Generation of short-term follow-up chest CT images using a latent diffusion model in COVID-19

Purpose Despite a global decrease in the number of COVID-19 patients, early prediction of the clinical course for optimal patient care remains challenging. Recently, the usefulness of image generation for medical images has been investigated. This study aimed to generate short-term follow-up chest C...

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Vydané v:	Japanese journal of radiology Ročník 43; číslo 4; s. 622 - 633
Hlavní autori:	Kawata, Naoko, Iwao, Yuma, Matsuura, Yukiko, Higashide, Takashi, Okamoto, Takayuki, Sekiguchi, Yuki, Nagayoshi, Masaru, Takiguchi, Yasuo, Suzuki, Takuji, Haneishi, Hideaki
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Singapore Springer Nature Singapore 01.04.2025 Springer Nature B.V
Predmet:	Adult Aged Chest Coders Computed tomography COVID-19 COVID-19 - diagnostic imaging Cross correlation Diffusion Diffusion models Female Follow-Up Studies Humans Image processing Imaging Lung - diagnostic imaging Male Medical imaging Medicine Medicine & Public Health Middle Aged Nuclear Medicine Original Original Article Parameters Patients Pneumonia Radiographic Image Interpretation, Computer-Assisted - methods Radiography, Thoracic - methods Radiology Radiomics Radiotherapy Respiratory diseases Retrospective Studies SARS-CoV-2 Signal to noise ratio Similarity Tomography, X-Ray Computed - methods Training COVID-19 Deep learning Chest CT images Prognostic image generation Latent diffusion model
ISSN:	1867-1071, 1867-108X, 1867-108X
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