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. Author manuscript; available in PMC: 2017 Jan 1.
Published in final edited form as: Med Image Anal. 2016 Sep 9;35:530–543. doi: 10.1016/j.media.2016.08.010

Table 5.

Average computational cost (measured in second) for feature extraction (including sparse feature encoding) on images with size 1000 × 1000 pixels. The evaluation is carried out with Intel(R) Xeon(R) CPU X5365 @ 3.00GHz, and GeForce GTX 580.

Feature Extraction Component(s) Average Computational Cost (in second)
Nuclear Segmentation 40
CMF-SFE 42 = Nuclear-Segmentation-Cost(40) + SFE-Cost(2)
DPSD-SFE 115 = DPSD-Cost(95) + SFE-Cost(20)
SPSD-SFE 70 = SPSD-Cost(60) + SFE-Cost(10)
DSIFT-SFE 16 = DSIFT-Cost(10) + SFE-Cost(6)
SSIFT-SFE 47 = SSIFT-Cost(45) + SFE-Cost(2)
DCT-SFE 90 = DCT-Cost(80) + SFE-Cost(10)
SCT-SFE 108 = SCT-Cost(105) + SFE-Cost(3)
CMF 40 = Nuclear-Segmentation-Cost(40)
DPSD 95
SPSD 60 = Nuclear-Segmentation-Cost(40) + PSD-Cost(20)
DSIFT 10
SSIFT 45 = Nuclear-Segmentation-Cost(40)+SIFT-Cost(5)
DCT 80
SCT 105 = Nuclear-Segmentation-Cost(40) + SCT-Cost(65)
StackedPSD 100
AlexNet 1200/180 (CPU-Only/GPU-Acceleration)