{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T18:52:33Z","timestamp":1759776753095},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2017,1,27]],"date-time":"2017-01-27T00:00:00Z","timestamp":1485475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The morphologies contained in 3D third harmonic generation (THG) images of human brain tissue can report on the pathological state of the tissue. However, the complexity of THG brain images makes the usage of modern image processing tools, especially those of image filtering, segmentation and validation, to extract this information challenging.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We developed a salient edge-enhancing model of anisotropic diffusion for image filtering, based on higher order statistics. We split the intrinsic 3-phase segmentation problem into two 2-phase segmentation problems, each of which we solved with a dedicated model, active contour weighted by prior extreme. We applied the novel proposed algorithms to THG images of structurally normal ex-vivo human brain tissue, revealing key tissue components\u2014brain cells, microvessels and neuropil, enabling statistical characterization of these components. Comprehensive comparison to manually delineated ground truth validated the proposed algorithms. Quantitative comparison to second harmonic generation\/auto-fluorescence images, acquired simultaneously from the same tissue area, confirmed the correctness of the main THG features detected.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and Implementation<\/jats:title>\n                  <jats:p>The software and test datasets are available from the authors.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx035","type":"journal-article","created":{"date-parts":[[2017,1,28]],"date-time":"2017-01-28T01:25:31Z","timestamp":1485566731000},"page":"1712-1720","source":"Crossref","is-referenced-by-count":11,"title":["Extracting morphologies from third harmonic generation images of structurally normal human brain tissue"],"prefix":"10.1093","volume":"33","author":[{"given":"Zhiqing","family":"Zhang","sequence":"first","affiliation":[{"name":"LaserLab Amsterdam, Department of Physics, Faculty of Sciences, VU University, HV Amsterdam, The Netherlands"},{"name":"Physics and Medical Technology Department, VU University Medical Center, \u2009HZ Amsterdam, The Netherlands"}]},{"given":"Nikolay V","family":"Kuzmin","sequence":"additional","affiliation":[{"name":"LaserLab Amsterdam, Department of Physics, Faculty of Sciences, VU University, HV Amsterdam, The Netherlands"},{"name":"Neuroscience Campus Amsterdam, VU University, HV Amsterdam, The Netherlands"}]},{"given":"Marie Louise","family":"Groot","sequence":"additional","affiliation":[{"name":"LaserLab Amsterdam, Department of Physics, Faculty of Sciences, VU University, HV Amsterdam, The Netherlands"},{"name":"Neuroscience Campus Amsterdam, VU University, HV Amsterdam, The Netherlands"}]},{"given":"Jan C","family":"de Munck","sequence":"additional","affiliation":[{"name":"Physics and Medical Technology Department, VU University Medical Center, \u2009HZ Amsterdam, The Netherlands"}]}],"member":"286","published-online":{"date-parts":[[2017,1,27]]},"reference":[{"key":"2023020205303547800_btx035-B1","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1137\/120867068","article-title":"A two-stage image segmentation method using a convex variant of the Mumford\u2013Shah model and thresholding","volume":"6","author":"Cai","year":"2013","journal-title":"SIAM J. 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