New Cervical Cancer Research from Yonsei University College of Medicine Described (Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT).

Předmět:	MAGNETIC resonance imaging COMPUTED tomography CERVICAL cancer CANCER patients CANCER research DICOM (Computer network protocol)
Zdroj:	Women's Health Weekly; 5/2/2024, p535-535, 1p
Abstrakt:	A recent study conducted by Yonsei University College of Medicine investigated the clinical feasibility of using deep learning-based synthetic CT images for cervical cancer patients. The study compared these synthetic images to MR images for calculating attenuation. The researchers used a patient cohort of 50 pairs of T2-weighted MR and CT images, with 40 images used for training and 10 for testing. The results showed that the synthetic CT images generated by deep learning outperformed the MR-based attenuation correction images in terms of image similarity and dosimetry similarity. This research provides valuable insights into the potential use of deep learning in improving cervical cancer treatment. [Extracted from the article]
Databáze:	Complementary Index
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