Super-resolution reconstruction for early cervical cancer magnetic resonance imaging based on deep learning

Abstract This study aims to develop a super-resolution (SR) algorithm tailored specifically for enhancing the image quality and resolution of early cervical cancer (CC) magnetic resonance imaging (MRI) images. The proposed method is subjected to both qualitative and quantitative analyses, thoroughly...

وصف كامل

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Chunxia Chen, Liu Xiong, Yongping Lin, Ming Li, Zhiyu Song, Jialin Su, Wenting Cao
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	BMC 2024-08-01
سلاسل:	BioMedical Engineering OnLine
الموضوعات:	Computer-aided diagnosis Deep learning Magnetic resonance imaging Uterine cavity line
الوصول للمادة أونلاين:	https://doi.org/10.1186/s12938-024-01281-5
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!