%0 Conference Paper %B Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 %D 2020 %T Learning Guided Electron Microscopy with Active Acquisition %A Mi, Lu %A Wang, Hao %A Meirovitch, Yaron %A Richard Schalek %A Turaga, Srinivas C. %A Lichtman, Jeff W. %A Aravinthan D. T. Samuel %A Shavit, Nir %E Anne L. Martel %E Abolmaesumi, Purang %E Stoyanov, Danail %E Mateus, Diana %E Zuluaga, Maria A. %E Zhou, S. Kevin %E Racoceanu, Daniel %E Joskowicz, Leo %X Single-beam scanning electron microscopes (SEM) are widely used to acquire massive datasets for biomedical study, material analysis, and fabrication inspection. Datasets are typically acquired with uniform acquisition: applying the electron beam with the same power and duration to all image pixels, even if there is great variety in the pixels' importance for eventual use. Many SEMs are now able to move the beam to any pixel in the field of view without delay, enabling them, in principle, to invest their time budget more effectively with non-uniform imaging. %B Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 %I Springer International Publishing %C Cham %P 77–87 %@ 978-3-030-59722-1 %G eng %U https://link.springer.com/chapter/10.1007%2F978-3-030-59722-1_8