Zhiqing Zhang1,2, Nikolay V Kuzmin1,3, Marie Louise Groot1,3, Jan C de Munck4. 1. LaserLab Amsterdam, Department of Physics, Faculty of Sciences, VU University, HV Amsterdam, The Netherlands. 2. Physics and Medical Technology Department, VU University Medical Center, HZ Amsterdam, The Netherlands. 3. Neuroscience Campus Amsterdam, VU University, HV Amsterdam, The Netherlands. 4. Physics and Medical Technology Department, VU University Medical Center, ?HZ Amsterdam, The Netherlands.
Abstract
MOTIVATION: 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. RESULTS: 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-brain 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. AVAILABILITY AND IMPLEMENTATION: The software and test datasets are available from the authors. CONTACT: z.zhang@vu.nl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: 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. RESULTS: 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-brain 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. AVAILABILITY AND IMPLEMENTATION: The software and test datasets are available from the authors. CONTACT: z.zhang@vu.nl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Zhiqing Zhang; Jan C de Munck; Niels Verburg; Annemieke J Rozemuller; Willem Vreuls; Pinar Cakmak; Laura M G van Huizen; Sander Idema; Eleonora Aronica; Philip C de Witt Hamer; Pieter Wesseling; Marie Louise Groot Journal: Adv Sci (Weinh) Date: 2019-04-05 Impact factor: 16.806
Authors: Laura M G van Huizen; Teodora Radonic; Frank van Mourik; Danielle Seinstra; Chris Dickhoff; Johannes M A Daniels; Idris Bahce; Jouke T Annema; Marie Louise Groot Journal: Transl Biophotonics Date: 2020-08-21
Authors: Laura M G van Huizen; Nikolay V Kuzmin; Ellis Barbé; Susanne van der Velde; Elisabeth A Te Velde; Marie Louise Groot Journal: J Biophotonics Date: 2019-03-21 Impact factor: 3.207