View Full Version : Complete female 3D human skeleton model available on PhysiomeSpace

06-28-2010, 03:28 AM
Super Computing Solutions –SCS- and the
Computational Bioengineering Lab –BIC- by the
Istituto Ortopedico Rizzoli in Bologna (Italy)
are happy to announce the release of the first
dataset that composes the Living Human Digital
Library –LHDL- multiscale musculoskeletal data
collection. The data represent the
three-dimensional skeletal anatomy of the cadaver
of a 78 years old woman with normal morphology
(height: 171 cm, weight: 64 kg, from now on referred to as “LHDL_Donor1”).
From today the consortium will start releasing
various datasets with a cadence of two weeks. By
the end of the 2010 the entire LHDL multiscale
collection on LHDL_Donor1 will be made available.
The bone surfaces of LHDL_Donor1 were obtained
from the segmentation of whole body Computer
Tomography (CT) images, in three stages:
- A qualified technician performed gross segmentation;
- A senior anatomist performed a
refinement of the segmentation on all bones.
Joint surfaces were segmented in order to respect joint morphology;
- 3D polygonal surface models were
generated for the external surface of each bone.

The bone surfaces can be downloaded from the PhysiomeSpace service at
and freely used for no profit research purposes
under the LHDL license agreement
The service currently provides free accounts with
up to 1 Gb of on-line storage space. A license
for commercial use of the LHDL data collection is
also available. If you wish to have more
information on this matter please contact: bic@ior.it.
How to access the PhysiomeSpace resources:
To be able to access the LHDL multiscale collection, you firstly need to:
- register to the BiomedTown portal,
- subscribe to the PhysiomeSpace user group,
- install the PSLoader© client application.
For more detailed instructions, please read the
“How to get access to the service” section, at

You are now ready to download the data
repository. Go
to www.physiomespace.com/ps_home and:
- Search within the available data
resources and then add those you wish to download
to your basket, clicking on the shopping cart
icon next to it. Now you are ready to download the resource with PSLoader©- Open PSLoader© and authenticate,
inserting BT username and password.
- To finalise the download into
PSLoader©, follow this path:
Operations>Manage>Download from basket. Proceed
saving the data. A window called “Download from
basket” will open, listing the resources currently in your basket.
- At the end of the download process,
the downloaded data resources will appear in the
PSLoader© data tree, and you can start working on them.

About the LHDL project:
The Living Human Digital Library (LHDL) research
FP6-2004-ICT- 026932) was a STREP Project
co-funded by the European Commission's as part of
the 6th Framework Programme. The project, under
the scientific coordination of the Istituto
Ortopedico Rizzoli (IOR, Italy), ran for three
years from February 2006 to February 2009 and saw
the participation of the University of
Bedfordshire (U.K.), the Université Libre de
Bruxelles (ULB, Belgium), the Open University
(U.K.) and the CINECA Super Computing Centre (Italy).

About PhysiomeSpace:
On the basis of the technology developed during
the LHDL, CINECA spin-off Super Computing
Solutions (SCS) has recently started an
interactive digital library service, called
designed to manage and share with other
researchers large collection of heterogeneous
biomedical data such as medical imaging, motion
capture, biomedical instrumentation signals, finite element models, etc.

About the LHDL multiscale musculoskeletal data collection:
The first large data collection that will be
hosted by the PhysiomeSpace service is the LHDL
multiscale musculoskeletal data collection, that
when fully published will constitute one of the
most extensive data collection publicly available of this kind.
The collection, generated by researchers at ULB
and IOR, is based on two female cadavers obtained
from the ULB donation program, and on a group of
body-matched volunteers recruited at IOR.
The data collection includes:
- Body level: in vitro whole-body CT and
MRI scans were performed. From those imaging data
3D models of bones and muscles were obtained
through segmentation. In parallel, in-vivo motion
analyses (stereophotogrammetry, force plate
measurements, and electromyography) were
performed on volunteers, including two volunteers
that anthropometrically matched the two cadavers.
- Organ level: passive joint kinematics
was obtained using conventional
stereophotogrammetry with skeletal-attahced
frames. Full deep dissection of the cadavers made
it possible the digitization of various muscle
parameters (pennation angles, origin & insertion
location, etc.) and the measurement of muscle
mass and volume. Long bones were then dissected
and bone biomechanical properties measured (whole
bone stiffness, strain distribution, bone strength).
- Tissue level: bone properties were
further processed at tissue level by performing
microCT of cancellous bone biopsies taken from
various regions of the skeleton and by testing
the mechanical properties of both cortical and cancellous bone specimens.
- Cell level: Muscle sarcomere length
was obtained using a laser diffraction technique for various muscle biopsies.
- Constituent level: to quantify bone
structure at sub-tissue level, ash density,
collagen orientation, micro-hardness, chemical composition were measured.
What makes this collection unique is that all
data come from the same body, and are registered
in space one to each other into a multiscale
hierarchy defined in a unique global reference framework.
Full details on the LHDL Data collection can be found

A complete description of the methods used to
collect the various data types can be found


Giovanna Farinella, Martina Contin, Enrico
Schileo and Marco Viceconti for the
BioEngineering Computing Laboratory of Istituto
Ortopedico Rizzoli, Bologna, Italy

Giovanna Farinella
Biomedical Engineer
BioEngineering Computing Laboratory
Istituti Ortopedici Rizzoli
Via di Barbiano 1/10, 40126, Bologna (Italy)
tel +39-051-6366965
e-mail: farinella@tecno.ior.it or bic@ior.it