Detection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network

Conference item

Gao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X. 2022. Detection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network. SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, USA 20 - 22 Feb 2022 Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2624423
TitleDetection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network
AuthorsGao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X.
Abstract

Human papillomavirus (HPV) remains a leading cause of virus-induced cancers. Hence early detection of HPV plays a crucial role in providing timely, optimal and effective intervention before such a cancer develops. While conventional light microscopy constitutes one of inseparable tools applied for studying biological cell structures, its low resolution at ~100nm per pixel falls short of detecting HPV that typically has a size of 52 to 55nm in diameter, giving rise to visualisation of HPV and subsequent evaluation of the efficacy of anti-HPV drugs at such sub-pixel level a challenging task if not overwhelmingly. This study employs an explainable deep learning network of texture transformer (TTSR) to up sample by four folds (×4). In comparison with other super resolution approaches, TTSR appears to perform the best with PSNR and SSIM being 28.70 and 0.8778 respectively whereas 25.80/0.7910, 18.35/0.5059. 30.31/0.8013, and 28.07/0.6074 are observed for the methods of RCAN, Pix2Pix, CycleGAN, and ESRGAN respectively. Significantly, the training pairs of TTSR does not need to be precisely match between low (LR) and high resolution (HR) images since the LR and HR images, which are required by many other super resolution approaches. This work constitutes one of the first to detect HPV applying explainable deep learning network, which will lead to the real world implementation to evaluate the efficacy of the developed anti-HPV drugs.

Keywordssuper resolution; Human papilloma virus like particles (HPVLPs) ; Texture transformer
ConferenceSPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging
Proceedings TitleProceedings Volume 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging
ISSN0277-786X
Electronic1996-756X
ISBN9781510649477
PublisherSociety of Photo-Optical Instrumentation Engineers
Publication dates
Print21 Feb 2022
Online04 Apr 2022
Publication process dates
Deposited21 Jan 2022
Accepted07 Jan 2022
Output statusPublished
Accepted author manuscript
Copyright Statement

Copyright 2022 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited
Xiaohong W. Gao, Xuesong Wen, Dong Li, Weiping Liu, Jichun Xiong, Xuefeng Liu, "Detection of human papillomavirus (HPV) from super resolution microscopic images applying a texture transformer network," Proc. SPIE 12036, Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1203627 (4 April 2022); https://doi.org/10.1117/12.2624423

