Classification of the Multiple Stages of Parkinson’s Disease by a Deep Convolution Neural Network Based on 99mTc-TRODAT-1 SPECT Images

• Published in: Molecules (Basel, Switzerland) Vol. 25; no. 20; p. 4792
• Main Authors: Hsu, Shih-Yen, Yeh, Li-Ren, Chen, Tai-Been, Du, Wei-Chang, Huang, Yung-Hui, Twan, Wen-Hung, Lin, Ming-Chia, Hsu, Yun-Hsuan, Wu, Yi-Chen, Chen, Huei-Yung
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 19.10.2020; MDPI
• Subjects: Algorithms; Classification; convolution neural network; Deep learning; Dopamine; Neural networks; Nuclear medicine; Parkinson's disease; Patients; SPECT; United States > US

Single photon emission computed tomography (SPECT) has been employed to detect Parkinson’s disease (PD). However, analysis of the SPECT PD images was mostly based on the region of interest (ROI) approach. Due to limited size of the ROI, especially in the multi-stage classification of PD, this study...