  Quantitative image reconstruction in dual-energy computed tomography (CT)
remains a topic of active research. We read with interest ``DIRECT-Net: A
unified mutual-domain material decomposition network for quantitative
dual-energy CT imaging,'' which appears in the 2022 February Issue of Med Phys.
In the paper the authors propose a deep-learning (DL) method, referred to as
the Direct-Net method, to address the problem of quantitative image
reconstruction directly from data in full-scan dual-energy CT (DECT). We
comment on the study and conclusion in the paper. The Reply to this comment
appears under Communications on medphys.org:
https://www.medphys.org/Communications/Reply-Pan_Response-Su.pdf In order to
have context for the Reply, we provide the full text of our Comments.
