The Journal of Medical Imaging covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal.
Editor-in-Chief: Maryellen L. Giger, The University of Chicago
Tissue classification in intercostal and paravertebral ultrasound using spectral analysis of radiofrequency backscatter
J.D. Klingensmith et al.
Heuristic neural network approach in histological sections detection of hydatidiform mole
P. Palee et al.
SLICR super-voxel algorithm for fast, robust quantification of myocardial blood flow by dynamic computed tomography myocardial perfusion imaging
H. Wu et al.
September 2019
Top Downloads
from the Journal of Medical Imaging
Applied Medical Image Processing, Second Edition: A Basic Course
Karen Drukker (2014)
History and future technical innovation in positron emission tomography
Terry Jones, David W. Townsend (2017)
Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens
Masahiro Ishikawa et. al (2016)
LUNGx Challenge for computerized lung nodule classification
Samuel G. Armato et al. (2016)
MARIA M4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detection
Alan W. Preece, Ian Craddock, Mike Shere, Lyn Jones, Helen L. Winton (2016)
Automatic extraction of cell nuclei from H&E-stained histopathological images
Faliu Yi, Junzhou Huang, Lin Yang, Yang Xie, Guanghua Xiao (2017)
Improved pulmonary nodule classification utilizing quantitative lung parenchyma features
Samantha K. Dilger et al. (2015)
Review of quantitative multiscale imaging of breast cancer
Michael A. Pinkert, Lonie R. Salkowski, Patricia J. Keely, Timothy J. Hall, Walter F. Block, Kevin W. Eliceiri (2018)
Global image registration using a symmetric block-matching approach
Marc Modat, David M. Cash, Pankaj Daga, Gavin P. Winston, John S. Duncan, Sébastien Ourselin (2014)
Prostate cancer diagnosis: the feasibility of needle-based optical coherence tomography
Berrend G. Muller et al. (2015)
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