Machine learning techniques for biomedical image segmentation: an overview of technical aspects and introduction to state‐of‐art applications
H Seo, M Badiei Khuzani, V Vasudevan… - Medical …, 2020 - Wiley Online Library
In recent years, significant progress has been made in developing more accurate and
efficient machine learning algorithms for segmentation of medical and natural images. In this …
efficient machine learning algorithms for segmentation of medical and natural images. In this …
Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods
T Vrtovec, D Močnik, P Strojan, F Pernuš… - Medical …, 2020 - Wiley Online Library
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck
(H&N), which requires a precise spatial description of the target volumes and organs at risk …
(H&N), which requires a precise spatial description of the target volumes and organs at risk …
Multi-task learning for the segmentation of organs at risk with label dependence
Automatic segmentation of organs at risk is crucial to aid diagnoses and remains a
challenging task in medical image analysis domain. To perform the segmentation, we use …
challenging task in medical image analysis domain. To perform the segmentation, we use …
Organ at risk segmentation in head and neck CT images using a two-stage segmentation framework based on 3D U-Net
Y Wang, L Zhao, M Wang, Z Song - IEEE Access, 2019 - ieeexplore.ieee.org
Accurate segmentation of organs at risk (OARs) plays a critical role in the treatment planning
of image-guided radiotherapy of head and neck cancer. This segmentation task is …
of image-guided radiotherapy of head and neck cancer. This segmentation task is …
Deep learning-based medical image segmentation with limited labels
Deep learning (DL)-based auto-segmentation has the potential for accurate organ
delineation in radiotherapy applications but requires large amounts of clean labeled data to …
delineation in radiotherapy applications but requires large amounts of clean labeled data to …
Weaving attention U‐net: A novel hybrid CNN and attention‐based method for organs‐at‐risk segmentation in head and neck CT images
Purpose In radiotherapy planning, manual contouring is labor‐intensive and time‐
consuming. Accurate and robust automated segmentation models improve the efficiency …
consuming. Accurate and robust automated segmentation models improve the efficiency …
Robustness study of noisy annotation in deep learning based medical image segmentation
Partly due to the use of exhaustive-annotated data, deep networks have achieved
impressive performance on medical image segmentation. Medical imaging data paired with …
impressive performance on medical image segmentation. Medical imaging data paired with …
Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy
Objective. Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk
(OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No …
(OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No …
Deep hybrid neural-like P systems for multiorgan segmentation in head and neck CT/MR images
J Xue, Y Wang, D Kong, F Wu, A Yin, J Qu… - Expert Systems with …, 2021 - Elsevier
Automatic segmentation of organs-at-risk (OARs) of the head and neck, such as the
brainstem, the left and right parotid glands, mandible, optic chiasm, and the left and right …
brainstem, the left and right parotid glands, mandible, optic chiasm, and the left and right …
[HTML][HTML] Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review
R Jin, Y Cai, S Zhang, T Yang, H Feng… - Frontiers in …, 2023 - frontiersin.org
Optic never fibers in the visual pathway play significant roles in vision formation. Damages of
optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and …
optic nerve fibers are biomarkers for the diagnosis of various ophthalmological and …