Medicine®, a Wolters Kluwer Health publication and one of the most respected and frequently cited journals in general medicine, is pleased to announce the launch of Medicine®: Radiology, an online channel of content specifically dedicated to the publication and curation of Radiology-related research within Medicine®.

Medicine®: Radiology will consider submissions in the following subject areas:

  • Diagnostic radiology
  • Interventional radiology
  • Medical physics
  • Nuclear medicine

Submissions will be published and indexed under the Medicine® ISSN.

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Temporal subtraction of low-dose and relatively thick-slice CT images with large deformation diffeomorphic metric mapping and adaptive voxel matching for detection of bone metastases: A STARD-compliant article

Tsuchiya, Mitsuteru; Masui, Takayuki; Katayama, Motoyuki; More

Medicine. 99(12):e19538, March 2020.

Added value of 18F-fluorocholine positron emission tomography-computed tomography in presurgical localization of hyperfunctioning parathyroid glands after dual tracer subtraction scintigraphy failure: A retrospective study of 47 patients

Morland, David; Lalire, Paul; Deguelte, Sophie; More

Medicine. 99(2):e18681, January 2020.

Nodules with nonspecific ultrasound pattern according to the 2015 American Thyroid Association malignancy risk stratification system: A comparison to the Thyroid Imaging Reporting and Data System (TIRADS-Na)

Xiang, Pingping; Chu, Xiaoqiu; Chen, Guofang; More

Medicine. 98(44):e17657, November 2019.

The accuracy of hippocampal volumetry and glucose metabolism for the diagnosis of patients with suspected Alzheimer's disease, using automatic quantitative clinical tools

Ferrari, Bruna Letícia; Neto, Guilherme de Carvalho Campos; Nucci, Mariana Penteado; More

Medicine. 98(45):e17824, November 2019.

Contrast enhancement on 100- and 120 kVp hepatic CT scans at thin adults in a retrospective cohort study: Bayesian inference of the optimal enhancement probability

Masuda, Takanori; Nakaura, Takeshi; Funama, Yoshinori; More

Medicine. 98(47):e17902, November 2019.

Application of deep learning (3-dimensional convolutional neural network) for the prediction of pathological invasiveness in lung adenocarcinoma: A preliminary study

Yanagawa, Masahiro; Niioka, Hirohiko; Hata, Akinori; More

Medicine. 98(25):e16119, June 2019.