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Proceedings Paper

Automatic segmentation and 3D feature extraction of protein aggregates in caenorhabditis elegans
Author(s): Pedro L. Rodrigues; António H. J. Moreira; Andreia Teixeira-Castro; João Oliveira; Nuno Dias; Nuno F. Rodrigues; João L. Vilaça
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Paper Abstract

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals' transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey's biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention.

Paper Details

Date Published: 13 April 2012
PDF: 7 pages
Proc. SPIE 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging, 83170K (13 April 2012); doi: 10.1117/12.911567
Show Author Affiliations
Pedro L. Rodrigues, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
António H. J. Moreira, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
Andreia Teixeira-Castro, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
João Oliveira, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
Nuno Dias, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
DIGARC, Instituto Politécnico do Cávado e do Ave (Portugal)
Nuno F. Rodrigues, DIGARC, Instituto Politécnico do Cávado e do Ave (Portugal)
HASLab / INESC TEC, Univ. of Minho (Portugal)
João L. Vilaça, Life and Health Sciences Research Institute, Univ. of Minho (Portugal)
ICVS/3B's - PT Government Associate Lab. (Portugal)
DIGARC, Instituto Politécnico do Cávado e do Ave (Portugal)


Published in SPIE Proceedings Vol. 8317:
Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging
Robert C. Molthen; John B. Weaver, Editor(s)

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