| 1. |
- Hagberg, Eva, et al.
(författare)
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Semi-supervised learning with natural language processing for right ventricle classification in echocardiography—a scalable approach
- 2022
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Ingår i: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825 .- 1879-0534. ; 143
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Tidskriftsartikel (refereegranskat)abstract
- We created a deep learning model, trained on text classified by natural language processing (NLP), to assess right ventricular (RV) size and function from echocardiographic images. We included 12,684 examinations with corresponding written reports for text classification. After manual annotation of 1489 reports, we trained an NLP model to classify the remaining 10,651 reports. A view classifier was developed to select the 4-chamber or RV-focused view from an echocardiographic examination (n = 539). The final models were two image classification models trained on the predicted labels from the combined manual annotation and NLP models and the corresponding echocardiographic view to assess RV function (training set n = 11,008) and size (training set n = 9951. The text classifier identified impaired RV function with 99% sensitivity and 98% specificity and RV enlargement with 98% sensitivity and 98% specificity. The view classification model identified the 4-chamber view with 92% accuracy and the RV-focused view with 73% accuracy. The image classification models identified impaired RV function with 93% sensitivity and 72% specificity and an enlarged RV with 80% sensitivity and 85% specificity; agreement with the written reports was substantial (both κ = 0.65). Our findings show that models for automatic image assessment can be trained to classify RV size and function by using model-annotated data from written echocardiography reports. This pipeline for auto-annotation of the echocardiographic images, using a NLP model with medical reports as input, can be used to train an image-assessment model without manual annotation of images and enables fast and inexpensive expansion of the training dataset when needed. © 2022
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| 2. |
- Ahlander, Britt-Marie, 1954-, et al.
(författare)
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An echo-planar imaging sequence is superior to a steady-state free precession sequence for visual as well as quantitative assessment of cardiac magnetic resonance stress perfusion
- 2017
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Ingår i: Clinical Physiology and Functional Imaging. - : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 37:1, s. 52-61
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: To assess myocardial perfusion, steady-state free precession cardiac magnetic resonance (SSFP, CMR) was compared with gradient-echo-echo-planar imaging (GRE-EPI) using myocardial perfusion scintigraphy (MPS) as reference.METHODS: Cardiac magnetic resonance perfusion was recorded in 30 patients with SSFP and in another 30 patients with GRE-EPI. Timing and extent of inflow delay to the myocardium was visually assessed. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated. Myocardial scar was visualized with a phase-sensitive inversion recovery sequence (PSIR). All scar positive segments were considered pathologic. In MPS, stress and rest images were used as in clinical reporting. The CMR contrast wash-in slope was calculated and compared with the stress score from the MPS examination. CMR scar, CMR perfusion and MPS were assessed separately by one expert for each method who was blinded to other aspects of the study.RESULTS: Visual assessment of CMR had a sensitivity for the detection of an abnormal MPS at 78% (SSFP) versus 91% (GRE-EPI) and a specificity of 58% (SSFP) versus 84% (GRE-EPI). Kappa statistics for SSFP and MPS was 0·29, for GRE-EPI and MPS 0·72. The ANOVA of CMR perfusion slopes for all segments versus MPS score (four levels based on MPS) had correlation r = 0·64 (SSFP) and r = 0·96 (GRE-EPI). SNR was for normal segments 35·63 ± 11·80 (SSFP) and 17·98 ± 8·31 (GRE-EPI), while CNR was 28·79 ± 10·43 (SSFP) and 13·06 ± 7·61 (GRE-EPI).CONCLUSION: GRE-EPI displayed higher agreement with the MPS results than SSFP despite significantly lower signal intensity, SNR and CNR.
