Correction to: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes (European Journal of Nuclear Medicine and Molecular Imaging, (2019), 10.1007/s00259-019-04663-3)

Jun Pyo Kim, Jeonghun Kim, Yeshin Kim, Seung Hwan Moon, Yu Hyun Park, Sole Yoo, Hyemin Jang, Hee Jin Kim, Duk L. Na, Sang Won Seo, Joon Kyung Seong

Research output: Contribution to journalComment/debate

Abstract

The Table 2 in the original version of this article contained a mistake in the alignment. Correct Table 2 presentation is presented here. The original article has been corrected.

Original languageEnglish
JournalEuropean Journal of Nuclear Medicine and Molecular Imaging
DOIs
Publication statusAccepted/In press - 2020 Jan 1

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Correction to: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes (European Journal of Nuclear Medicine and Molecular Imaging, (2019), 10.1007/s00259-019-04663-3)'. Together they form a unique fingerprint.

  • Cite this