nnU-Net

Image datasets are enormously diverse: image dimensionality (2D, 3D), modalities/input channels (RGB image, CT, MRI, microscopy, ...), image sizes, voxel sizes, class ratio, target structure properties and more change substantially between datasets. Traditionally, given a new problem, a tailored solution needs to be manually designed and optimized - a process that is prone to errors, not scalable and where success is overwhelmingly determined by the skill of the experimenter. Even for experts, this process is anything but simple: there are not only many design choices and data properties that need to be considered, but they are also tightly interconnected, rendering reliable manual pipeline optimization all but impossible!

搜集汇总

背景与挑战

背景概述

nnU-Net是一个针对多样化图像数据集（如2D/3D图像、CT、MRI等）设计的工具，旨在克服传统手动定制解决方案易出错且不可扩展的问题。该数据集包含心脏图像数据和nnU-Net主程序文件。