Tethered capsule detects GI tract disease February 26, 2016 -- A method for imaging and characterizing the esophageal wall using a tethered capsule has been developed by researchers from Harvard Medical School and Strasbourg University. The technology may provide a simple and convenient method for diagnosing upper gastrointestinal (GI) tract diseases.
3D printing of human organs on horizon February 23, 2016 -- Investigators are envisioning a brave new world in which functional 3D-printed organs can be manufactured at low cost for implantation in patients -- provided several tough obstacles can be overcome, concludes new research from a top London institution.
CAD finds breast cancer on negative DCE-MRI February 23, 2016 -- A study using a new computer-aided detection (CAD) algorithm found breast cancers in women whose dynamic contrast-enhanced (DCE) MRI breast exams were thought to be negative, conclude authors in European Journal of Radiology.
Volumetric CT beats RECIST in therapy response February 22, 2016 -- Three-dimensional volumetric measurements of lung cancer tumors are better predictors of survival than conventional Response Evaluation Criteria in Solid Tumors (RECIST) measurements, according to a new study published by the European Journal of Radiology.
Quantitative ultrasound method stages fatty liver February 16, 2016 -- A computer-aided ultrasound technique can be used to stage liver steatosis, or fatty liver, offering high correlation with fat measurements produced from MR spectroscopy, according to a pilot study from Radboud University Medical Center in Nijmegen, the Netherlands.
Holoxica wins funding for video display project February 10, 2016 -- Holographic imaging firm Holoxica has received 1.3 million euros from the European Commission's Horizon 2020 Small and Medium-sized Enterprises initiative to develop a holographic video display for medical scanners.
Fraunhofer MEVIS eyes deep learning for medical imaging February 3, 2016 -- The Fraunhofer Institute for Medical Image Computing (MEVIS) in Germany is teaming with Radboud University in Nijmegen, the Netherlands, on a project that will deploy deep-learning computer algorithms to improve the accuracy of computer-generated diagnoses.