nnFormer: Interleaved Transformer for Volumetric Segmentation
Code for paper “nnFormer: Interleaved Transformer for Volumetric Segmentation “. Please read our preprint at the following link: paper_address.
Parts of codes are borrowed from nn-UNet.
Installation
1、System requirements
This software was originally designed and run on a system running Ubuntu 18.01, with Python 3.6, PyTorch 1.8.1, and CUDA 10.1. For a full list of software packages and version numbers, see the Conda environment file environment.yml.
This software leverages graphical processing units (GPUs) to accelerate neural network training and evaluation; systems lacking a suitable GPU will likely take an extremely long time to train or evaluate models. The software was tested with the NVIDIA RTX 2080 TI GPU, though we anticipate that other GPUs will also