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| 3. |
- Ahlander, Britt-Marie, 1954-
(författare)
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Magnetic Resonance Imaging of the Heart : Image quality, measurement accuracy and patient experience
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Background: Non-invasive diagnostic imaging of atherosclerotic coronary artery disease (CAD) is frequently carried out with cardiovascular magnetic resonance imaging (CMR) or myocardial perfusion single photon emission computed tomography (MPS). CMR is the gold standard for the evaluation of scar after myocardial infarction and MPS the clinical gold standard for ischemia. Magnetic Resonance Imaging (MRI) is at times difficult for patients and may induce anxiety while patient experience of MPS is largely unknown.Aims: To evaluate image quality in CMR with respect to the sequences employed, the influence of atrial fibrillation, myocardial perfusion and the impact of patient information. Further, to study patient experience in relation to MRI with the goal of improving the care of these patients.Method: Four study designs have been used. In paper I, experimental cross-over, paper (II) experimental controlled clinical trial, paper (III) psychometric crosssectional study and paper (IV) prospective intervention study. A total of 475 patients ≥ 18 years with primarily cardiac problems (I-IV) except for those referred for MRI of the spine (III) were included in the four studies.Result: In patients (n=20) with atrial fibrillation, a single shot steady state free precession (SS-SSFP) sequence showed significantly better image quality than the standard segmented inversion recovery fast gradient echo (IR-FGRE) sequence (I). In first-pass perfusion imaging the gradient echo-echo planar imaging sequence (GREEPI) (n=30) had lower signal-to-noise and contrast–to-noise ratios than the steady state free precession sequence (SSFP) (n=30) but displayed a higher correlation with the MPS results, evaluated both qualitatively and quantitatively (II). The MRIAnxiety Questionnaire (MRI-AQ) was validated on patients, referred for MRI of either the spine (n=193) or the heart (n=54). The final instrument had 15 items divided in two factors regarding Anxiety and Relaxation. The instrument was found to have satisfactory psychometric properties (III). Patients who prior CMR viewed an information video scored significantly (lower) better in the factor Relaxation, than those who received standard information. Patients who underwent MPS scored lower on both factors, Anxiety and Relaxation. The extra video information had no effect on CMR image quality (IV).Conclusion: Single shot imaging in atrial fibrillation produced images with less artefact than a segmented sequence. In first-pass perfusion imaging, the sequence GRE-EPI was superior to SSFP. A questionnaire depicting anxiety during MRI showed that video information prior to imaging helped patients relax but did not result in an improvement in image quality.
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| 4. |
- Javeed, Ashir, 1989-, et al.
(författare)
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Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning
- 2023
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clinical decision support system for predicting mortality in cardiac patients to address this problem. The dataset collected for the experimental purposes of the proposed model consisted of 55 features with a total of 368 samples. We found that the classes in the dataset were highly imbalanced. To avoid the problem of bias in the machine learning model, we used the synthetic minority oversampling technique (SMOTE). After balancing the classes in the dataset, the newly proposed system employed a (Formula presented.) statistical model to rank the features from the dataset. The highest-ranked features were fed into an optimized random forest (RF) model for classification. The hyperparameters of the RF classifier were optimized using a grid search algorithm. The performance of the newly proposed model ((Formula presented.) _RF) was validated using several evaluation measures, including accuracy, sensitivity, specificity, F1 score, and a receiver operating characteristic (ROC) curve. With only 10 features from the dataset, the proposed model (Formula presented.) _RF achieved the highest accuracy of 94.59%. The proposed model (Formula presented.) _RF improved the performance of the standard RF model by 5.5%. Moreover, the proposed model (Formula presented.) _RF was compared with other state-of-the-art machine learning models. The experimental results show that the newly proposed decision support system outperforms the other machine learning systems using the same feature selection module ((Formula presented.)).
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| 5. |
- Ebbers, Tino, 1972-
(författare)
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Flow Imaging: Cardiac Applications of 3D Cine Phase-Contrast MRI
- 2011
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Ingår i: Current Cardiovascular Imaging Reports. - : Springer Science and Business Media LLC. - 1941-9074 .- 1941-9066. ; 4:2, s. 127-133
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Forskningsöversikt (refereegranskat)abstract
- Global and regional blood flow dynamics are of pivotal importance to cardiac function. Fluid mechanical forces can affect hemolysis and platelet aggregation, as well as myocardial remodeling. In recent years, assessment of blood flow patterns based on time-resolved, three-dimensional, three-directional phase-contrast MRI (3D cine PC MRI) has become possible and rapidly gained popularity. Initially, this technique was mainly known for its intuitive and appealing visualizations of the cardiovascular blood flow. Most recently, the technique has begun to go beyond compelling images toward comprehensive and quantitative assessment of blood flow. In this article, cardiac applications of 3D cine PC MRI data are discussed, starting with a review of the acquisition and analysis techniques, and including descriptions of promising applications of cardiac 3D cine PC MRI for the clinical evaluation of myocardial, valvular, and vascular disorders.
