Computer-aided diagnosis for (123I)FP-CIT imaging: impact on clinical reporting
Abstract Background For (123I)FP-CIT imaging, a number of algorithms have shown high performance in distinguishing normal patient images from those with disease, but none have yet been tested as part of reporting workflows. This study aims to evaluate the impact on reporters’ performance of a comput...
Main Authors: | Jonathan Christopher Taylor, Charles Romanowski, Eleanor Lorenz, Christine Lo, Oliver Bandmann, John Fenner |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2018-05-01
|
Series: | EJNMMI Research |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13550-018-0393-5 |
Similar Items
-
Comparison of machine learning and semi-quantification algorithms for (I123)FP-CIT classification: the beginning of the end for semi-quantification?
by: Jonathan Christopher Taylor, et al.
Published: (2017-11-01) -
123I-FP-CIT SPECT imaging in early diagnosis of dementia in patients with and without a vascular component
by: Marina eGarriga, et al.
Published: (2015-07-01) -
Case Report: Bupropion Reduces the [123I]FP-CIT Binding to Striatal Dopamine Transporter
by: Ivan Milenkovic, et al.
Published: (2021-02-01) -
Assessing Nigrostriatal Dopaminergic Pathways via 123I-FP-CIT SPECT in Dementia With Lewy Bodies in a Psychiatric Patient Cohort
by: Niels Hansen, et al.
Published: (2021-06-01) -
Serial I-123-FP-CIT SPECT Image Findings of Parkinson's Disease Patients With Levodopa-Induced Dyskinesia
by: Eun Hye Jeong, et al.
Published: (2018-12-01)