{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T11:49:34Z","timestamp":1793274574776,"version":"4.5.0"},"reference-count":42,"publisher":"International Union of Crystallography (IUCr)","issue":"11","license":[{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["101055413"],"award-info":[{"award-number":["101055413"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["iucr.org","wiley.com","iucrj.org"],"crossmark-restriction":true},"short-container-title":["Acta Crystallogr D Struct Biol","Acta Crystallogr D","Acta Cryst D","Acta Cryst D Struct Biol","Acta Cryst Sect D","Acta Cryst Sect D Struct Biol","Acta Crystallogr Sect D","Acta Crystallogr Sect D Struct Biol","Acta Crystallogr D Biol Crystallogr","Acta Cryst D Biol Cryst"],"accepted":{"date-parts":[[2026,9,25]]},"published-print":{"date-parts":[[2026,11,1]]},"abstract":"<jats:p>\n                    Cryo-electron tomography is an expanding technology for the study of macromolecules, viruses and cells. It is often applied to specimens that are too large or heterogeneous for methods based on 2D image averaging such as single-particle analysis, for example intracellular membranes or organelles. Current practice records a tilt series of projection images in rotation. Reconstruction is normally an ill-posed mathematical problem. Particularly for the under-determined case of sparse data, discrete tilt angles and a limited tilt range, characteristic artifacts appear in the reconstructed slices. Much of what appears as noise is in fact structural: the projection of contrast from different planes. Various schemes are employed to regularize the reconstruction, including machine-learning frameworks built on neural networks. To the extent that the noise is structural, based on the geometry of the tilt series, it might be suppressed by deconvolution with a suitable kernel. This was demonstrated and has been used regularly in cryo-STEM tomography of thick specimens where the under-sampling problem is particularly acute. Here, we present 3\n                    <jats:italic>dcon<\/jats:italic>\n                    as an open-source extension of the entropy-regularized deconvolution algorithm that had been adopted from fluorescence microscopy. It takes advantage of modern computing hardware for convenient and fast processing. Deconvolution is entirely algorithmic, meaning that successful processing of the data does not depend on the data itself. As such, it should be robust in a wide variety of applications.\n                  <\/jats:p>","DOI":"10.1107\/s205979832600999x","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T10:55:58Z","timestamp":1791370558000},"page":"1240-1250","update-policy":"https:\/\/doi.org\/10.1107\/cm_01","source":"Crossref","is-referenced-by-count":0,"title":["3\n                    <i>dcon<\/i>\n                    : tomogram denoising by deconvolution"],"prefix":"10.1107","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9162-9485","authenticated-orcid":true,"given":"Peter","family":"Kirchweger","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0101-2746","authenticated-orcid":true,"given":"Lev","family":"Melnikovsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3168-0577","authenticated-orcid":true,"given":"Shahar","family":"Seifer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7915-5512","authenticated-orcid":true,"given":"Michael","family":"Elbaum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"329","published-online":{"date-parts":[[2026,10,12]]},"reference":[{"key":"sor5008_bb99","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1093\/bioinformatics\/btq692","volume":"27","author":"Agulleiro","year":"2011","journal-title":"Bioinformatics"},{"key":"sor5008_bb98","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.jsb.2014.11.009","volume":"189","author":"Agulleiro","year":"2015","journal-title":"J. Struct. Biol."},{"key":"sor5008_bb1","doi-asserted-by":"crossref","unstructured":"Ansel, J., Yang, E., He, H., Gimelshein, N., Jain, A., Voznesensky, M., Bao, B., Bell, P., Berard, D., Burovski, E., Chauhan, G., Chourdia, A., Constable, W., Desmaison, A., DeVito, Z., Ellison, E., Feng, W., Gong, J., Gschwind, M., Hirsh, B., Huang, S., Kalambarkar, K., Kirsch, L., Lazos, M., Lezcano, M., Liang, Y., Liang, J., Lu, Y., Luk, C. K., Maher, B., Pan, Y., Puhrsch, C., Reso, M., Saroufim, M., Siraichi, M. Y., Suk, H., Zhang, S., Suo, M., Tillet, P., Zhao, X., Wang, E., Zhou, K., Zou, R., Wang, X., Mathews, A., Wen, W., Chanan, G., Wu, P. & Chintala, S. (2024). ASPLOS '24: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Vol. 2, pp. 929-947. New York: ACM.","DOI":"10.1145\/3620665.3640366"},{"key":"sor5008_bb2","doi-asserted-by":"crossref","first-page":"17344","DOI":"10.1073\/pnas.1315675110","volume":"110","author":"Arigovindan","year":"2013","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"sor5008_bb3","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.jsb.2009.02.012","volume":"166","author":"Baxter","year":"2009","journal-title":"J. Struct. Biol."},{"key":"sor5008_bb4","doi-asserted-by":"crossref","unstructured":"Buchholz, T.-O., Jordan, M., Pigino, G. & Jug, F. (2019). 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), pp. 502-506. Piscataway: IEEE.","DOI":"10.1109\/ISBI.2019.8759519"},{"key":"sor5008_bb5","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/bs.mcb.2019.05.001","volume":"152","author":"Buchholz","year":"2019","journal-title":"Methods Cell Biol."},{"key":"sor5008_bb6","unstructured":"Carazo, J.-M., Herman, G. T., Sorzano, C. O. S. & Marabini, R. 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