34 citations · 34 across the 1 of their papers we have counts for
3 papers
cs.CV2018
Joint Correction of Attenuation and Scatter Using Deep Convolutional Neural Networks (DCNN) for Time-of-Flight PET
Jaewon Yang, Dookun Park, Jae Ho Sohn +3
Deep convolutional neural networks (DCNN) have demonstrated its capability to convert MR image to pseudo CT for PET attenuation correction in PET/MRI. Conventionally, attenuated ev…
cs.CV2017★ 34 cited
Iterative PET Image Reconstruction Using Convolutional Neural Network Representation
Kuang Gong, Jiahui Guan, Kyungsang Kim +4
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons. Recently deep neural networks have been widely and su…
astro-ph2001
ZEPLIN IV: A 1-Ton Very Sensitive ZEPLIN II Extension for SUSY Dark Matter
David B. Cline, Hanguo Wang, Y. Seo
We present a concept of a one ton two-phase liquid Xenon detector based on the concept of the ZEPLIN II detector currently under construction by a UCLA/Torino/UKDM team. The ZEPLIN…