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Multi-Label Learning With Visual-Semantic Embedded Knowledge Graph for Diagnosis of Radiology Imaging
2021
IEEE Access
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A significant task of automatic diagnosis for radiology imaging, especially for chest X-rays, is to identify disease types, which can be viewed as a multi-label learning problem. ...
However, the utilization of medical reports paired with radiology images is neglected in such approaches. Hence, at least two novel improvements are proposed in this paper. ...
The authors of DenseNet-KG constructed a medical concept graph based on prior knowledge to diagnose chest-X-ray images. ...
doi:10.1109/access.2021.3052794
fatcat:y7nddtvezbehpof6uiws73oxki
Retrieval From and Understanding of Large-Scale Multi-modal Medical Datasets: A Review
2017
IEEE transactions on multimedia
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This text is a systematic review of recent work (concentrating on the period between 2011-2017) on content-based multi-modal retrieval and image understanding in the medical domain, where image understanding ...
based on the experience available in the multimedia community. ...
related radiology reports for multimodal retrieval enriched by semantics. ...
doi:10.1109/tmm.2017.2729400
fatcat:td4s7hbegzbmhlosalzlc3p7tq
Chest ImaGenome Dataset for Clinical Reasoning
[article]
2021
arXiv
pre-print
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extracted from text reports, or trained via a joint image and unstructured text learning strategy. ...
Local annotations are automatically produced using a joint rule-based natural language processing (NLP) and atlas-based bounding box detection pipeline. ...
Acknowledgements This work was supported by the Rensselaer-IBM AI Research Collaboration, part of the IBM AI Horizons Network, and the IBM-MIT Critical Data Collaboration. ...
arXiv:2108.00316v1
fatcat:lfuj6nv2znghdd2vwnfljqee6e
Automatic Report Generation for Chest X-Ray Images via Adversarial Reinforcement Learning
2021
IEEE Access
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INTRODUCTION Automatic radiology-report generation is a computer-aided diagnostic technology used for generating a free-text description of disease diagnosis or future treatment based on radiology images ...
[5] conducted a multi-view fusion on deep features after the CNN backbone. ...
doi:10.1109/access.2021.3056175
fatcat:ryv4noypxbfhdeadytlme26wgq
Towards case-based medical learning in radiological decision making using content-based image retrieval
2011
BMC Medical Informatics and Decision Making
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To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). ...
Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. ...
The IRMAdiag trainer is based on approved learning methods applied in both protected and realistic contexts and represents a modern training concept to enrich the range of current medical training. ...
doi:10.1186/1472-6947-11-68
pmid:22032775
pmcid:PMC3217894
fatcat:xt6e2bzelvfqdgvpi5b465bdga
A survey on attention mechanisms for medical applications: are we moving towards better algorithms?
[article]
2022
arXiv
pre-print
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on medical image classification with three different use cases. ...
Naturally, the use of attention-based algorithms for medical applications occurred smoothly. ...
Acknowledgements This work, developed within the scope of the project "TAMI -Transparent Artificial Medical Intelligence" (NORTE-01-0247-FEDER-045905), is co-financed by ERDF -European Regional Fund through ...
arXiv:2204.12406v1
fatcat:lwz3hvd44bfqnhf7n57ejehidu
Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges
2021
Diagnostics
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and rectal cancers on computed tomography (CT) and magnetic resonance imaging (MRI), highlighting the key findings, challenges and limitations. ...
The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit detail from large datasets have attracted substantial research attention in the field of medical image processing ...
Although previous publications have provided technical reviews of recent automatic medical image segmentation approaches, [12] [13] [14] [15] [16] [17] some with a particular focus on radiology [18] ...
doi:10.3390/diagnostics11111964
pmid:34829310
pmcid:PMC8625809
fatcat:alr36jtq6fgeddnluclp5neb2i
Prototypes for Content-Based Image Retrieval in Clinical Practice
2011
Open Medical Informatics Journal
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We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS ...
Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). ...
hospital (WIDTH): interpretation, infrastructure, and integration). ...
doi:10.2174/1874431101105010058
pmid:21892374
pmcid:PMC3149811
fatcat:qf4z2x4ayffmbgd2wk72s3p7nq
Deformation and Refined Features Based Lesion Detection on Chest X-ray
2020
IEEE Access
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To deal with problems, we propose the deformation and refined features based lesion detection on the chest X-ray algorithm called DRCXNet. ...
Automatic and accurate detection of chest X-ray lesion is a challenging task. ...
[9] built a classifier based on PCA, linear SVM, and multi-kernel SVM, which can compare and discriminate between healthy controls (HC) and Alzheimer's disease (AD) patients. ...
doi:10.1109/access.2020.2963926
fatcat:fqbsoknsbbefpj5yv2fuwguxq4
Multispecialty Enterprise Imaging Workgroup Consensus on Interactive Multimedia Reporting Current State and Road to the Future: HIMSS-SIIM Collaborative White Paper
2021
Journal of digital imaging
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, radiology, endoscopic procedural specialties, and other medical disciplines. ...
The workgroup adopted a consensus definition of IMR as "interactive medical documentation that combines clinical images, videos, sound, imaging metadata, and/or image annotations with text, typographic ...
Structured and synoptic data lend themselves far better than prose to generating interactive multimedia reports due to being able to automatically associate data element, images, and downstream actions ...
doi:10.1007/s10278-021-00450-5
pmid:34131793
pmcid:PMC8329131
fatcat:pi4r6xaajbfa3bovmahssoe4mi
Navigation in surgery
2013
Langenbeck's archives of surgery (Print)
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Over the past decade, navigation in surgery has evolved beyond imaging modalities and bulky systems into the rich networking of the cloud or devices that are pocket-sized. ...
Introduction "Navigation in surgery" spans a broad area, which, depending on the clinical challenge, can have different meanings. ...
and the source are credited. ...
doi:10.1007/s00423-013-1059-4
pmid:23430289
pmcid:PMC3627858
fatcat:kzuvxitnxrgs3kaablcnkaar3u
Data Mining and Knowledge Discovery
[chapter]
1998
Data Mining Methods for Knowledge Discovery
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In this paper, a review study is done on existing data mining and knowledge discovery techniques, applications and process models that are applicable to healthcare environments. ...
Organizations that take advantage of KDD techniques will find that they can lower the healthcare costs while improving healthcare quality by using fast and better clinical decision making. ...
images for radiology. ...
doi:10.1007/978-1-4615-5589-6_1
fatcat:p2oyvrwv6rdxlam7jtunbsz56q
Symmetry and asymmetry analysis and its implications to computer-aided diagnosis: A review of the literature
2009
Journal of Biomedical Informatics
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lesions, based solely on the information contained in images. ...
In neuro-imaging applications, for example, one way to perform this knowledge integration is to uncover symmetry/asymmetry information from the corresponding regions of the head and to explore its implication ...
Celina Imielinska and Dr. Andrew Laine for the useful discussions concerning this topic. ...
doi:10.1016/j.jbi.2009.07.003
pmid:19615468
fatcat:kmwgz6btbncj5f6zomyiofohom
State-of-the-Art Mobile Radiation Detection Systems for Different Scenarios
2021
Sensors
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Examples of improvements are: the use of silicon photomultiplier-based scintillators, new scintillating crystals, compact dual-mode detectors (gamma/neutron), data fusion, mobile sensor networks, cooperative ...
Four scenarios are considered: radiological and nuclear accidents and emergencies; illicit traffic of special nuclear materials and radioactive materials; nuclear, accelerator, targets, and irradiation ...
its impact on the general public and environment radiation safety [38] and radiological risks. ...
doi:10.3390/s21041051
pmid:33557104
pmcid:PMC7913838
fatcat:b2bw2jhqifaadbwq5qkwkdgkjm
Informatics
2015
Laboratory Investigation
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Background: The development of next generation sequencing (NGS) and associated target sequence enrichment technologies has enabled time and cost effective detection of clinically relevant molecular alterations ...
efficient multi-step data processing. ...
Whole slide imaging technology is used for the telepathology consultation service. ...
doi:10.1038/labinvest.2015.17
fatcat:74eygyy7o5gkrhizoootoyfol4
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