The adaptive integration of the colour and texture attributes in the development of complex
image descriptors is one of the most investigated topics of research in computer vision. The …

The medical image analysis field has traditionally been focused on the development of
organ-, and disease-specific methods. Recently, the interest in the development of more …

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here
we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform …

This survey gives an overview over different techniques used for pixel-level semantic
segmentation. Metrics and datasets for the evaluation of segmentation algorithms and …

In this paper, we propose a probabilistic model for detecting relevant changes in registered
aerial image pairs taken with the time differences of several years and in different seasonal …

This paper presents a new, simple, and efficient segmentation approach, based on a fusion
procedure which aims at combining several segmentation maps associated to simpler …

Background Radiomic analysis is defined as computationally extracting features from
radiographic images for quantitatively characterizing disease patterns. There has been …

Due to the complicated structure of breast and poor quality of ultrasound images, accurately
and automatically locating regions of interest (ROIs) and segmenting tumors are challenging …

Current semantic segmentation methods mainly focus on modeling the context of the global
image to obtain high-quality segmentation results. However, they ignore the role of local …

In recent years, the acquisition of image and video information for processing, analysis,
understanding, and exploitation of the underlying content in various applications, ranging …