AUTHOR=Sherwani Moiz Khan , Gopalakrishnan Shyam 

TITLE=A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy

JOURNAL=Frontiers in Radiology

VOLUME=4

YEAR=2024

URL=https://www.frontiersin.org/journals/radiology/articles/10.3389/fradi.2024.1385742

DOI=10.3389/fradi.2024.1385742

ISSN=2673-8740

ABSTRACT=<p>The aim of this systematic review is to determine whether Deep Learning (DL) algorithms can provide a clinically feasible alternative to classic algorithms for synthetic Computer Tomography (sCT). The following categories are presented in this study: <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM1"><mml:mo>∙</mml:mo></mml:math></inline-formula> MR-based treatment planning and synthetic CT generation techniques. <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM2"><mml:mo>∙</mml:mo></mml:math></inline-formula> Generation of synthetic CT images based on Cone Beam CT images. <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM3"><mml:mo>∙</mml:mo></mml:math></inline-formula> Low-dose CT to High-dose CT generation. <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM4"><mml:mo>∙</mml:mo></mml:math></inline-formula> Attenuation correction for PET images. To perform appropriate database searches, we reviewed journal articles published between January 2018 and June 2023. Current methodology, study strategies, and results with relevant clinical applications were analyzed as we outlined the state-of-the-art of deep learning based approaches to inter-modality and intra-modality image synthesis. This was accomplished by contrasting the provided methodologies with traditional research approaches. The key contributions of each category were highlighted, specific challenges were identified, and accomplishments were summarized. As a final step, the statistics of all the cited works from various aspects were analyzed, which revealed that DL-based sCTs have achieved considerable popularity, while also showing the potential of this technology. In order to assess the clinical readiness of the presented methods, we examined the current status of DL-based sCT generation.</p>