  The living body is composed of innumerable fine and complex structures and
although these structures have been studied in the past, a vast amount of
information pertaining to them still remains unknown. When attempting to
observe these ultra-structures, the use of electron microscopy (EM) has become
indispensable. However, conventional EM settings are limited to a narrow tissue
area that can bias observations. Recently, new trends in EM research have
emerged that provide coverage of far broader, nano-scale fields of view for
two-dimensional wide areas and three-dimensional large volumes. Together with
cutting-edge bioimage informatics conducted via deep learning, such techniques
have accelerated the quantification of complex morphological images. Moreover,
these advances have led to the comprehensive acquisition and quantification of
cellular morphology, which is now treated as a new omics science termed
'morphomics'. Moreover, by incorporating these new methodologies, the field of
traditional pathology is expected to advance, potentially with the
identification of previously unknown structures, quantification of rare events,
reclassification of diseases and automatic diagnosis of diseases. In this
review, we discuss these technological and analytical advances, which have
arisen from the need to analyse nano-scale bioimages, in detail, as well as
focusing on state-of-art image analysis involving deep learning.
