https://www.selleckchem.com/pr....oducts/FK-506-(Tacro
93) ResNet-34 and Faster R-CNN in classifying breasts with malignant findings. On the CBIS-DDSM dataset, our model achieves performance (AUC = 0.858) on par with state-of-the-art approaches. Compared to ResNet-34, our model is 4.1x faster for inference while using 78.4% less GPU memory. Furthermore, we demonstrate, in a reader study, that our model surpasses radiologist-level AUC by a margin of 0.11.Automatic sigmoid colon segmentation in CT for radiotherapy treatment planning is challenging due to complex organ shape, close
Like
Comment
Share
