FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4317254226> ?p ?o ?g. }

• W4317254226 abstract "<p>Background: The main goal of ultrasound therapy is to have clinical effects in the tissue without damage to the intervening and surrounding tissues. Treatments have been developed for both in vitro and in clinical applications. HIFU therapy is one of these. Non-invasive surgeries, such as HIFU, have been developed to treat tumors or to stop bleeding. In this approach, an adequate imaging method for monitoring and controlling the treatment is required. Methods: In this paper, an adaptive compressive sensing representation of ultrasound RF echo signals is presented based on empirical mode decomposition (EMD). According to the different numbers of intrinsic mode functions (IMFs) produced by the EMD, the ultrasound signals is adaptively compressive sampled in the source and then adaptively reconstructed in the receiver domains. In this paper, a new application of compressive sensing based on EMD (CS-EMD) in the monitoring of high-intensity focused ultrasound (HIFU) treatment is presented. Non-invasive surgeries such as HIFU have been developed for various therapeutic applications. In this technique, a suitable imaging method is necessary for monitoring of the treatment to achieve adequate treatment safety and efficacy. So far, several methods have been proposed, such as ultrasound radiofrequency (RF) signal processing techniques, and imaging methods such as X-ray, MRI, and ultrasound to monitor HIFU lesions. Results:In this paper, a CS-EMD method is used to detect the HIFU thermal lesion dimensions using different types of wavelet transform. The results of the processing on the real data demonstrate the potential for this technique in image-guided HIFU therapy. Conclusions: In this study, a new application of compressive sensing in the field of monitoring of the HIFU treatment is presented. To the best of our knowledge, so far no studies on compressive sensing have been carried out in the monitoring of the HIFU. Based on the results obtained, it was showed that the number of measurements and Intrinsic Mode Functions have the function of noise reduction. In addition, results were shown that the successful reconstruction of the compressive sensing signals can be gained using a threshold based algorithm. To this end, in this paper it was shown that by selecting an suitable number of measurements, the sparse transform, and a thresholding algorithm, we can achieve a more accurate detection of the HIFU thermal lesion size. </p>" @default.
• W4317254226 created "2023-01-18" @default.
• W4317254226 creator A5013520442 @default.
• W4317254226 creator A5032257241 @default.
• W4317254226 creator A5042201308 @default.
• W4317254226 date "2023-01-09" @default.
• W4317254226 modified "2023-10-17" @default.
• W4317254226 title "High-Intensity Focused Ultrasound Lesion Detection Using Adaptive Compressive Sensing Based on Empirical Mode Decomposition" @default.
• W4317254226 doi "https://doi.org/10.32920/21842496" @default.
• W4317254226 hasPublicationYear "2023" @default.
• W4317254226 type Work @default.
• W4317254226 citedByCount "0" @default.
• W4317254226 crossrefType "posted-content" @default.
• W4317254226 hasAuthorship W4317254226A5013520442 @default.
• W4317254226 hasAuthorship W4317254226A5032257241 @default.
• W4317254226 hasAuthorship W4317254226A5042201308 @default.
• W4317254226 hasBestOaLocation W43172542261 @default.
• W4317254226 hasConcept C106131492 @default.
• W4317254226 hasConcept C124851039 @default.
• W4317254226 hasConcept C126838900 @default.
• W4317254226 hasConcept C136229726 @default.
• W4317254226 hasConcept C143753070 @default.
• W4317254226 hasConcept C154945302 @default.
• W4317254226 hasConcept C199360897 @default.
• W4317254226 hasConcept C25570617 @default.
• W4317254226 hasConcept C2777365067 @default.
• W4317254226 hasConcept C2779843651 @default.
• W4317254226 hasConcept C31972630 @default.
• W4317254226 hasConcept C41008148 @default.
• W4317254226 hasConcept C47432892 @default.
• W4317254226 hasConcept C71924100 @default.
• W4317254226 hasConceptScore W4317254226C106131492 @default.
• W4317254226 hasConceptScore W4317254226C124851039 @default.
• W4317254226 hasConceptScore W4317254226C126838900 @default.
• W4317254226 hasConceptScore W4317254226C136229726 @default.
• W4317254226 hasConceptScore W4317254226C143753070 @default.
• W4317254226 hasConceptScore W4317254226C154945302 @default.
• W4317254226 hasConceptScore W4317254226C199360897 @default.
• W4317254226 hasConceptScore W4317254226C25570617 @default.
• W4317254226 hasConceptScore W4317254226C2777365067 @default.
• W4317254226 hasConceptScore W4317254226C2779843651 @default.
• W4317254226 hasConceptScore W4317254226C31972630 @default.
• W4317254226 hasConceptScore W4317254226C41008148 @default.
• W4317254226 hasConceptScore W4317254226C47432892 @default.
• W4317254226 hasConceptScore W4317254226C71924100 @default.
• W4317254226 hasLocation W43172542261 @default.
• W4317254226 hasLocation W43172542262 @default.
• W4317254226 hasLocation W43172542263 @default.
• W4317254226 hasLocation W43172542264 @default.
• W4317254226 hasOpenAccess W4317254226 @default.
• W4317254226 hasPrimaryLocation W43172542261 @default.
• W4317254226 hasRelatedWork W2024057000 @default.
• W4317254226 hasRelatedWork W2057253292 @default.
• W4317254226 hasRelatedWork W2110603325 @default.
• W4317254226 hasRelatedWork W2362274487 @default.
• W4317254226 hasRelatedWork W2372667652 @default.
• W4317254226 hasRelatedWork W2512626015 @default.
• W4317254226 hasRelatedWork W2903061581 @default.
• W4317254226 hasRelatedWork W2921176206 @default.
• W4317254226 hasRelatedWork W4313887759 @default.
• W4317254226 hasRelatedWork W4317254226 @default.
• W4317254226 isParatext "false" @default.
• W4317254226 isRetracted "false" @default.
• W4317254226 workType "article" @default.