2021
DOI: 10.21203/rs.3.rs-721186/v1
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Artificial Intelligence-Based Assistance in Clinical 123I-FP-CIT SPECT Scan Interpretation

Abstract: Purpose: Dopamine transporter (DAT) imaging with 123I-FP-CIT SPECT is used to support the diagnosis of Parkinson’s disease (PD) in clinically uncertain cases. Previous studies showed that automatic classification of 123I‑FP‑CIT SPECT images (marketed as DaTSCAN) is feasible by using machine learning algorithms. However, these studies lacked sizable use of data from routine clinical practice. This study aims to contribute to the discussion whether artificial intelligence (AI) can be applied in clinical practice… Show more

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Cited by 2 publications
(2 citation statements)
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“…3. Analyze and train the images on DenseNet-121, CNN topologies with a soft attention block in addition to it, influenced by the works of Martínez-Murcia et al (2017) , Oliveira et al (2018) , and Wolfswinkel et al (2021) .…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…3. Analyze and train the images on DenseNet-121, CNN topologies with a soft attention block in addition to it, influenced by the works of Martínez-Murcia et al (2017) , Oliveira et al (2018) , and Wolfswinkel et al (2021) .…”
Section: Related Workmentioning
confidence: 99%
“…The region values of the putamen and caudate were then fetched to the ANN classifier for recognition. Wolfswinkel et al (2021) developed a convolutional neural network called DaTNet-3 to differentiate and classify normal and PD subjects that underwent the DaTSCAN procedure. They collected the imaging data from Parkinson's Progression Marker Initiative (PPMI) and a hospital-based dataset.…”
Section: Introductionmentioning
confidence: 99%