SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation

ArXi:2604.17451v1 Announce Type: new Increasingly advanced data augmentation techniques have greatly aided clinical medical research, increasing data diversity and improving model generalization capabilities. Although most current basic models exhibit strong generalization abilities, image quality varies due to differences in equipment and operators. To address these challenges, we present SegTTA, a framework that improves medical image segmentation without model re