Infrared (IR) thermography-based quantitative parameters to predict the risk of post-operative cancerous breast resection flap necrosis

@article{Saxena2019InfraredT,
  title={Infrared (IR) thermography-based quantitative parameters to predict the risk of post-operative cancerous breast resection flap necrosis},
  author={Ashish Kumar Saxena and Eugene Yew Jing Ng and Vignesh Raman and Muhammad Syarifuddin Bin Mohamed Hamli and Mateusz Moderhak and Szymon Kołacz and Jerzy Jankau},
  journal={Infrared Physics \& Technology},
  year={2019},
  volume={103},
  pages={103063}
}
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Deep learning based thermal image segmentation for laboratory animals tracking
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An efficiency analysis of deep learning based image segmentation algorithms for the need of laboratory rats images and results indicate, that networks trained on images containing a narrow range of temperature data equal to animals’ body temperature or even its part, are able to better perform the object segmentation than networkstrained on the original data.
Sub-pixel matching method for low-resolution thermal stereo images
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