… The concept of automated segmentation using deep learning … automated segmentation
of intra- and subretinal fluid in OCT images of 37 patients [17]. Initial automated segmentation …

… accurate segmentation of the mandibular condyles and the glenoid fossae. This study
aimed to develop and validate an automated segmentation tool based on a deep learning …

… Deep neural networks have recently gained attention for their ability to automate segmentation
… of the literature on deep learning (DL) techniques for segmentation in radiation therapy …

… In this paper, we propose a new automated segmentation approach for the endocardial
and epicardial borders of the left ventricle (LV) from all slices of the end diastole (ED) and end …

… In this paper we have presented a pipeline for semi-automated segmentation of pulmonary
nodules which requires very little intervention from the user. The proposed solution can be …

… Since the manually segmented … automated segmentation compared to manual segmentation.
Nevertheless, efforts have been made to contain this limitation by training a deep learning …

… To address this need, we developed a deep learning model that segmented 11 intracranial
… general utility for future deep learning–based approaches to medical image segmentation. …

… in deep learning (17,22) may be applied for fully automated detection and segmentation of
CLM… , agreement, and efficiency of deep learning–based detection and segmentation of CLM. …

… application of an image segmentation method based on deep learning that is capable of
segmenting images such as Fig. 1 automatically. This deep learning method relies on artificial …

… deep convolutional neural network application based on autoencoders aimed at segmentation
… on the publicly available Brain Tumor Image Segmentation Benchmark (BRATS) data set, …