premature infants/thermal images/parts detection/temperature extraction/deep learning

Body Part Detection from Neonatal Thermal Images Using Deep Learning

Because premature infants have an immature thermoregulatory function, proper temperature control with an incubator is essential. Currently, the probe is attached to the skin of the infants to measure the body temperature. However, the probe may come off easily and long-term measurement may be difficult because the skin of infants is immature and the limbs also move. Therefore, we try to measure body temperature by using a thermography, which is a non-contact device. It is possible to measure the body temperature of the whole body without giving stress to the infants. In order to perform non-invasive temperature measurement, we need to estimate the position and measurement region of the infants from the images. We perform binary classification during intervention (treatment by medical staff)/ non-intervention by using deep learning. We also construct detection model of six body parts (head/ chest/ upper right limb/ upper left limb/ lower right limb/ lower left limb). Then, after applying clustering to separate the infants region and other areas (reflection of blankets, medical devices, etc.), we extract the body surface temperature of the neck and limb based on the detected body parts. We are proceeding with the analysis using data provided by medical institutions conducting joint research. In the future, we will investigate the relationship between body surface temperature and core body temperature, and estimate the core body temperature so as to control incubator temperature automatically.

Published Papers

  • 別府文香, 吉川寛樹, 内山彰, 東野輝夫, 濱田啓介, & 平川英司. (2021). 新生児熱画像の部位検出における相対位置制約の有効性評価. 研究報告マルチメディア通信と分散処理 (DPS)2021(18), 1-6.
  • 別府文香, 吉川寛樹, 内山彰, 東野輝夫, 濱田啓介, & 平川英司. (2021). 深層学習を用いた新生児熱画像の部位検出. 第 29 回マルチメディア通信と分散処理ワークショップ論文集, 230-234.
  • 別府文香, 吉川寛樹, 内山彰, 東野輝夫, 濱田啓介, & 平川英司. (2021). 深層学習を用いた新生児熱画像の部位検出に基づく体温抽出手法の検討. 研究報告モバイルコンピューティングと新社会システム (MBL)2021(1), 1-7.
  • Beppu, F., Yoshikawa, H., Uchiyama, A., Higashino, T., Hamada, K., & Hirakawa, E. (2021, November). Body part detection from neonatal thermal images using deep learning. In International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services (pp. 438-450). Cham: Springer International Publishing.
  • 別府文香, 吉川寛樹, 内山彰, 東野輝夫, 濱田啓介, & 平川英司. (2021). 深層学習を用いた熱画像における新生児の身体部位検出法の検討. 研究報告モバイルコンピューティングとパーベイシブシステム (MBL)2021(22), 1-2.
  • 別府文香, 吉川寛樹, 内山彰, 東野輝夫, 濱田啓介, & 平川英司. (2022). 深層学習を用いた新生児熱画像の部位検出に基づく体温抽出手法の提案. 第 84 回全国大会講演論文集2022(1), 423-424.


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