WindowNet: Learnable Windows for Chest X-ray Classification
暂无分享,去创建一个
[1] B. Sabel,et al. Attention-based Saliency Maps Improve Interpretability of Pneumothorax Classification , 2023, Radiology. Artificial intelligence.
[2] Manohar Karki,et al. CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings , 2020, Artif. Intell. Medicine.
[3] Kihwan Choi,et al. Trainable Multi-contrast Windowing for Liver CT Segmentation , 2020, 2020 IEEE International Conference on Big Data and Smart Computing (BigComp).
[4] Shunxing Bao,et al. Stochastic tissue window normalization of deep learning on computed tomography , 2019, Journal of medical imaging.
[5] Hyunkwang Lee,et al. Practical Window Setting Optimization for Medical Image Deep Learning , 2018, ArXiv.
[6] Frank Hutter,et al. Decoupled Weight Decay Regularization , 2017, ICLR.
[7] Ronald M. Summers,et al. ChestX-ray: Hospital-Scale Chest X-ray Database and Benchmarks on Weakly Supervised Classification and Localization of Common Thorax Diseases , 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.
[8] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Tom Kimpe,et al. Increasing the Number of Gray Shades in Medical Display Systems—How Much is Enough? , 2007, Journal of Digital Imaging.