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| 6. |
- Liu, Xixi, 1995, et al.
(författare)
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Deep Nearest Neighbors for Anomaly Detection in Chest X-Rays
- 2024
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 1611-3349 .- 0302-9743. ; 14349 LNCS, s. 293-302
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Konferensbidrag (refereegranskat)abstract
- Identifying medically abnormal images is crucial to the diagnosis procedure in medical imaging. Due to the scarcity of annotated abnormal images, most reconstruction-based approaches for anomaly detection are trained only with normal images. At test time, images with large reconstruction errors are declared abnormal. In this work, we propose a novel feature-based method for anomaly detection in chest x-rays in a setting where only normal images are provided during training. The model consists of lightweight adaptor and predictor networks on top of a pre-trained feature extractor. The parameters of the pre-trained feature extractor are frozen, and training only involves fine-tuning the proposed adaptor and predictor layers using Siamese representation learning. During inference, multiple augmentations are applied to the test image, and our proposed anomaly score is simply the geometric mean of the k-nearest neighbor distances between the augmented test image features and the training image features. Our method achieves state-of-the-art results on two challenging benchmark datasets, the RSNA Pneumonia Detection Challenge dataset, and the VinBigData Chest X-ray Abnormalities Detection dataset. Furthermore, we empirically show that our method is robust to different amounts of anomalies among the normal images in the training dataset. The code is available at: https://github.com/XixiLiu95/deep-kNN-anomaly-detection.
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| 7. |
- Grishenkov, Dmitry, 1983-, et al.
(författare)
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Acoustic properties of polymer-shelled ultrasound contrast agents. Bulk volume vs. microcapillary
- 2009
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Ingår i: 16th International Congress on Sound and Vibration 2009, ICSV 2009. - Krakow. - 9781615677368 ; , s. 2515-2522
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Konferensbidrag (refereegranskat)abstract
- The focus of contrast-enhanced ultrasound research has developed beyond detecting the blood pool to new areas such as perfusion imaging, drug and gene therapy, and targeted imaging. Polymer-shelled microbubbles are proposed as a new generation of ultrasound contrast agents (UCAs) which fulfil the requirements of these applications. With a shelf-life of several months and possibility to conjugate pharmacological molecules to their surface, these UCAs will allow not only to enhance the contrast of ultrasound images, but also to function as carriers of drugs to be delivered locally. In this study, the results of an experimental investigation of three types of UCAs stabilized by thick poly vinyl alcohol (PVA) shell are presented. These UCAs are synthesized from a PVA aqueous solution under varied pH values and temperature. The UCAs differ from each other in their average diameter, shell thickness and polydispersity. Knowledge of the peak negative pressure at which the solid shell fractures is paramount for a proper use of UCAs. Therefore, the dependence of this quantity on temperature and number of cycles in the incident pulse is examined. Much of the blood volume resides in the microcirculation, with capillaries playing a particularly important role in patho-physiology and drug delivery. In this sense in vitro characterization of the UCAs oscillation was moved from bulk volume to the capillary scale, where tissue-bubble interaction takes place. The main conclusion to be drawn from these results is that the shell of the UCAs begin to fracture at values of mechanical index (MI) approved for clinical applications. The fatigue, i.e. the accumulation of damage within the shell of the UCAs, is found to play an important role in fracturing the shell. Finally adhesion of the UCAs to the elastic wall is studied and correlated with estimates of the shell’s visco-elastic constants. Open questions arising from this comparison are briefly discussed.
