Specific Binding Ratio Estimation of [¹²³I]-FP-CIT SPECT Using Frontal Projection Image and Machine Learning.

ABSTRACT: This study aimed to develop a new convolutional neural network (CNN) method for estimating the specific binding ratio (SBR) from only frontal projection images in single-photon emission-computed tomography using [¹²³I]ioflupane. We created five datasets to train two CNNs, LeNet and AlexNet: (1) 128FOV used a 0° projection image without preprocessing, (2) 40FOV used 0° projection images cropped to 40 × 40 pixels centered on the striatum, (3) 40FOV training data doubled by data augmentation (40FOV_DA, left-right reversal only), (4) 40FOVhalf, and (5) 40FOV_DAhalf, split into left and right (20 × 40) images of 40FOV and 40FOV_DA to separately evaluate the left and right SBR. The accuracy of the SBR estimation was assessed using the mean absolute error, root mean squared error, corr

SUBMITTER: Kita A 

PROVIDER: S-EPMC10137239 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature