作者: Chris R. Johnson , Xavier Tricoche
DOI: 10.1016/B978-0-444-53075-2.00006-X
关键词: Physical phenomena 、 Clinical Practice 、 Scientific visualization 、 Artificial intelligence 、 Salient 、 Computer science 、 Data science 、 Biomedicine 、 Visualization 、 Field (computer science)
摘要: Publisher Summary This chapter presents an overview of the techniques devised by scientific visualization research to address specific needs biomedical applications. Computers have become indispensable and clinical practice biomedicine. Their widespread use now permits manipulation massive amounts measured data, as well as, study sophisticated models through numerical simulations. The rapidly growing size complexity resulting information from experiments or simulations creates a challenging demand on tools needed derive knowledge insight data. Scientific offers very powerful approach tackle this data analysis challenge creating visual representations that convey salient properties large sets permit their effective interpretation analysis. field is focused images about underlying processes. In past three decades, there has been unprecedented growth in computational acquisition technologies, resulted increased ability both sense physical world precise detail model simulate complex phenomena. As such, plays crucial role our comprehend such data—data which, two, three, more dimensions, into diverse applications understanding bioelectric currents within heart, characterizing white matter tracts diffusion tensor imaging, morphology differences between different genetic mice phenotypes, among many others.