BioClinica and Rutgers University Announce Research Project Results
News Nov 23, 2013
Under the research project entitled 'Quantitative Tissue Assessment', scientific experts from BioClinica and Rutgers University worked together to define, direct and develop important quantitative tools for the clinical assessment of new therapies for muscle, liver and spleen diseases. These tools enable the extraction of quantitative data from medical images with increased automation and precision. The quantification of muscle tissue is becoming an increasingly important measurement in aging populations for assessing sarcopenia and other musculoskeletal diseases. Additionally, tools for the evaluation of liver and spleen are needed for clinical trials for non-alcoholic steato-hepatitis (NASH) and for a number of orphan diseases.
"These types of advances are the first steps in the application of big data that are being brought to bear on the diagnosis and development of new drugs in areas of unmet medical need" said Colin Miller PhD, Senior Vice President of Medical Affairs at BioClinica. The methods developed here will be put into production to facilitate the analysis of large imaging datasets that arise from ongoing global, multi-site clinical trials. "The Quantitative Tissue Assessment project underscores BioClinica's commitment to innovation in medical imaging" added David S. Herron, Executive Vice President at BioClinica and President of the company's Imaging Core Lab Division. "We are excited to partner with the CDDA on these strategic projects which have the potential to revolutionize big data computing for medical imaging".
On the heels of the success of the 'Quantitative Tissue Assessment' project, BioClinica and the CDDA have additional projects in the works, including the development of scalable algorithms for automated image analysis for additional therapeutic areas and unmet medical needs.
Scientists have used machine learning to train computers to see parts of the cell the human eye cannot easily distinguish. Using 3D images of fluorescently labeled cells, the research team taught computers to find structures inside living cells without fluorescent labels, using only black and white images generated by an inexpensive technique known as brightfield microscopy.READ MORE