If you made any changes in Pure these will be visible here soon.

Fingerprint Dive into the research topics where Koichi Oshio is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 1 Similar Profiles
Echo-Planar Imaging Medicine & Life Sciences
Magnetic Resonance Imaging Medicine & Life Sciences
Protons Medicine & Life Sciences
Fats Medicine & Life Sciences
Water Medicine & Life Sciences
echoes Physics & Astronomy
Imaging techniques Chemical Compounds
Temperature Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1989 2018

  • 2360 Citations
  • 24 h-Index
  • 75 Article
  • 2 Conference contribution

Quantification of edematous changes by diffusion magnetic resonance imaging in gastrocnemius muscles after spinal nerve ligation

Abe, K., Nakamura, T., Yamabe, E., Oshio, K., Miyamoto, T., Nakamura, M., Matsumoto, M. & Satou, K., 2018 Feb 1, In : PLoS One. 13, 2, e0193306.

Research output: Contribution to journalArticle

Complex Regional Pain Syndromes
Spinal Nerves
Diffusion Magnetic Resonance Imaging
Magnetic resonance
magnetic resonance imaging
4 Citations (Scopus)
Echo-Planar Imaging
Signal Transduction
4 Citations (Scopus)

Diffusion-weighted MR imaging for the assessment of renal function: Analysis using statistical models based on truncated gaussian and gamma distributions

Yamada, K., Shinmoto, H., Oshio, K., Ito, S., Kumagai, H. & Kaji, T., 2016 Apr 11, In : Magnetic Resonance in Medical Sciences. 15, 2, p. 237-245 9 p.

Research output: Contribution to journalArticle

Diffusion Magnetic Resonance Imaging
Normal Distribution
Statistical Models
Glomerular Filtration Rate
Kidney

Removing ambiguity caused by T2 shine-through using weighted diffusion subtraction (WDS)

Oshio, K., Okuda, S. & Shinmoto, H., 2016, In : Magnetic Resonance in Medical Sciences. 15, 1, p. 146-148 3 p.

Research output: Contribution to journalArticle

7 Citations (Scopus)

Diffusion-weighted imaging of prostate cancer using a statistical model based on the gamma distribution

Shinmoto, H., Oshio, K., Tamura, C., Soga, S., Okamura, T., Yamada, K., Kaji, T. & Mulkern, R. V., 2015 Jul 1, In : Journal of Magnetic Resonance Imaging. 42, 1, p. 56-62 7 p.

Research output: Contribution to journalArticle

Statistical Models
Prostatic Neoplasms
Prostatic Hyperplasia
Diffusion Magnetic Resonance Imaging
Prostate