论文标题
Heartspot：私有和可解释的数据压缩，用于心脏肿大检测
HeartSpot: Privatized and Explainable Data Compression for Cardiomegaly Detection
论文作者
论文摘要
胸部X射线图像分析的数据驱动深度学习的进展强调了解释性，隐私，大数据集和大量计算资源的需求。我们将隐私性和解释性框起来是有损的单形图像压缩问题，可以在没有培训的情况下减少计算和数据要求。为了在胸部X射线图像中检测到心脏全面检测，我们提出了心脏点和四个空间偏置先验。 Heartspot先生定义了如何根据医学文献和机器中的领域知识进行样品样本。 Heartspot通过丢弃多达97％的像素来私有化胸部X射线图像，例如揭示胸腔笼子，骨骼，小病变和其他敏感特征的像素。 Heartspot先生是可以解释的，并给出了保存的空间特征的人类解剖图像，这些特征清楚地概述了心脏。 HeartSpot提供强大的压缩，最多减少了32倍的像素和11倍较小的文件。与基线densenet121相比，使用心脏点的心脏肿大探测器的训练速度高达9倍或至少至少准确（最高为+.01 AUC ROC）。 Heartspot是可通过重新使用现有归因方法而无需访问原始非私密图像的情况来解释的事后解释。总之，心脏点提高速度和准确性，降低图像大小，改善隐私并确保解释性。 源代码：https：//www.github.com/adgaudio/heartspot
Advances in data-driven deep learning for chest X-ray image analysis underscore the need for explainability, privacy, large datasets and significant computational resources. We frame privacy and explainability as a lossy single-image compression problem to reduce both computational and data requirements without training. For Cardiomegaly detection in chest X-ray images, we propose HeartSpot and four spatial bias priors. HeartSpot priors define how to sample pixels based on domain knowledge from medical literature and from machines. HeartSpot privatizes chest X-ray images by discarding up to 97% of pixels, such as those that reveal the shape of the thoracic cage, bones, small lesions and other sensitive features. HeartSpot priors are ante-hoc explainable and give a human-interpretable image of the preserved spatial features that clearly outlines the heart. HeartSpot offers strong compression, with up to 32x fewer pixels and 11x smaller filesize. Cardiomegaly detectors using HeartSpot are up to 9x faster to train or at least as accurate (up to +.01 AUC ROC) when compared to a baseline DenseNet121. HeartSpot is post-hoc explainable by re-using existing attribution methods without requiring access to the original non-privatized image. In summary, HeartSpot improves speed and accuracy, reduces image size, improves privacy and ensures explainability. Source code: https://www.github.com/adgaudio/HeartSpot
