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Research Article

Deep learning based thermal image segmentation for laboratory animals tracking

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Pages 159-176 | Received 30 Aug 2019, Accepted 21 Jan 2020, Published online: 06 Feb 2020

References

  • Alberts JR. Observe, simplify, titrate, model, and synthesize: a paradigm for analyzing behavior. Behav Brain Res. 2012;231(2):250–261.
  • Lezak KR, Missig G, Carlezon WA Jr. Behavioral methods to study anxiety in rodents. Dialogues Clin Neurosci. 2017;19(2):181–191.
  • Grant EC, MacKintosh JH. A comparison of the social postures of some common laboratory rodents. Behaviour. 1963;21:246–259.
  • Yang Q, Kang W. General research on image segmentation algorithms. Graphics Signal Process. 2009 Oct;1:1–8.
  • Chaudhary A, Chaturvedi D. Efficient thermal image segmentation for heat visualization in solar panels and batteries using watershed transform. Int J Image Graphics Signal Process. 2017 Nov;9:10–17.
  • Aslani S, Harb MR, Costa PS, et al. Day and night: diurnal phase influences the response to chronic mild stress. Front Behav Neurosci. 2014;8; 82.
  • Roedel A, Storch C, Holsboer F, et al. Effects of light or dark phase testing on behavioural and cognitive performance in dba mice. Lab Anim. 2006;40(4):371–381.
  • Jin C, Yang Y, Xue Z-J, et al. Automated analysis method for screening knee osteoarthritis using medical infrared thermography. J Med Biol Eng. 2013;01;33:471–477.
  • Fernndez-Cuevas I, Marins JCB, Lastras JA, et al. Classification of factors influencing the use of infrared thermography in humans: a review. Infrared Phys Technol. 2015;71:28–55.
  • Ng EYK, Etehadtavakol M, editors. Application of infrared to biomedical sciences. Springer Nature Science; Germany; 2017.
  • Etehadtavakol M, Emrani Z, Ng EYK. Rapid extraction of the hottest or coldest regions of medical thermographic images. Med Biol Eng Comput. 2019 Feb;57(2):379–388.
  • Szentkuti A, Kavanagh HS, Grazio S. Infrared thermography and image analysis for biomedical use. Period Biol. 2011.
  • Jang EH, Park BJ, Park MS, et al. Analysis of physiological signals for recognition of boredom, pain, and surprise emotions. J Physiol Anthropol. 2015;34(1): 25.
  • Tan CL, Knight ZA. Regulation of body temperature by the nervous system. Neuron. 2018;98(1):31–48.
  • Crispim C,F Jr, Pederiva CN, Bose RC, et al. Ethowatcher: validation of a tool for behavioral and video-tracking analysis in laboratory animals. Comput Biol Med. 2012;42(2):257–264.
  • Branson K, Belongie S. Tracking multiple mouse contours (without too many samples). 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05). Vol. 1; San Diego, USA; 2005 Jun. p. 1039–1046.
  • Sona D, Zanotto M, Papaleo F, et al. Automated discovery of behavioural patterns in rodents. Proc Measuring Behav. 2014. Wageningen. 168–169.
  • Qiao Y, Wei Z, Zhao Y. Thermal infrared pedestrian image segmentation using level set method. Sensors. 2017;08;17:1811.
  • Barcelos EZ, Caminhas WM, Ribeiro E, et al. A combined method for segmentation and registration for an advanced and progressive evaluation of thermal images. Sensors. 2014;14(11):21950–21967.
  • Dayakshini D, Kamath S, Prasad K, et al. Segmentation of breast thermogram images for the detection of breast cancer: a projection profile approach.Journal of Image and Graphics. 2015 June;3(1):47–51.
  • Umapathy S, Vasu S, Gupta N. Computer aided diagnosis based hand thermal image analysis: a potential tool for the evaluation of rheumatoid arthritis. J Med Biol Eng. 2018 Aug;38(4):666–677.
  • Nida Mir U, Snekhalatha M, Choden Y. Thermal image segmentation of facial thermograms using k-means algorithm in evaluation of orofacial pain. In: Pandian D, Fernando X, Baig Z, et al., editors. Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB), Cham; Springer International Publishing; 2019. p. 565–572.
  • Shaikh S, Gite H, Manza RR, et al. Segmentation of thermal images using thresholding-based methods for detection of malignant tumours. In: Rodriguez JMC, Mitra S, Thampi SM, et al., editors. Intelligent systems technologies and applications. Cham: Springer International Publishing; 2016. p. 131–146.
  • Duarte A, Carro L, Espanha M, et al. Segmentation algorithms for thermal images. Procedia Technol. 2014;16:1560–1569.
  • Dalmia A, Kakileti ST, Manjunath G. Exploring deep learning networks for tumour segmentation in infrared images. 14th Quantitative InfraRed Thermography Conference; 2018. p. 521–530.
  • Ronneberger O, Fischer P, Brox T. U-net: convolutional networks for biomedical image segmentation. Medical Image Computing and Computer-Assisted Intervention MICCAI 2015; 2015. p. 234241.
  • Milletari F, Navab N, Ahmadi S-A. V-net: fully convolutional neural networks for volumetric medical image segmentation. CoRR. 2016; 565–571. abs/1606.04797.
  • Noh H, Hong S, Han B. Learning deconvolution network for semantic segmentation. 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, 2015, p. 1520–1528..
  • Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation.2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, 2015, p. 3431–3440..
  • Albonetti ME, Farabollini F. Social stress by repeated defeat: effects on social behavior and emotionality. Behav Brain Res. 1994;62:187–193.
  • Pellis SM, Pellis VC. Play-fighting differs from serious fighting in both target of attack and tactics of fighting in the laboratory rat rattus norvegicus. Aggress Behav. 1987;13:227–242.
  • Brain PF, McAllister KH, Walmsley S. Psychopharmacology, volume 13 of neuromethods. Clifton: Humana Press; 1989.
  • Mazur-Milecka M, Ruminski J. Automatic analysis of the aggressive behavior of laboratory animals using thermal video processing. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Seogwipo; 2017. p. 3827–3830.
  • Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern. 1979;9(1):62–66.
  • Felzenszwalb PF, HuttenlocherD PDP. Efficient graph-based image segmentation. Int J Comput Vis. 2004 Sep;59(2):167–181.
  • Saxena A, Ng EYK and Lim ST. Infrared (ir) thermography as a potential screening modality for carotid artery stenosis. Comput Biol Med. 2019;113:103419.
  • Saxena A, Ng EYK, Raman V, et al. Infrared (ir) thermography-based quantitative parameters to predict the risk of post-operative cancerous breast resection flap necrosis. Infrared Phys Technol. 2019. Article 103063;103:103063.
  • He K, Gkioxari G, Dollár P, et al. Mask R-CNN. The IEEE International Conference on Computer Vision (ICCV), 2017, p. 2961–2969.
  • Liu S, Lu Q, Qin H, et al. Path aggregation network for instance segmentation. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (2018): 8759–8768.
  • Chen K, Pang J, Wang J, et al. Hybrid task cascade for instance segmentation.2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019): 4969–4978.

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