Synthesizing Ct from Mri with Cycle-Consistent Generative Adversarial Networks for Prostate Tumor Radiotherapy Treatment Planning

Weng, Jun-Cheng (PI)
Lin, Gigin (CoPI)
Wang, Chun Chieh (CoPI)

Department of Medical Imaging and Radiological Sciences

Project: National Science and Technology Council › National Science and Technology Council Academic Grants

Abstract

We will develop cycle-consistent generative adversarial net (cycleGAN) approaches for magnetic resonance imaging-based attenuation correction (MRAC) in pelvic MR imaging, and evaluate the feasibility of MRAC on MR simulation for radiation therapy treatment planning of prostate tumor patients.

Project IDs

Project ID:PB11407-11785
External Project ID:NSTC112-2221-E182-013-MY3

Status	Active
Effective start/end date	01/08/25 → 31/07/26

Keywords

deep learning
cycle-consistent generative adversarial net (cycleGAN)
attenuation correction
MR-only simulation
radiotherapy planning
prostate tumor

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https://www.grb.gov.tw/search/planDetail?id=17945455

Synthesizing Ct from Mri with Cycle-Consistent Generative Adversarial Networks for Prostate Tumor Radiotherapy Treatment Planning

Project Details

Abstract

Project IDs

Keywords

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