蒙特卡洛采样应用于多示例学习进行组织学图像分类
计算机视觉与模式识别
2019-01-01 v1 机器学习
机器学习
摘要
我们提出一种基于序贯蒙特卡洛方法的图像块采样策略，用于多示例学习背景下的高分辨率图像分类。与网格采样和均匀采样技术相比，它取得了更高的泛化性能。我们在两个人工数据集以及用于乳腺癌和日晒分类的两个组织学数据集上验证了该策略。
引用
@article{arxiv.1812.11560,
title = {Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification},
author = {Marc Combalia and Veronica Vilaplana},
journal= {arXiv preprint arXiv:1812.11560},
year = {2019}
}
备注
accepted at 4th International Workshop on Deep Learning for Medical Image Analysis (DLMIA), MICCAI 2018, Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Springer International Publishing, 2018