{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T22:43:19Z","timestamp":1766011399539,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T00:00:00Z","timestamp":1722297600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"],"award-info":[{"award-number":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"]}]},{"name":"Inner Mongolia Natural Science Foundation of China","award":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"],"award-info":[{"award-number":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"]}]},{"name":"Inner Mongolia Autonomous Region Science and Technology Major Project","award":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"],"award-info":[{"award-number":["12361088","12261067","62065015","61961033","2021LHMS01006","2022MS01008","2021MS06021","2019ZD025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical challenge for ensuring treatment efficacy and patient safety. This study presents a novel approach to simulate real MH and precisely determine the temperature of the target region within biological tissues using a temporal-informed neural network. We conducted MH experiments on 30 sets of phantoms and 10 sets of ex vivo pork tissues. We proposed a novel perspective: the evolving tissue responses to continuous electromagnetic radiation stimulation are a joint evolution in temporal and spatial dimensions. Our model leverages TimesNet to extract periodic features and Cloblock to capture global information relevance in two-dimensional periodic vectors from ultrasound images. By assimilating more ultrasound temporal data, our model improves temperature-estimation accuracy. In the temperature range 25\u201365 \u00b0C, our neural network achieved temperature-estimation root mean squared errors of approximately 0.886 \u00b0C and 0.419 \u00b0C for fresh ex vivo pork tissue and phantoms, respectively. The proposed temporal-informed neural network has a modest parameter count, rendering it suitable for deployment on ultrasound mobile devices. Furthermore, it achieves temperature accuracy close to that prescribed by clinical standards, making it effective for non-destructive temperature monitoring during MH of biological tissues.<\/jats:p>","DOI":"10.3390\/s24154934","type":"journal-article","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T15:25:23Z","timestamp":1722353123000},"page":"4934","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Ultrasound Image Temperature Monitoring Based on a Temporal-Informed Neural Network"],"prefix":"10.3390","volume":"24","author":[{"given":"Yuxiang","family":"Han","sequence":"first","affiliation":[{"name":"School of Digital and Intelligence Industry, Inner Mongolia University of Science & Technology, Baotou 014000, China"}]},{"given":"Yongxing","family":"Du","sequence":"additional","affiliation":[{"name":"School of Digital and Intelligence Industry, Inner Mongolia University of Science & Technology, Baotou 014000, China"}]},{"given":"Limin","family":"He","sequence":"additional","affiliation":[{"name":"School of Science, Inner Mongolia University of Science & Technology, Baotou 014000, China"}]},{"given":"Xianwei","family":"Meng","sequence":"additional","affiliation":[{"name":"Laboratory of Controllable Preparation and Application of Nanomaterials, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Minchao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Digital and Intelligence Industry, Inner Mongolia University of Science & Technology, Baotou 014000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4188-495X","authenticated-orcid":false,"given":"Fujun","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Science, Inner Mongolia University of Science & Technology, Baotou 014000, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3322\/caac.21763","article-title":"Cancer Statistics, 2023","volume":"73","author":"Siegel","year":"2023","journal-title":"CA Cancer J. 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