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| 8. |
- Bondesson, Johan, 1991
(författare)
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Geometric Modeling of Thoracic Aortic Surface Morphology - Implications for Pathophysiology and Clinical Interventions
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Vascular disease risk factors such as hypertension, hyperlipidemia and old age are all results of modern-day lifestyle, and these diseases are getting more and more common. One treatment option for vascular diseases such as aneurysms and dissections is endovascular aortic repair introduced in the early 1990s. This treatment uses tubular fabric covered metallic structures (endografts) that are implanted using a minimally invasive approach and placed to serve as an articial vessel in a damaged portion of the vasculature. To ensure that the interventions are successful, the endograft must be placed in the correct location, and designed to sustain the hostile biological, chemical, and mechanical conditions in the body for many years. This is an interaction that goes both ways, and keeping in mind that the endograft is a foreign object placed in the sensitive vascular system, it is also important that it does not disrupt the native conditions more than necessary. This thesis presents a segmentation and quantication methodology to accurately describe the complex morphology and motion of diseased blood vessels in vivo through a natural and intuitive description of their luminal surfaces. After methodology validation, a series of important clinical applications are performed, all based on non-invasive imaging. Firstly, it is shown that explicit surface curvature quantication is necessary when compared to relying solely on centerline curvature and estimation methods. Secondly, it is shown that endograft malapposition severity can be predicted from preoperative geometric analysis of thoracic aortic surfaces. Thirdly, a multiaxial dynamics analysis of cardiac induced thoracic aortic surface motion shows how thoracic endovascular aortic repair affects the deformations of the dierent portions of the thoracic aorta. Fourthly, the helical propagation pattern of type B aortic dissection is determined, and two distinct modes of chirality are revealed, i.e., achiral and right-handed chiral groups. Finally, the effects of thoracic endovascular aortic repair on helical and cross-sectional morphology of type B dissections are investigated revealing how acuity and chirality affects the alteration due to intraluminal lining with endografts. Thus, the work presented in this thesis contributes by adding knowledge about pathology and pathophysiology through better geometric description of surface conditions of diseased thoracic aortas. This gives clinicians insights to use in their treatment planning and provides more nuanced boundary conditions for endograft manufacturers. Comprehensive knowledge about diseases, better treatment planning, and better devices are all crucial in order to improve the outcomes of performed interventions and ultimately the quality of life for the treated patients.
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| 9. |
- Polymeri, Erini, et al.
(författare)
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Deep learning-based quantification of PET/CT prostate gland uptake : association with overall survival
- 2020
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Ingår i: Clinical Physiology and Functional Imaging. - Chichester : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 40:2, s. 106-113
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To validate a deep-learning (DL) algorithm for automated quantification of prostate cancer on positron emission tomography/computed tomography (PET/CT) and explore the potential of PET/CT measurements as prognostic biomarkers. Material and methods: Training of the DL-algorithm regarding prostate volume was performed on manually segmented CT images in 100 patients. Validation of the DL-algorithm was carried out in 45 patients with biopsy-proven hormone-naïve prostate cancer. The automated measurements of prostate volume were compared with manual measurements made independently by two observers. PET/CT measurements of tumour burden based on volume and SUV of abnormal voxels were calculated automatically. Voxels in the co-registered 18F-choline PET images above a standardized uptake value (SUV) of 2·65, and corresponding to the prostate as defined by the automated segmentation in the CT images, were defined as abnormal. Validation of abnormal voxels was performed by manual segmentation of radiotracer uptake. Agreement between algorithm and observers regarding prostate volume was analysed by Sørensen-Dice index (SDI). Associations between automatically based PET/CT biomarkers and age, prostate-specific antigen (PSA), Gleason score as well as overall survival were evaluated by a univariate Cox regression model. Results: The SDI between the automated and the manual volume segmentations was 0·78 and 0·79, respectively. Automated PET/CT measures reflecting total lesion uptake and the relation between volume of abnormal voxels and total prostate volume were significantly associated with overall survival (P = 0·02), whereas age, PSA, and Gleason score were not. Conclusion: Automated PET/CT biomarkers showed good agreement to manual measurements and were significantly associated with overall survival. © 2019 The Authors. Clinical Physiology and Functional Imaging published by John Wiley & Sons Ltd on behalf of Scandinavian Society of Clinical Physiology and Nuclear Medicine
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| 10. |
- Johansson, Björn
(författare)
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Opacification of anterior part of hydrophilic acrylic IOL or a prelenticular inflammatory membrane?
- 2012
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Ingår i: Journal of cataract and refractive surgery. - Philadelphia : Elsevier. - 0886-3350 .- 1873-4502. ; 38:6, s. 1115-1116
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Tidskriftsartikel (refereegranskat)abstract
- In their recent case report, Park and Chuck1 describe the bilateral appearance of an opacification at the plane of the anterior surface of the hydrophilic acrylic Akreos MI60 intraocular lens (IOL) (Bausch & Lomb). The patient's general history of diabetes mellitus, proliferative retinopathy, and iris rubeosis explains the limited pupil dilation preventing visualization of the capsulorhexis opening in their slitlamp images.
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