4.7 Article

A comparative study of auto-contouring softwares in delineation of organs at risk in lung cancer and rectal cancer

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Radiology, Nuclear Medicine & Medical Imaging

Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma

Li Lin et al.

RADIOLOGY (2019)

Article Oncology

Cancer statistics, 2019

Rebecca L. Siegel et al.

CA-A CANCER JOURNAL FOR CLINICIANS (2019)

Meeting Abstract Radiology, Nuclear Medicine & Medical Imaging

Pre-clinical geometric, dosimetric and timing assessment of head and neck OARs using an in-house atlas-based auto-segmentation (ABAS) tool

Eman Khawandanh et al.

MEDICAL PHYSICS (2016)

Article Computer Science, Artificial Intelligence

Deep Learning

Xing Hao et al.

INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING (2016)

Editorial Material Oncology

Recommendations on how to establish evidence from auto-segmentation software in radiotherapy

Vincenzo Valentini et al.

RADIOTHERAPY AND ONCOLOGY (2014)

Article Oncology

VARIATIONS IN THE CONTOURING OF ORGANS AT RISK: TEST CASE FROM A PATIENT WITH OROPHARYNGEAL CANCER

Benjamin E. Nelms et al.

INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2012)

Article Oncology

ATLAS-BASED SEGMENTATION IMPROVES CONSISTENCY AND DECREASES TIME REQUIRED FOR CONTOURING POSTOPERATIVE ENDOMETRIAL CANCER NODAL VOLUMES

Amy V. Young et al.

INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2011)

Article Oncology

Reduce in variation and improve efficiency of target volume delineation by a computer-assisted system using a deformable image registration approach

K. S. Clifford Chao et al.

INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2007)

Article Oncology

Timeline - Radiation oncology: a century of achievements

J Bernier et al.

NATURE REVIEWS CANCER (2004)