The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …

Abstract Diffusion Probabilistic Model (DPM) has recently become one of the hottest topics in
computer vision. Its image generation applications, such as Imagen, Latent Diffusion …

The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of
computer vision, thanks to its image generation applications, such as Imagen, Latent …

Ultrasound segmentation of thyroid nodules is a challenging task, which plays an vital role in
the diagnosis of thyroid cancer. However, the following two factors limit the development of …

The large-scale pre-trained vision language models (VLM) have shown remarkable domain
transfer capability on natural images. However, it remains unknown whether this capability …

Medical image segmentation plays a pivotal role in clinical diagnostics and treatment
planning, yet existing models often face challenges in generalization and in handling both …

Zero-shot anomaly detection (ZSAD) targets the identification of anomalies within images
from arbitrary novel categories. This study introduces AdaCLIP for the ZSAD task, leveraging …

Background and Objective Deep learning (DL) has contributed substantially to the evolution
of image analysis by unlocking increased data and computational power. These DL …

Abstract Background and Objective: Accurate and efficient segmentation of thyroid nodules
on ultrasound images is critical for computer-aided nodule diagnosis and treatment. For …

Abstract Convolutional Neural Networks (CNNs), particularly UNet, have become prevalent
in medical image segmentation tasks. However, CNNs inherently struggle to capture global …