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	Author	Zeegers, M.T.; Kadu, A.; van Leeuwen, T.; Batenburg, K.J.
	Title	ADJUST : a dictionary-based joint reconstruction and unmixing method for spectral tomography			Type	A1 Journal article
	Year	2022	Publication	Inverse problems	Abbreviated Journal	Inverse Probl
	Volume	38	Issue	12	Pages	125002-125033
	Keywords	A1 Journal article; Electron microscopy for materials research (EMAT)
	Abstract	Advances in multi-spectral detectors are causing a paradigm shift in x-ray computed tomography (CT). Spectral information acquired from these detectors can be used to extract volumetric material composition maps of the object of interest. If the materials and their spectral responses are known a priori, the image reconstruction step is rather straightforward. If they are not known, however, the maps as well as the responses need to be estimated jointly. A conventional workflow in spectral CT involves performing volume reconstruction followed by material decomposition, or vice versa. However, these methods inherently suffer from the ill-posedness of the joint reconstruction problem. To resolve this issue, we propose 'A Dictionary-based Joint reconstruction and Unmixing method for Spectral Tomography' (ADJUST). Our formulation relies on forming a dictionary of spectral signatures of materials common in CT and prior knowledge of the number of materials present in an object. In particular, we decompose the spectral volume linearly in terms of spatial material maps, a spectral dictionary, and the indicator of materials for the dictionary elements. We propose a memory-efficient accelerated alternating proximal gradient method to find an approximate solution to the resulting bi-convex problem. From numerical demonstrations on several synthetic phantoms, we observe that ADJUST performs exceedingly well compared to other state-of-the-art methods. Additionally, we address the robustness of ADJUST against limited and noisy measurement patterns. The demonstration of the proposed approach on a spectral micro-CT dataset shows its potential for real-world applications. Code is available at https://github.com/mzeegers/ADJUST.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos	000868885200001	Publication Date	2022-09-20
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0266-5611	ISBN		Additional Links	UA library record; WoS full record
	Impact Factor	2.1	Times cited		Open Access	Not_Open_Access
	Notes				Approved	Most recent IF: 2.1
	Call Number	UA @ admin @ c:irua:191536			Serial	7280
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	Author	Skorikov, A.; Batenburg, K.J.; Bals, S.
	Title	Analysis of 3D elemental distribution in nanomaterials : towards higher throughput and dose efficiency			Type	A1 Journal article
	Year	2023	Publication	Journal of microscopy	Abbreviated Journal
	Volume	289	Issue	3	Pages	157-163
	Keywords	A1 Journal article; Electron microscopy for materials research (EMAT)
	Abstract	Many advanced nanomaterials rely on carefully designed morphology and elemental distribution to achieve their functionalities. Among the few experimental techniques that can directly visualise the 3D elemental distribution on the nanoscale are approaches based on electron tomography in combination with energy-dispersive X-ray spectroscopy (EDXS) and electron energy loss spectroscopy (EELS). Unfortunately, these highly informative methods are severely limited by the fundamentally low signal-to-noise ratio, which makes long experimental times and high electron irradiation doses necessary to obtain reliable 3D reconstructions. Addressing these limitations has been the major research question for the development of these techniques in recent years. This short review outlines the latest progress on the methods to reduce experimental time and electron irradiation dose requirements for 3D elemental distribution analysis and gives an outlook on the development of this field in the near future.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos	000910532600001	Publication Date	2022-12-26
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0022-2720	ISBN		Additional Links	UA library record; WoS full record; WoS citing articles
	Impact Factor	2	Times cited	2	Open Access	OpenAccess
	Notes	ERC Consolidator Grant, Grant/Award Number: 815128			Approved	Most recent IF: 2; 2023 IF: 1.692
	Call Number	UA @ admin @ c:irua:193428			Serial	7281
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	Author	Kavak, S.; Kadu, A.A.; Claes, N.; Sánchez-Iglesias, A.; Liz-Marzán, L.M.; Batenburg, K.J.; Bals, S.
	Title	Quantitative 3D Investigation of Nanoparticle Assemblies by Volumetric Segmentation of Electron Tomography Data Sets			Type	A1 Journal Article
	Year	2023	Publication	The journal of physical chemistry: C : nanomaterials and interfaces	Abbreviated Journal
	Volume	127	Issue	20	Pages	9725-9734
	Keywords	A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT)
	Abstract	Morphological characterization of nanoparticle assemblies and hybrid nanomaterials is critical in determining their structure-property relationships as well as in the development of structures with desired properties. Electron tomography has become a widely utilized technique for the three-dimensional characterization of nanoparticle assemblies. However, the extraction of quantitative morphological parameters from the reconstructed volume can be a complex and labor-intensive task. In this study, we aim to overcome this challenge by automating the volumetric segmentation process applied to three-dimensional reconstructions of nanoparticle assemblies. The key to enabling automated characterization is to assess the performance of different volumetric segmentation methods in accurately extracting predefined quantitative descriptors for morphological characterization. In our methodology, we compare the quantitative descriptors obtained through manual segmentation with those obtained through automated segmentation methods, to evaluate their accuracy and effectiveness. To show generality, our study focuses on the characterization of assemblies of CdSe/CdS quantum dots, gold nanospheres and CdSe/CdS encapsulated in polymeric micelles, and silica-coated gold nanorods decorated with both CdSe/CdS or PbS quantum dots. We use two unsupervised segmentation algorithms: the watershed transform and the spherical Hough transform. Our results demonstrate that the choice of automated segmentation method is crucial for accurately extracting the predefined quantitative descriptors. Specifically, the spherical Hough transform exhibits superior performance in accurately extracting quantitative descriptors, such as particle size and interparticle distance, thereby allowing for an objective, efficient, and reliable volumetric segmentation of complex nanoparticle assemblies.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Wos	000991752700001	Publication Date	2023-05-25
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	1932-7447	ISBN		Additional Links	UA library record; WoS full record; WoS citing articles
	Impact Factor	3.7	Times cited	2	Open Access	OpenAccess
	Notes	Fonds Wetenschappelijk Onderzoek, 1181122N ; Horizon 2020 Framework Programme, 861950 ; H2020 European Research Council, 815128 ;			Approved	Most recent IF: 3.7; 2023 IF: 4.536
	Call Number	EMAT @ emat @c:irua:196971			Serial	8793
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