Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

Journal: Computational and mathematical methods in medicine

PMID: 34745329

Abstract

OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ureteral stones during pregnancy. We compare the clinical effect of ureteroscopy with double J tube placement on pregnancy complicated with ureteral stones and use medical imaging to diagnose the patient's condition and design a treatment plan.

Authors

Xiao-Yan Miao

Department of Radiation Oncology, The First People's Hospital of Fuyang (Fuyang First Affiliated Hospital of Zhejiang Chinese Medical University Ben Giang College), Hangzhou, China 311400.
Xiao-Nan Miao

Department of Endocrinology, The First People's Hospital of Fuyang (Fuyang First Affiliated Hospital of Zhejiang Chinese Medical University Ben Giang College), Hangzhou, China 311400.
Li-Yin Ye

Department of Urology, The First People's Hospital of Fuyang (Fuyang First Affiliated Hospital of Zhejiang Chinese Medical University Ben Giang College), Hangzhou, China 311400.
Hong Cheng

Department of Neurology, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China. ch8706@sohu.com.

Keywords

Artifacts Computational Biology Deep Learning Diagnosis, Computer-Assisted Female Humans Image Enhancement Lithotripsy Models, Statistical Neural Networks, Computer Pregnancy Pregnancy Complications Ultrasonography Ureteral Calculi Ureteroscopy

External Resources

View on PubMed Access via DOI PubMed (34745329)

Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

Abstract

Authors

Keywords

External Resources

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