Additional information

This is a poster presentation and a paper contribution

Web address (URL)https://spie.org/medical-imaging/presentation/Detection-of-human-papillomavirus-HPV-from-super-resolution-microscopic-images/12036-82?enableBackToBrowse=true
Digital Object Identifier (DOI)https://doi.org/10.1117/12.2624423
Scopus EID2-s2.0-85132017943
Web of Science identifierWOS:000836321800072
LanguageEnglish
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Qian, Y., Hui, R. and Gao, X. 2013. 3D CBIR with sparse coding for image-guided neurosurgery. Signal Processing. 93 (6), pp. 1673-1683. https://doi.org/10.1016/j.sigpro.2012.10.020
Retrieval of 3D medical images via their texture features
Gao, X., Qian, Y., Loomes, M., Barn, B., Comley, R., Chapman, A., Rix, J., Hui, R. and Tian, Z. 2012. Retrieval of 3D medical images via their texture features. International Journal on Advances in Software. 4 (3&4), pp. 499-509.
Bridging the abridged – the diffusion of Telemedicine in Europe and China
Gao, X., Loomes, M. and Comley, R. 2012. Bridging the abridged – the diffusion of Telemedicine in Europe and China. in: Rodrigues, J., Díez, I. and Abajo, B. (ed.) Telemedicine and e-health services, policies, and applications: avancements and developments USA IGI Global. pp. 451-495
The state of the art of medical imaging technology: from creation to archive and back.
Gao, X., Qian, Y. and Hui, R. 2011. The state of the art of medical imaging technology: from creation to archive and back. The Open Medical Informatics Journal. 5 (1-M8), pp. 73-85. https://doi.org/10.2174/1874431101105010073
Ectopic HCG beta may induce epithelialmensenchymal transition on human kera tinocytes in vitro and this could promote tumour progression and invasion.
Wen, S., Li, D., Ghali, L. and Iles, R. 2010. Ectopic HCG beta may induce epithelialmensenchymal transition on human kera tinocytes in vitro and this could promote tumour progression and invasion. Tumour Biology. 31 (S44).
The anatomy of teleneurosurgery in China
Gao, X. 2011. The anatomy of teleneurosurgery in China. International Journal of Telemedicine and Applications. 2011. https://doi.org/10.1155/2011/353405
Texture-based 3d image retrieval for medical applications
Gao, X., Qian, Y., Hui, R., Loomes, M., Comley, R., Barn, B., Chapman, A. and Rix, J. 2010. Texture-based 3d image retrieval for medical applications. Macedo, M. (ed.) IADIS International Conference e-Health 2010. Freiburg, Germany 29 - 31 Jul 2010 IADIS. pp. 101-108
Application of mesh morphing techniques in modelling 3D objects
Gao, X. and Hassan, M. 2010. Application of mesh morphing techniques in modelling 3D objects. Annual International Conference on Computer Games Multimedia and Allied Technology. Singapore 06 - 07 Apr 2010 Global Science and Technology Forum. https://doi.org/10.5176/978-981-08-5480-5_048
Estradiol, progesterone, testosterone profiles in human follicular fluid and cultured granulosa cells from luteinized pre-ovulatory follicles
Wen, S., Li, D., Tozer, A., Docherty, S. and Iles, R. 2010. Estradiol, progesterone, testosterone profiles in human follicular fluid and cultured granulosa cells from luteinized pre-ovulatory follicles. Reproductive Biology and Endocrinology. 8 (117). https://doi.org/10.1186/1477-7827-8-117
High follicular fluid adenosine levels may be pivotal in the metabolism and recycling of adenosine nucleotides in the human follicle
Wen, S., Perrett, D., Jones, N., Tozer, A., Docherty, S. and Iles, R. 2010. High follicular fluid adenosine levels may be pivotal in the metabolism and recycling of adenosine nucleotides in the human follicle. Metabolism: Clinical and Experimental. 59 (8), pp. 1145-1155. https://doi.org/10.1016/j.metabol.2009.09.037
Capillary electrophoresis of human follicular fluid
Wen, S., Perrett, D., Patel, P., Li, N., Docherty, S., Tozer, A. and Iles, R. 2009. Capillary electrophoresis of human follicular fluid. Journal of Chromatography B. 877 (31), pp. 3946-3952. https://doi.org/10.1016/j.jchromb.2009.09.046
Road sign recognition by one fixation of space-variant sensor.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N. and Hong, K. 2002. Road sign recognition by one fixation of space-variant sensor. in: Gorodnich, D. and Zhang, H. (ed.) Vision Interface ’2002: proceedings Quebec Canadian Image Processing and Pattern Recognition Society.
Invariant recognition of traffic signs
Gao, X., Shaposhnikov, D., Podladchikova, L., Shevtsova, N. and Golovan, A. 2002. Invariant recognition of traffic signs.
Application of the behavioural model of vision for invariant recognition of facial and traffic sign images.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N., Gusakova, V. and Gizatdinova, Y. 2003. Application of the behavioural model of vision for invariant recognition of facial and traffic sign images. in: Gulaev, Y. and Galushkin, A. (ed.) Neurocomputers and their application. [In Russian] Moscow Radiotechnics.
Image classification based on the informative regions properties.
Gao, X., Podladchikova, L. and Shaposhnikov, D. 2003. Image classification based on the informative regions properties. in: Proceedings of PRIA-6-2002 : 6th International conference on pattern recognition and image analysis: new information technologies. MAIK Nauka/Interperiodica. pp. 439-441
