TY - GEN
T1 - Hyperquadrics for shape analysis of 3D nanoscale reconstructions of brain cell nuclear envelopes
AU - Agus, M.
AU - Calì, C.
AU - Tapia Morales, A.
AU - Lehväslaiho, H. O.
AU - Magistretti, P. J.
AU - Gobbetti, E.
AU - Hadwiger, M.
N1 - Funding Information:
Acknowledgments. This work was supported by the CRG grant no.2313 from King Abdullah University of Science and Technology KAUST-EPFL Alliance for Integrative Modeling of Brain Energy Metabolism. We also acknowledge the contribution of Sardinian Regional Authorities under project VIGEC.
Publisher Copyright:
© 2018 The Eurographics Association.
PY - 2018
Y1 - 2018
N2 - Shape analysis of cell nuclei is becoming increasingly important in biology and medicine. Recent results have identified that the significant variability in shape and size of nuclei has an important impact on many biological processes. Current analysis techniques involve automatic methods for detection and segmentation of histology and microscopy images, and are mostly performed in 2D. Methods for 3D shape analysis, made possible by emerging acquisition methods capable to provide nanometric-scale 3D reconstructions, are, however, still at an early stage, and often assume a simple spherical shape. We introduce here a framework for analyzing 3D nanoscale reconstructions of nuclei of brain cells (mostly neurons), obtained by semiautomatic segmentation of electron micrographs. Our method considers an implicit parametric representation customizing the hyperquadrics formulation of convex shapes. Point clouds of nuclear envelopes, extracted from image data, are fitted to our parametrized model, which is then used for performing statistical analysis and shape comparisons. We report on the preliminary analysis of a collection of 92 nuclei of brain cells obtained from a sample of the somatosensory cortex of a juvenile rat.
AB - Shape analysis of cell nuclei is becoming increasingly important in biology and medicine. Recent results have identified that the significant variability in shape and size of nuclei has an important impact on many biological processes. Current analysis techniques involve automatic methods for detection and segmentation of histology and microscopy images, and are mostly performed in 2D. Methods for 3D shape analysis, made possible by emerging acquisition methods capable to provide nanometric-scale 3D reconstructions, are, however, still at an early stage, and often assume a simple spherical shape. We introduce here a framework for analyzing 3D nanoscale reconstructions of nuclei of brain cells (mostly neurons), obtained by semiautomatic segmentation of electron micrographs. Our method considers an implicit parametric representation customizing the hyperquadrics formulation of convex shapes. Point clouds of nuclear envelopes, extracted from image data, are fitted to our parametrized model, which is then used for performing statistical analysis and shape comparisons. We report on the preliminary analysis of a collection of 92 nuclei of brain cells obtained from a sample of the somatosensory cortex of a juvenile rat.
UR - http://www.scopus.com/inward/record.url?scp=85075489574&partnerID=8YFLogxK
U2 - 10.2312/stag.20181304
DO - 10.2312/stag.20181304
M3 - Conference contribution
AN - SCOPUS:85075489574
T3 - Italian Chapter Conference 2018 - Smart Tools and Apps in Computer Graphics, STAG 2018
SP - 115
EP - 122
BT - Italian Chapter Conference 2018 - Smart Tools and Apps in Computer Graphics, STAG 2018
A2 - Signoroni, Alberto
A2 - Livesu, Marco
A2 - Agus, Marco
PB - Eurographics Association
T2 - 2018 Italian Chapter Conference - Smart Tools and Apps in Computer Graphics, STAG 2018
Y2 - 18 October 2018 through 19 October 2018
ER -