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01-07-2022 | Research paper

Effective quantum mechanics–embedded nanoparticle occlusion analysis framework

Authors: Maryam Khairunissa, Hyunsoo Lee

Published in: Journal of Nanoparticle Research | Issue 7/2022

Abstract

While the occlusion analysis of nanoparticles (NPs) has been important in detecting NPs in images, most existing methods fail to accurately segment contours, and additional time-consuming manual inspections are required. To overcome this issue, a new and effective quantum-mechanics-embedded NP occlusion analysis framework is proposed. The integration of quantum mechanics in occlusion analysis helps identify irregular shaped NPs with noise. Brownian motion–based drift and diffusion were used to detect whether the NPs had occluded regions. The decision parameters and relevant quantum mechanics–based differential equations were derived from scanning electron microscopy images of the applied NPs. The overall proposed framework consists of five stages, from preprocessing to quantum mechanics–based contour estimation. To demonstrate the effectiveness of the proposed framework, comparative analyses with the existing methods were carried out. This revealed that the proposed framework contributed to more accurate occlusion identification.

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Shahzad Y, Rizvi SAA, Yousaf AM, Hussain T (2022) Drug delivery using nanomaterials. CRC Press, London

Demir E (2020) A review on nanotoxicity and nano genotoxicity of different shapes of nanomaterials. J Appl Toxicol 41:118–147. https://doi.org/10.1002/jat.4061 CrossRef

Liu Y, Zhu S, Gu Z, Chen C, Zhao Y (2021) Toxicity of manufactured nanomaterials. J Particuology. https://doi.org/10.1016/j.partic.2021.11.007 CrossRef

Khan I, Saeed K, Khan I (2019) Nanoparticles: properties, applications and toxicities. Arab J Chem 12:908–931. https://doi.org/10.1016/j.arabjc.2017.05.011

Crouzier L, Delvallee A, Ducourtieux S, Devoille L, Tromas C, Feltin N (2019) A new method for measuring nanoparticle diameter from a set of SEM images using a remarkable point. J Ultramicroscopy 207:112847. https://doi.org/10.1016/j.ultramic.2019.112847 CrossRef

Ali R, El-Boubbou K, Boudjelal M (2021) An easy, fast and inexpensive method of preparing a biological specimen for scanning electron microscopy (SEM). J MethodsX 8:101521. https://doi.org/10.1016/j.mex.2021.101521

Oktay AB, Gurses A (2019) Automatic detection, localization and segmentation of nano-particles with deep learning in microscopy images. J Micron 120:113–119. https://doi.org/10.1016/j.micron.2019.02.009 CrossRef

Gardiner CW (2004) Handbook of stochastic methods for physics, chemistry, and the natural sciences. Springer, New York CrossRef

Monthus C (2021) Jump-drift and jump diffusion processes: large deviations for the density, the current and the jump-flow and for the excursions between jumps. J Stat Mech. https://doi.org/10.1088/1742-5468/ac12c5 CrossRef

10.

Boiko DA, Pentsak EO, Cherepanova VA, Ananikov VP (2020) Electron microscopy dataset for the recognition of nanoscale ordering effects and location of nanoparticles. J Sci Data 7:101. https://doi.org/10.1038/s41597-020-0439-1 CrossRef

11.

Electron microscopy dataset for the recognition of nanoscale ordering effects and location of nanoparticles – dataset 2 (disordered). Available online: https://figshare.com/articles/dataset/Electron_microscopy_dataset_for_the_recognition_of_nanoscale_ordering_effects_and_location_of_nanoparticles_Dataset_2_disordered_/11783667/1 (accessed September 27, 2021)

12.

Chen A, Ostrom C (2015) Palladium-based nanomaterials: synthesis and electrochemical applications. J Chem Rev 115(21):11999–12044. https://doi.org/10.1021/acs.chemrev.5b00324 CrossRef

13.

Koyama A, Miyauchi S, Morooka K, Hojo H, Einaga H, Murakami Y (2021) Analysis of TEM images of metallic nanoparticles using convolutional neural networks and transfer learning. J Magn Magn Mater 538:168225. https://doi.org/10.1016/j.jmmm.2021.168225 CrossRef

14.

Bourrous S, Ribeyre Q, Lintis L, Yon J, Bau S, Thomas D, Vallieres C, Ouf F (2018) A semi-automatic analysis tool for the determination of primary particle size, overlap coefficient and specific surface area of nanoparticles aggregates. J Aerosol Sci 126:122–132. https://doi.org/10.1016/j.jaerosci.2018.09.001 CrossRef

15.

Deng X, Cui Y (2021) An improved belief structure satisfaction to uncertain target values by considering the overlapping degree between events. J Inform Sci 580:398–407. https://doi.org/10.1016/j.ins.2021.08.083 CrossRef

16.

Park C, Huang JZ, Ji JX, Ding Y (2013) Segmentation, inference, and classification of partially overlapping nanoparticles. IEEE Trans Pattern Anal Mach Intell 35:669–681. https://doi.org/10.1109/TPAMI.2012.163 CrossRef

17.

Li J, Ostling M (2016) Precise percolation thresholds of two-dimensional random systems comprising overlapping ellipse. J Phys A Stat Mech Appl 462:940–950. https://doi.org/10.1016/j.physa.2016.06.020 CrossRef

18.

Cid-Mejias A, Alonso-Calvo R, Gavilan H, Crespo J, Maojo V (2021) A deep learning approach using synthetic images for segmenting and estimation 3D orientation of nanoparticles in EM images. J Comput Methods Programs Biomed 202:105958. https://doi.org/10.1016/j.cmpb.2021.105958 CrossRef

19.

Li H (2019) Multiple ellipses fitting of densely connected contours. J Inform Sci 502:330–345. https://doi.org/10.1016/j.ins.2019.06.045 CrossRef

20.