Image retrieval through perceptual shape modelling.
Gao, X., Ren, M., Riley, K., Eakins, J. and Briggs, P. 2001. Image retrieval through perceptual shape modelling. London Council for Museums, Archives and Libraries.
Telemedicine in Europe.
Gao, X. 2006. Telemedicine in Europe. ChinaPacs. Beijing 14 - 16 Apr 2006
A new approach to traffic sign recognition
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K., Batty, S., Golovan, A., Gusakova, V. and Shevtsova, N. 2002. A new approach to traffic sign recognition. in: Arabnia, H. and Mun, Y. (ed.) Proceedings of the international conference on imaging science, systems, and technology: CISST'02. Athens CSREA Press.
Road sign recognition by means of the behavioural model of vision.
Gao, X., Golovan, A., Hong, K., Podladchikova, L. and Shevtsova, N. 2002. Road sign recognition by means of the behavioural model of vision. in: Proceedings of the third all-Russian conference on neuroinformatics [In Russian]. Moscow. pp. 63-69
Colour reproduction for tele-imaging systems
Gao, X. and He, P. 2006. Colour reproduction for tele-imaging systems. Computerized medical imaging and graphics. 30 (6-7), pp. 79-84.
Measurement of vessel diameters on retinal for cardiovascular studies.
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. Measurement of vessel diameters on retinal for cardiovascular studies. in: Claridge, E., Bamber, J. and Marlow, K. (ed.) Medical image understanding and analysis 2001. Medical Imaging Understanding and Analysis.
Extraction of sagittal symmetry planes from PET images.
Gao, X., Batty, S., Clark, J., Fryer, T., Blandford, A. and International Association of Science and Technology for Development. 2001. Extraction of sagittal symmetry planes from PET images. in: Hamza, M. (ed.) Visualization, imaging and image processing: proceedings of the IASTED international conference. Calgary IASTED. pp. 428-433
The state of art of medical displays.
Gao, X. 2006. The state of art of medical displays. EuroPacs 2006. Trondheim, Norway 14 - 17 Jun 2006
Towards archiving wallpaper images
Gao, X., Qian, Y., Tully, T. and Hendon, Z. 2004. Towards archiving wallpaper images. in: Hamza, M. (ed.) Proceedings of the seventh IASTED international conference on computer graphics and imaging. Anaheim Acta Press. pp. 305-309
High-precision detection of facial landmarks to estimate head motions based on vision models
Gao, X., Anishenko, S., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. High-precision detection of facial landmarks to estimate head motions based on vision models. Journal of computer sciences. 3 (7), pp. 528-532.
Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels
Gao, X., Batty, S., Clark, J. and Fryer, T. 2006. Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels. Computerized medical imaging and graphics. 30 (6-7), pp. 70-74.
Extraction of physiological information from 3D PET brain images.
Gao, X., Batty, S., Fryer, T., Clark, J., Turkheimer, F. and International Association of Science and Technology for Development. 2003. Extraction of physiological information from 3D PET brain images. in: Villanueva, J. (ed.) Visualization imaging and image processing. Acta Press. pp. 401-405
Extraction of features from 3D PET images.
Gao, X., Batty, S., Clark, J. and Fryer, T. 2002. Extraction of features from 3D PET images. in: Houston, A. and Zwiggelar, R. (ed.) Medical image understanding and analysis 2002. BMVA.
Towards archiving 3D PET brain images based on their physiological and visual content.
Gao, X., Batty, S., Clark, J., Fryer, T. and Turkheimer, F. 2002. Towards archiving 3D PET brain images based on their physiological and visual content. International conference on diagnostic imaging and analysis. Shanghai, China 18 - 20 Aug 2002
A new approach to estimation of non-isotropic scale factors for correction of MR distortion
Gao, X., Hui, R., White, A.S. and Tian, Z. 2009. A new approach to estimation of non-isotropic scale factors for correction of MR distortion. International Journal of Computer Assisted Radiology and Surgery. 4 (s1), pp. s349-s350.
Classification of images on the basis of the properties of informative regions.
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2003. Classification of images on the basis of the properties of informative regions. Pattern Recognition and Image Analysis. 13 (2), pp. 349-352.
A fast approach to segmentation of PET brain images for extraction of features
Gao, X. and Clark, J. 2008. A fast approach to segmentation of PET brain images for extraction of features. Gao, X., Loomes, M., Comley, R., Muller, H. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_25
Prototype system for semantic retrieval of neurological PET images
Batty, S., Clark, J., Fryer, T. and Gao, X. 2008. Prototype system for semantic retrieval of neurological PET images. Gao, X., Muller, H., Loomes, M., Comley, R. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_23
Colour vision model-based approach for segmentation of traffic signs
