… we survey the image datasets most commonly used to train and test DL image segmentation
… We have surveyed image segmentation algorithms based on deep learning models, which …

… The inaccurate segmentation results are unable to meet the … review of current medical image
segmentation methods based on … based on deep learning is summarized in this review [93]. …

… image segmentation evaluation in … in evaluation are discussed. As a summary, we propose
a guideline for standardized medical image segmentation evaluation to improve evaluation …

… segmentation in medical image segmentation since each organ or tissue is quite different.
We review the advances of deep learning techniques … survey on medical image segmentation …

… of the task of image segmentation is everywhere. Therefore, in this article, we have tried to
give a survey of different image segmentation models. This survey study has covered recent …

… In this paper we aim to identify a measure for image segmentation that is sensitive to boundary
… We study error-sensitivity characteristics of each measure by generating a variety of error …

… image segmentation. In this paper, we aim to provide a comprehensive review with a focus
on multi-organ image segmentation, which … We grouped the surveyed methods into two broad …

… review of medical image segmentation based on U-net, focusing on the successful segmentation
… Along with the latest advances in DL, this article introduces the method of combining …

… EVALUATION METRICS As crucial as designing image processing models are, it is equally
important to evaluate … and widely used image segmentation evaluation metrics. Many of …

… A large number of novel methods have been proposed. This paper aims to provide a brief
review of research efforts on deep-learning-based semantic segmentation methods. We …