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Proceedings ArticleDOI

Regularized Nakagami Ultrasound Imaging for Microwave Hyperthermia monitoring

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TLDR
In this article, the feasibility of using ultrasound-based regularized Nakagami imaging (RNI) to image the spatial and temporal evolution of hotspot during microwave (MW) hyperthermia experiment was explored on in-vitro polyacrylamide gel (PAG)-agar based phantoms.
Abstract
The study involves development of ultrasound-based regularized Nakagami imaging (RNI) that improves the quality of Nakagami image. The feasibility of RNI to image the spatial and temporal evolution of hotspot during microwave (MW) hyperthermia experiment was explored on in-vitro polyacrylamide gel (PAG)-agar based phantoms. The normalized cumulative differential regularized Nakagami (NCDRN) maps were estimated from the envelope of beamformed ultrasound radiofrequency (RF) data using proposed RNI technique. The NCDRN maps were estimated at different time instants for the entire duration of the experiment. The experiments were carried out on phantoms at power level of 12 W fed to the microwave antenna. The contour maps of the NCDRN and the ground truth temperature map, obtained using an infra-red (IR) thermal camera corresponding to ultrasound imaging plane, showed that NCDRN was able to locate the axial and lateral co-ordinates of the hotspot with an error of < 1.5 mm axially and < 0.4 mm laterally. This preliminary in-vitro study demonstrates that NCDRN maps estimated using the regularized Nakagami imaging may have potential in imaging and evaluating the spatio-temporal evolution of hotspot and may help in the development of ultrasound-based image guided hotspot monitoring system for microwave hyperthermia.

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Proceedings ArticleDOI

Regularized Kurtosis Imaging and its Comparison with Regularized Log Spectral Difference and Regularized Nakagami Imaging for Microwave Hyperthermia Hotspot Monitoring

TL;DR: An improved method of regularized Kurtosis imaging (RKI) is introduced and its performance against regularized log spectral difference (RLSD) and regularized Nakagami imaging methods are compared and offer an alternative way to track the hotspot during microwave hyperthermia treatment.
References
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Book

Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

TL;DR: It is argued that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas.
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Monitoring radiofrequency ablation with ultrasound Nakagami imaging.

TL;DR: This study demonstrated that ultrasound Nakagami imaging based on the analysis of backscattered statistics has the ability to visualize the RFA-induced ablation zone, even if the shadow effect exists in the B-scan.
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