Deep learning has shown great potential for automated medical image segmentation to
improve the precision and speed of disease diagnostics. However, the task presents …

Image segmentation plays an important role in vision understanding. Recently, the emerging
vision foundation models continuously achieved superior performance on various tasks …

Recent developments underscore the potential of textual information in enhancing learning
models for a deeper understanding of medical visual semantics. However, language-guided …

Prostate cancer (PCa) poses a significant threat to men's health, with early diagnosis being
crucial for improving prognosis and reducing mortality rates. Transrectal ultrasound (TRUS) …

Despite that the segment anything model (SAM) achieved impressive results on general-
purpose semantic segmentation with strong generalization ability on daily images, its …

The success of deep learning (DL) relies heavily on training data from which DL models
encapsulate information. Consequently, the development and deployment of DL models …

Accurate lung tumor segmentation from Computed Tomography (CT) scans is crucial for
lung cancer diagnosis. Since the 2D methods lack the volumetric information of lung CT …

The semantic segmentation of high-resolution remote sensing images (HRRSIs) faces
persistent challenges in handling complex architectural structures and shadow occlusions …

The universality of deep neural networks across different modalities and their generalization
capabilities to unseen domains play an essential role in medical image segmentation. The …

The fetus's health is evaluated with the biometric parameters obtained from the low-
resolution ultrasound images. The accuracy of biometric parameters in existing protocols …