Zafari S, Murashkina M, Eerola T, Sampo J, Kalviainen H, Haario H (2020) Resolving overlapping convex objects in silhouette images by concavity analysis and Gaussian process. J Vis Commun Image Represent 73:102962. https://doi.org/10.1016/j.jvcir.2020.102962 CrossRef

21.

Phromsuwan U, Sirisathitkul C, Sirisathitkul Y, Uyyanonvara B, Muneesawang P (2013) Application of image processing to determine size distribution of magnetic nanoparticles. J Magn 18:311–316. https://doi.org/10.4283/JMAG.2013.18.3.311 CrossRef

22.

Zafari S, Murashkina M, Eerola T, Sampo J, Kalviainen H, Haario H (2015) Segmentation of overlapping elliptical objects in silhouette images. IEEE Trans Image Process 24:5942–5952. https://doi.org/10.1109/TIP.2015.2492828 CrossRef

23.

Kapaldo J (2018) Seed-point based geometric partitioning of nuclei clumps. arXiv:1804.04549. https://doi.org/10.48550/arXiv.1804.04549

24.

Fromhold Jr AT (2001) Quantum Mechanics. Encyclopedia of physical science and technology 13:359–408. https://doi.org/10.1016/b0-12-227410-5/00626-8

25.

Oliveira IS, Bonagamba TJ, Sarthour RS, Freitas JCC, deAzevedo ER (2007) Fundamentals of quantum computation and quantum information. NMR Quantum Information Processing 3:93–136. https://doi.org/10.1016/B978-044452782-0/50005-1

26.

Ahmed SN (2015) Interaction of radiation with matter. J Phys Eng Radiat Detect 2:65–155. https://doi.org/10.1016/B978-0-12-801363-2.00002-4

27.

Sauer J (2007) Structure and reactivity of solid catalysts — quantum chemical approach. Stud Surf Sci Catal 172:19–26. https://doi.org/10.1016/B978-0-444-53202-2.50003-8 CrossRef

28.

Lin YK, Cai GQ (2001) Stochastic analysis of nonlinear systems. Encyclopedia of Vibration 2001:1238–1246. https://doi.org/10.1006/rwvb.2001.0044

29.

The Brownian Movement. Available online: https://www.feynmanlectures.caltech.edu/I_41.html (accessed on 4th January 2022)

30.

Ross SM (2014) Introduction to Probability Models. Elsevier, Oxford

31.

Øksendal B (2002) Stochastic differential equations: an introduction with applications, 5th edn. Springer-Verlag, Heidelberg

32.

Imkeller P, Schmalfuss B (2001) The conjugacy of stochastic and random differential equations and the existence of global attractors. J Dyn Diff Equat 13:215–249. https://doi.org/10.1023/A:1016673307045 CrossRef

33.

Munoz-Salinas R, Medina-Carnicer R, Madrid-Cuevas FJ, Carmona-Poyato A (2008) Depth silhouette for gesture recognition. J Pattern Recognit Lett 29:319–329. https://doi.org/10.1016/j.patrec.2007.10.011 CrossRef

34.

Liu Y, Xie Z, Liu H (2019) Fast and robust ellipse detector based on edge following method. IET Image Proc 13:2409–2419. https://doi.org/10.1049/iet-ipr.2018.5687 CrossRef

35.

Sonka M, Hlavac V, Boyle R (2015) Image processing, analysis, and machine vision, 4th edn. Cengage Learning, USA

36.

He XC, Yung NHC (2004) Curvature scale space corner detector with adaptive threshold and dynamic region of support. Proceedings of the 17th International Conference on Pattern Recognition ICPR 791–794. https://doi.org/10.1109/ICPR.2004.1334377

37.

Casey JE (1996) Exploring curvature. Vieweg, Braunschweig/Wiesbaden. https://doi.org/10.1007/978-3-322-80274-3

38.

Image segmentation in computer vision. Available online: https://www.analyticsvidhya.com/blog/2021/09/active-contours-a-method-for-image-segmentation-in-computer-vision/ (accessed December 8, 2021)

39.

Adluru N, Latecki LJ, Lakaemper R (2007) Contour grouping based on local symmetry. IEEE Int Conf Comput Vis. https://doi.org/10.1109/ICCV.2007.4408879 CrossRef

40.

Bai X, Sun C, Zhou F (2009) Splitting touching cells based on concave points and ellipse fitting. J Pattern Recognit 42:2434–2446. https://doi.org/10.1016/j.patcog.2009.04.003 CrossRef

41.

Douillet D, Rolley E, Guthmann C, Prevost AM (2000) An easy-to-build long working distance microscope. J Phys B Condens Matter 284:2059–2060. https://doi.org/10.1016/S0921-4526(99)02943-9 CrossRef

42.

Haase JR, Go DB (2016) Analysis of thermionic and thermo-field emission in microscale gas discharges. J Phys D Appl Sci 49:055206. https://doi.org/10.1088/0022-3727/49/5/055206 CrossRef

43.

Zafari S, Murashkina M, Eerola T, Sampo J, Kalviainen H, Haario H (2017) Segmentation of partially overlapping convex objects using branch and bound algorithm. Springer International Publishing AG. https://doi.org/10.1007/978-3-319-54526-4_6 CrossRef

Title: Effective quantum mechanics–embedded nanoparticle occlusion analysis framework
Authors: Maryam Khairunissa
Hyunsoo Lee
Publication date: 01-07-2022
Publisher: Springer Netherlands
Published in: Journal of Nanoparticle Research / Issue 7/2022
Print ISSN: 1388-0764
Electronic ISSN: 1572-896X
DOI: https://doi.org/10.1007/s11051-022-05517-0

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