Desam: Decoupled segment anything model for generalizable medical image segmentation
Deep learning-based medical image segmentation models often suffer from domain shift,
where the models trained on a source domain do not generalize well to other unseen …
where the models trained on a source domain do not generalize well to other unseen …
Deep network-based comprehensive parotid gland tumor detection
Rationale and Objectives Salivary gland tumors constitute 2%-6% of all head and neck
tumors and are most common in the parotid gland. Magnetic resonance (MR) imaging is the …
tumors and are most common in the parotid gland. Magnetic resonance (MR) imaging is the …
Parotid Gland Segmentation Using Purely Transformer-Based U-Shaped Network and Multimodal MRI
Z Xu, Y Dai, F Liu, S Li, S Liu, L Shi, J Fu - Annals of Biomedical …, 2024 - Springer
Parotid gland tumors account for approximately 2% to 10% of head and neck tumors.
Segmentation of parotid glands and tumors on magnetic resonance images is essential in …
Segmentation of parotid glands and tumors on magnetic resonance images is essential in …
MBA-Net: SAM-Driven Bidirectional Aggregation Network for Ovarian Tumor Segmentation
Accurate segmentation of ovarian tumors from medical images is crucial for early diagnosis,
treatment planning, and patient management. However, the diverse morphological …
treatment planning, and patient management. However, the diverse morphological …
A Weakly-Supervised Multi-lesion Segmentation Framework Based on Target-Level Incomplete Annotations
Effectively segmenting Crohn's disease (CD) from computed tomography is crucial for
clinical use. Given the difficulty of obtaining manual annotations, more and more …
clinical use. Given the difficulty of obtaining manual annotations, more and more …