Interaction in the segmentation of medical images: A survey

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Automated medical image segmentation techniques (2010, methodology): “Unsupervised methods are preferred to ensure a reproducible result[43]; however, operator interaction is still required for error correction in the event of an inadequate result.[44]”
PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques (2010, background): “Medical image segmentation has been identified as the key problem of medical image analysis and remains a popular and challenging area of research [22–25].”
A comparative evaluation of interactive segmentation algorithms (2010, positive): “evaluate algorithms whose interactions can be modelled by pictorial input on an image grid [21]; we do not consider interactive segmentation algorithms based on parameter tuning or other forms of interaction.”
State of the art survey on MRI brain tumor segmentation. (2013, methodology): “According to Olabarriaga et al. [6], the main components of an interactive brain tumor segmentation Edema Necrotic Active Nec T1 T2 Fig.”
A Comparative Analysis of Object Detection Metrics with a Companion Open-Source Toolkit (2021, background): “Later on, advancements in object detection techniques led to their increasing adoption in areas that included the manufacturing industry with optical inspections [13], video surveillance [14], forensics [15,16], medical image analysis [17–19], autonomous vehicles [20], and trafﬁc monitoring [21].”