Comparative parotid gland segmentation by using ResNet ‐18 and MobileNetV2 based DeepLab v3+ architectures from magnetic resonance images

Investigating the potential of deep learning for patient-specific quality assurance of salivary gland contours using EORTC-1219-DAHANCA-29 clinical trial data

(2021) Hanne Nijhuis et al.   ACTA ONCOLOGICA

Training deep‐learning segmentation models from severely limited data

(2021) Yao Zhao et al.   MEDICAL PHYSICS

Cascaded deep learning‐based auto‐segmentation for head and neck cancer patients: Organs at risk on T2‐weighted magnetic resonance imaging

(2021) James C. Korte et al.   MEDICAL PHYSICS

Detection of the respiratory rate of standing cows by combining the Deeplab V3+ semantic segmentation model with the phase-based video magnification algorithm

(2020) Dihua Wu et al.   BIOSYSTEMS ENGINEERING

Head and neck multi‐organ auto‐segmentation on CT images aided by synthetic MRI

(2020) Yingzi Liu et al.   MEDICAL PHYSICS

Boosting‐based Cascaded Convolutional Neural Networks for the Segmentation of CT Organs‐at‐risk in Nasopharyngeal Carcinoma

(2019) Tao Zhong et al.   MEDICAL PHYSICS

Benefits of deep learning for delineation of organs at risk in head and neck cancer

(2019) J. van der Veen et al.   RADIOTHERAPY AND ONCOLOGY

Spinal Cord Based Kidney Segmentation Using Connected Component Labeling and K-Means Clustering Algorithm

(2019) Seda Tuncer et al.   Traitement du Signal

Segmentation of parotid glands from registered CT and MR images

(2018) Domen Močnik et al.   Physica Medica-European Journal of Medical Physics

AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy

(2018) Wentao Zhu et al.   MEDICAL PHYSICS

Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015

(2017) Patrik F. Raudaschl et al.   MEDICAL PHYSICS

Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks

(2017) Bulat Ibragimov et al.   MEDICAL PHYSICS

Global cancer statistics, 2012

(2015) Lindsey A. Torre et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Estimating the demand for radiotherapy from the evidence: A review of changes from 2003 to 2012

(2014) Michael B. Barton et al.   RADIOTHERAPY AND ONCOLOGY

Atlas-based Auto-segmentation of CT Images in Head and Neck Cancer: What is the Best Approach?

(2008) M.S. Hoogeman et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS