Hybrid Apparent Diffusion Coefficient (HADC) Map
Multiparametric MRI (mpMRI) is an established framework for prostate cancer assessment which includes T2-weighted magnetic resonance (T2w-MR) and diffusion weighted (DW) sequences. Low quality of Apparent Diffusion Coefficient (ADC) maps from the diffusion sequence can hinder such clinical assessment. Herein, we propose to generate Hybrid ADC (HADC) maps from high-quality T2w-MRI using “lesion-aware cycle-consistent generative adversarial network (LA-CGAN)”. Our produced HADC maps contain anatomical information from T2w-MR, and high intra-prostatic contrast of cancerous vs normal tissue, similar to the acquired ADC. Initial results have satisfied the expert radiologist in producing HADC. This work can considerably improve the quality of mpMRI combined assessment for prostate cancer detection.
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Generative Adversarial NetworkSimilar Papers 제목 키워드 기반
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