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Three‐dimensional volume reconstruction of extracellular matrix proteins in uveal melanoma from fluorescent confocal laser scanning microscope images
Author(s) -
BAJCSY P.,
LEE SC.,
LIN A.,
FOLBERG R.
Publication year - 2006
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2006.01539.x
Subject(s) - confocal , confocal microscopy , artificial intelligence , biomedical engineering , computer vision , computer science , optical coherence tomography , microscopy , optics , materials science , medicine , physics
Summary The distribution of looping patterns of laminin in uveal melanomas and other tumours has been associated with adverse outcome. Moreover, these patterns are generated by highly invasive tumour cells through the process of vasculogenic mimicry and are not therefore blood vessels. Nevertheless, these extravascular matrix patterns conduct plasma. The three‐dimensional (3D) configuration of these laminin‐rich patterns compared with blood vessels has been the subject of speculation and intensive investigation. We have developed a method for the 3D reconstruction of volume for these extravascular matrix proteins from serial paraffin sections cut at 4 µm thicknesses and stained with a fluorescently labelled antibody to laminin (Maniotis et al ., 2002). Each section was examined via confocal laser‐scanning focal microscopy (CLSM) and 13 images were recorded in the Z ‐dimension for each slide. The input CLSM imagery is composed of a set of 3D subvolumes (stacks of 2D images) acquired at multiple confocal depths, from a sequence of consecutive slides. Steps for automated reconstruction included (1) unsupervised methods for selecting an image frame from a subvolume based on entropy and contrast criteria, (2) a fully automated registration technique for image alignment and (3) an improved histogram equalization method that compensates for spatially varying image intensities in CLSM imagery due to photo‐bleaching. We compared image alignment accuracy of a fully automated method with registration accuracy achieved by human subjects using a manual method. Automated 3D volume reconstruction was found to provide significant improvement in accuracy, consistency of results and performance time for CLSM images acquired from serial paraffin sections.