetic resonance (MR) head images. The evaluation of the proposed method was done both directly in terms of segmentation accuracy and indirectly in terms of source localization accuracy. The direct evaluation was performed relative to a commonly used reference method brain extraction tool (BET)–FMRIB’s automated segmenta- tion tool (FAST) and four variants of the HSA using both synthetic data and real data from ten subjects. The synthetic data includes multiple realizations of four different noise levels and several realizations of typical noise with a 20 % bias field level. The Dice index and Hausdorff distance were used to measure the segmentation accuracy. The indirect evaluation was performed relative to the reference method BET-FAST using synthetic two-dimensional (2D) multimodal magnetic resonance (MR) data with 3 % noise and synthetic EEG (generated for a prescribed source). The source localiza- tion accuracy was determined in terms of localization error and relative error of potential. The experimental results dem- onstrate the efficacy of HSA-BAMS, its robustness to noise and the bias field, and that it provides better segmentation accuracy than the reference method and variants of the HSA. They also show that it leads to a more accurate localization accuracy than the commonly used reference method and sug- gest that it has potential as a surrogate for expert manual segmentation for the EEG source localization problem.
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| 15. |
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| 16. |
- Thunberg, Per, 1968-, et al.
(författare)
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Visualization of through-plane blood flow measurements obtained from phase-contrast MRI
- 2011
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Ingår i: Journal of digital imaging. - New York, USA : Springer. - 0897-1889 .- 1618-727X. ; 24:3, s. 470-477
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Tidskriftsartikel (refereegranskat)abstract
- The purpose of this work was to develop a visualization method for concurrent observation of both velocity and magnitude data obtained from through-plane velocity measurements using phase-contrast magnetic resonance imaging. Magnitude and velocity images were combined using an opacity transfer function (OTF) where the opacity was a function of a velocity range defined by the velocity encoding (v (enc)) parameter. Measured velocities were color-coded according to a predefined color scale and then combined into one image with the gray-scale magnitude image according to the OTF. In the combined images, simultaneous information of velocity and anatomy was presented. The proposed visualization method facilitated the understanding of how the measured blood flow was related to the underlying anatomy. Results are shown where the method is used to visualize blood flow measurements in the ascending aorta and the aortic valve. Adjustments of the OTF render possible identification of the peak velocities and their localization. Forward and backward blood flow is easily shown when applying appropriate OTF and color-coding. An advantage when using the proposed method is the ability of developing standardized protocol settings since the velocity information is quantitative and not relative as is the case for data obtained from the magnitude images. The intended application of the visualization method is the analysis of common flow studies used in the diagnosis of different cardiovascular diseases.
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| 17. |
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| 18. |
- Kirkhorn, Tomas, et al.
(författare)
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Demonstration of digital radiographs by means of ink jet-printed paper copies : Pilot study
- 1992
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Ingår i: Journal of Digital Imaging. - 0897-1889. ; 5:4, s. 246-251
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Tidskriftsartikel (refereegranskat)abstract
- Different digital medical images have been printed on paper with a continuous ink jet printer, and the quality has been evaluated. The emphasis has been on digital chest radiographs from a computed radiography system. The ink jet printing technique is described as well as the handling of the image data from image source to printer. Different versions of paper prints and viewing conditions were compared to find the optimum alternative. The evaluation has been performed to maximize the quality of the paper images to make them conform with the corresponding film prints and monitor images as much as possible. The continuous ink jet technique offers high-quality prints on paper at a considerably lower cost per copy compared with the cost of a film print. With a future switch-over from diagnosing of digital images on film to diagnosing them on monitors, hard copies for demonstration purposes will occasionally be needed. This need can be filled by ink jetprinted paper copies.
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| 19. |
- Lyttkens, Kerstin, et al.
(författare)
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Evaluation of the image quality of ink-jet printed paper copies of digital chest radiographs as compared with film : A receiver operating characteristic study
- 1994
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Ingår i: Journal of Digital Imaging. - 0897-1889. ; 7:2, s. 61-68
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Tidskriftsartikel (refereegranskat)abstract
- Paper copies of digital radiographs printed with the continuous ink-jet technique have proved to be of a high enough quality for demonstration purposes. We present a study on the image quality of ink-jet printed paper copies of digital chest radiographs, based on receiver operating characteristic (ROC) analysis. Eighty-three digital radiographs of a chest phatom with simulated tumors in the mediastinum and right lund, derived from a computed radiography (CR) system were presented in two series of hard copies as ink-jet printed paper copies and as laser recorded film. The images, with a matrix of 1,760×2,140 pixels, were printed with a spatial resolution of 10 pixels/mm in the CR film recorder as well as in the ink-jet printer. On film, every image was recorded in two versions, one optimized for the mediastinum and one for the lungs. On paper, only one image was printed; this constituted an effort to optimize both the mediastinum and the lungs. The ink-jet printed images, printed on a matt coated paper, were viewed as on-sight images with reflected light. The exdaminations were reviewed by six radiologists, and ROC curves were constructed. No significant difference was found between the performance of film and that of ink-jet paper prints. Because the cost for a paper copy is only a tenth of that of film, remarkable cost reductions can be achieved by using the ink jet technique instead. Our results show that further quality studies of ink-jet printed images are worthwhile.
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