Jan 4, 2022 · Inspired by the success of vision transformers and their variants, we propose a novel segmentation model termed Swin UNEt TRansformers (Swin UNETR).

This repository contains the code for self-supervised pre-training of Swin UNETR model for medical image segmentation. In this readme, you will find a description of Swin UNETR, …

This repository contains the code for Swin UNETR [1,2] for the task of brain tumor segmentation using the BraTS 21 challenge dataset [3,4,5,6]. Swin UNETR ranked among top-perfoming …

Jul 22, 2022 · In this work, we propose a novel architecture termed Swin UNEt TRansformers (Swin UNETR), which utilizes a U-shaped network with a Swin transformer as the encoder and …

Nov 29, 2021 · Specifically, we propose: (i) a new 3D transformer-based model, dubbed Swin UNEt TRansformers (Swin UNETR), with a hierarchical encoder for self-supervised pre …

Swin UNETR ranked among top-performing models in the BraTS 21 validation phase. The architecture of Swin UNETR is demonstrated below. The following features are included in this …

Nov 11, 2023 · In this work, we propose Swin UNETR++, that contains a lightweight 3D Dual Cross-Attention (DCA) module to capture the intra and inter-volume relationships of each …

Mar 9, 2023 · Swin UNEt TRansformers (Swin UNETR) is proposed, in which the task of 3D brain tumor semantic segmentation is reformulated as a sequence to sequence prediction problem …

We use weights from self-supervised pre-training of Swin UNETR encoder (3D Swin Tranformer) on a cohort of 5050 CT scans from publicly available datasets. The encoder is pre-trained using...

In this paper, we enhance the Swi-nUNETR with convolutions, which results in a surprisingly stronger backbone, the SwinUNETR-V2, for 3D medical image segmentation.