A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI

Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation of the prostate is a crucial step of CAD for prostate cancer, but visual inspect...

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מידע ביבליוגרפי

Principais autores:	Mohammed R. S. Sunoqrot, Kirsten M. Selnæs, Elise Sandsmark, Gabriel A. Nketiah, Olmo Zavala-Romero, Radka Stoyanova, Tone F. Bathen, Mattijs Elschot
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2020-09-01
סדרה:	Diagnostics
נושאים:	prostate segmentation deep learning radiomics quality control computer-aided detection and diagnosis
גישה מקוונת:	https://www.mdpi.com/2075-4418/10/9/714
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!