Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis

Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis

The usefulness of sparse-sampling CT with deep learning-based reconstruction for detection of metastasis of malignant ovarian tumors was evaluated. We obtained contrast-enhanced CT images (<i>n</i> = 141) of ovarian cancers from a public database, whose images were randomly divided into...

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Bibliographic Details
Main Authors: Yasuyo Urase, Mizuho Nishio, Yoshiko Ueno, Atsushi K. Kono, Keitaro Sofue, Tomonori Kanda, Takaki Maeda, Munenobu Nogami, Masatoshi Hori, Takamichi Murakami
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Applied Sciences
Subjects:
deep learning
neoplasm metastasis
ovarian neoplasms
radiation exposure
tomography
x-ray computed
Online Access:https://www.mdpi.com/2076-3417/10/13/4446

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https://www.mdpi.com/2076-3417/10/13/4446

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