Complete Female 3D Human Skeleton Model Available on PhysiomeSpace

Ortopedico Rizzoli in Bologna (Italy) announced 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 www.physiomespace.com/ps_home and freely used for no profit research purposes under the LHDL license agreement www.physiomespace.com/public/LHDLdata_Licence. 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.

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 www.physiomespace.com/access.

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 project (www.livinghuman.org, 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 PhysiomeSpace, 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-attached 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 http://www.biomedtown.org/biomed_town/LHDL/Reception/lhp-public-repository/public_D/plfng_view.

A complete description of the methods used to collect the various data types can be found http://www.biomedtown.org/biomed_town/LHDL/Reception/collection/.

Most Popular Now

Is AI in Medicine Playing Fair?

As artificial intelligence (AI) rapidly integrates into health care, a new study by researchers at the Icahn School of Medicine at Mount Sinai reveals that all generative AI models may...

Generative AI's Diagnostic Capabili…

The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were...

New System for the Early Detection of Au…

A team from the Human-Tech Institute-Universitat Politècnica de València has developed a new system for the early detection of Autism Spectrum Disorder (ASD) using virtual reality and artificial intelligence. The...

AI Tool can Track Effectiveness of Multi…

A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by UCL researchers. AI uses...

Diagnoses and Treatment Recommendations …

A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations...

Dr Jason Broch Joins the Highland Market…

The Highland Marketing advisory board has welcomed a new member - Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation. Dr Broch...

Surrey and Sussex Healthcare NHS Trust g…

Surrey and Sussex Healthcare NHS Trust has marked an important milestone in connecting busy radiologists across large parts of South East England, following the successful go live of Sectra's enterprise...

Multi-Resistance in Bacteria Predicted b…

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically...

DMEA 2025 Ends with Record Attendance an…

8 - 10 April 2025, Berlin, Germany. DMEA 2025 came to a successful close with record attendance and an impressive program. 20,500 participants attended Europe's leading digital health event over the...