Clinically, retinal vessel segmentation is a significant step in the diagnosis of fundus
diseases. However, recent methods generally neglect the difference of semantic information …

Open international challenges are becoming the de facto standard for assessing computer
vision and image analysis algorithms. In recent years, new methods have extended the …

Cracks are usually curve-like structures that are the focus of many computer-vision
applications (eg, road safety inspection and surface inspection of industrial facilities). The …

Curvilinear object segmentation is critical for many applications. However, manually
annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently …

Multimodal image matching is a core basis for information fusion, change detection, and
image-based navigation. However, multimodal images may simultaneously suffer from …

Retinal vessel segmentation plays a crucial role in the diagnosis and treatment of ocular
pathologies. Current methods have limitations in feature fusion and face challenges in …

Vessel segmentation is crucial in many medical image applications, such as detecting
coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high …

Most pavement crack detection methods based on deep learning rely too much on pixel-
wise labels, and are facing with sample imbalance problem. This paper proposes a three …

Intractable sparse feature extraction, overweight model size, and limited training samples
are currently bewildering in infrared dim small target detection, which is not adequately …

Vessel enhancement (aka vesselness) filters, are part of angiographic image processing for
more than twenty years. Their popularity comes from their ability to enhance tubular …