Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection
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8,730 citations
Cites background from "Multilevel Contextual 3-D CNNs for ..."
...…data set Ciompi et al. (2016) Multi-stream CNN to classify nodules into subtypes: solid, part-solid, non-solid, calcified, spiculated, perifissural Dou et al. (2017) Uses 3D CNN around nodule candidates; ranks #1 in LUNA16 nodule detection challenge Li et al. (2016a) Detects nodules with 2D CNN…...
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Cites methods from "Multilevel Contextual 3-D CNNs for ..."
...…other type of methods employed real 3D CNNs to detect or segment objects from volumetric data and demonstrated compelling performance (Dou et al.; Dou et al., 2016a, 2016b; Cicek et al., 2016; Yu et al., 2017; Merkow et al., 2015; Milletari et al., 2016; Kamnitsas et al., 2017; Chen et al.,…...
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References
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"Multilevel Contextual 3-D CNNs for ..." refers background in this paper
...Recently, with the remarkable successes of deep convolutional neural networks (CNNs) in image and video processing [13]–[16], the representation capability of the high-level features which are learned from large amounts of training data has been broadly recognized....
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15,055 citations
Additional excerpts
...012) and updated with standard backpropagation [31]....
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