Orthogonal annotation benefits barely-supervised medical image segmentation
Recent trends in semi-supervised learning have significantly boosted the performance of 3D
semi-supervised medical image segmentation. Compared with 2D images, 3D medical …
semi-supervised medical image segmentation. Compared with 2D images, 3D medical …
DMSPS: Dynamically mixed soft pseudo-label supervision for scribble-supervised medical image segmentation
High performance of deep learning on medical image segmentation rely on large-scale pixel-
level dense annotations, which poses a substantial burden on medical experts due to the …
level dense annotations, which poses a substantial burden on medical experts due to the …
Recist-induced reliable learning: Geometry-driven label propagation for universal lesion segmentation
Automatic universal lesion segmentation (ULS) from Computed Tomography (CT) images
can ease the burden of radiologists and provide a more accurate assessment than the …
can ease the burden of radiologists and provide a more accurate assessment than the …
3D vascular segmentation supervised by 2D annotation of maximum intensity projection
Vascular structure segmentation plays a crucial role in medical analysis and clinical
applications. The practical adoption of fully supervised segmentation models is impeded by …
applications. The practical adoption of fully supervised segmentation models is impeded by …
Weakly supervised semantic segmentation via saliency perception with uncertainty-guided noise suppression
Abstract Weakly Supervised Semantic Segmentation (WSSS) has become increasingly
popular for achieving remarkable segmentation with only image-level labels. Current WSSS …
popular for achieving remarkable segmentation with only image-level labels. Current WSSS …
Weakly supervised medical image segmentation via superpixel-guided scribble walking and class-wise contrastive regularization
Deep learning-based segmentation typically requires a large amount of data with dense
manual delineation, which is both time-consuming and expensive to obtain for medical …
manual delineation, which is both time-consuming and expensive to obtain for medical …
Data efficient deep learning for medical image analysis: A survey
The rapid evolution of deep learning has significantly advanced the field of medical image
analysis. However, despite these achievements, the further enhancement of deep learning …
analysis. However, despite these achievements, the further enhancement of deep learning …
Scribble-supervised rgb-t salient object detection
Salient object detection segments attractive objects in scenes. RGB and thermal modalities
provide complementary information and scribble annotations alleviate large amounts of …
provide complementary information and scribble annotations alleviate large amounts of …
Scribble-Based 3D Multiple Abdominal Organ Segmentation via Triple-Branch Multi-Dilated Network with Pixel-and Class-Wise Consistency
Multi-organ segmentation in abdominal Computed Tomography (CT) images is of great
importance for diagnosis of abdominal lesions and subsequent treatment planning. Though …
importance for diagnosis of abdominal lesions and subsequent treatment planning. Though …
Point based weakly supervised deep learning for semantic segmentation of remote sensing images
Y Zhao, G Sun, Z Ling, A Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Weakly supervised semantic segmentation methods can effectively alleviate the problem of
high cost and difficult access to annotation in traditional methods. Among these approaches …
high cost and difficult access to annotation in traditional methods. Among these approaches …