Gao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D. 2008. Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing. 2008. https://doi.org/10.1155/2008/386705
Human granulosa-lutein cell in vitro production of progesterone, inhibin A, inhibin B, and activin A are dependent on follicular size and not the presence of the oocyte
Wen, S., Tozer, A., Li, D., Docherty, S., Al-Shawaf, T. and Iles, R. 2008. Human granulosa-lutein cell in vitro production of progesterone, inhibin A, inhibin B, and activin A are dependent on follicular size and not the presence of the oocyte. Fertility and Sterility. 89 (5), pp. 1406-1413. https://doi.org/10.1016/j.fertnstert.2007.03.086
Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach
Anishenko, S., Osimov, V., Shaposhnikov, D., Podladchikova, L., Comley, R. and Gao, X. 2008. Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach. Puuronen, S., Pechenizkiy, M., Tsymbal, A. and Lee, D. (ed.) 21st IEEE International Symposium on Computer-Based Medical Systems. Jyvaskyla, Finland 17 - 19 Jun 2008 IEEE Computer Society. pp. 50-52 https://doi.org/10.1109/CBMS.2008.19
Detection of head motions using a vision model
Gao, X., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. Detection of head motions using a vision model. Bashshur, R. (ed.) 3rd IASTED International Conference on Telehealth. Montreal, QC, Canada 31 May - 01 Jun 2007 Anaheim, CA Acta Press. pp. 167-171
Follicular fluid levels of inhibin A, inhibin B, and activin A levels reflect changes in follicle size but are not independent markers of the oocyte's ability to fertilize
Wen, S., Tozer, A., Butler, S., Bell, C., Docherty, S. and Iles, R. 2006. Follicular fluid levels of inhibin A, inhibin B, and activin A levels reflect changes in follicle size but are not independent markers of the oocyte's ability to fertilize. Fertility and Sterility. 85 (6), pp. 1723-1729. https://doi.org/10.1016/j.fertnstert.2005.11.058
Recognition of traffic signs based on their colour and shape features extracted using human vision models
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K. and Shevtsova, N. 2006. Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation. 17 (4), pp. 675-685. https://doi.org/10.1016/j.jvcir.2005.10.003
Characteristics of populations of granulosa cells from individual follicles in women undergoing 'coasting' during controlled ovarian stimulation (COS) for IVF
Tozer, A., Iles, R., Iammarrone, E., Gillott, C., Wen, S., Al-Shawaf, T. and Grudzinskas, J. 2004. Characteristics of populations of granulosa cells from individual follicles in women undergoing 'coasting' during controlled ovarian stimulation (COS) for IVF. Human Reproduction. 19 (11), pp. 2561-2568. https://doi.org/10.1093/humrep/deh487
Colour management in telemedicine
Gao, X. 2004. Colour management in telemedicine. Hamza, M. (ed.) 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 Anaheim, CA Acta Press. pp. 361-364
Application of vision models to traffic sign recognition
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2004. Application of vision models to traffic sign recognition. Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. (ed.) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Istanbul, Turkey 26 - 29 Sep 2003 Berlin, Heidelberg Springer. https://doi.org/10.1007/3-540-44989-2_131
Towards content-based retrieval for wallpaper images
Qian, Y., Tully, C., Hendon, Z. and Gao, X. 2003. Towards content-based retrieval for wallpaper images. 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 pp. 305-309
Vision models based identification of traffic signs
Gao, X., Podladchikova, L., Shaposhnikov, D., Shevtsova, N., Hong, K., Batty, S., Golovan, A. and Gusakova, V. 2002. Vision models based identification of traffic signs. 1st European Conference on Colour Graphics, Imaging, and Vision. University of Poitiers, France 02 - 05 Apr 2002 Society for Imaging Science and Technology.
Content based retrieval of lesioned brain images
Batty, S., Blandford, A., Clark, J., Fryer, T. and Gao, X. 2002. Content based retrieval of lesioned brain images. Siegel, E. and Huang, H. (ed.) SPIE Medical Imaging 2002. San Diego, California, United States 23 - 28 Feb 2002 Bellingham Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.466997
A method of vessel tracking for vessel diameter measurement on retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. A method of vessel tracking for vessel diameter measurement on retinal images. 2001 International Conference on Image Processing. Thessaloniki, Greece 07 - 10 Oct 2001 IEEE.
Computer algorithms for the automated measurement of retinal arteriolar diameters
Chapman, N., Witt, N., Gao, X., Bharath, A., Stanton, A., Thom, S. and Hughes, A. 2001. Computer algorithms for the automated measurement of retinal arteriolar diameters. British Journal of Ophthalmology. 85 (1), pp. 74-79. https://doi.org/10.1136/bjo.85.1.74
Quantification and characterization of arteries in retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2000. Quantification and characterization of arteries in retinal images. Computer Methods and Programs in Biomedicine. 63 (2), pp. 133-146. https://doi.org/10.1016/S0169-2607(00)00082-1