Purpose: Y selective internal radiation therapy (SIRT) has become a safe and effective treatment option for liver cancer. However, segmentation of target and organ-at-risks is labor-intensive and time-consuming in Y SIRT planning. In this study, we developed a convolutional neural network (CNN)-based method for automated lungs, liver, and tumor segmentation on Tc-MAA SPECT/CT images for Y SIRT planning.
View Article and Find Full Text PDFObjective: To compare sensitivity, specificity, accuracy and diagnostic confidence in the differentiation between benign and metastatic bone lesions on whole body planar bone scintigraphy and Evolution SPECT/CT.
Material And Method: Eighty diagnosed or suspected cancer patients with indeterminate lesions on planar scintigraphy were recruited in the present prospective study. Additional whole body Evolution SPECT/CT was performed after whole body planar scintigraphy.
The value of Tc-99m MIBI parathyroid SPECT for localizing parathyroid hyperplasia in chronic renal failure patients remains inconclusive due to limited image quality. Advanced reconstruction methods to improve image quality have been developed but require optimization and evaluation. The goal of this study was to optimize and evaluate compensation methods and reconstruction parameters for Tc-99m MIBI parathyroid SPECT.
View Article and Find Full Text PDFObjective: The purpose of the study was to study factors affecting SUV of PET imaging with 18F-FDG.
Material And Method: PET/CT Biograph 64 was used to acquire the data. A NEMA PET phantom with 6 spheres varying in diameter from 10 to 37 mm was used to mimic the human body and tumors.
Objective: The purpose of this study was to investigate the effect of attenuation correction (AC) on lesion detection for a hybrid PET system.
Material And Method: Experimental list-mode data were acquired from hot spheres inside a uniform cylindrical phantom with an elliptical cross-section using a Siemens E. CAM+ dual-camera hybrid PET system.