Abstract Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …

Deep learning has recently been used for the analysis of neuroimages, such as structural
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …

The tremendous success of machine learning algorithms at image recognition tasks in
recent years intersects with a time of dramatically increased use of electronic medical …

Identifying and interpreting fetal standard scan planes during 2-D ultrasound mid-pregnancy
examinations are highly complex tasks, which require years of training. Apart from guiding …

Remote sensing is useful for detecting and quantifying cyanobacteria blooms for managing
water systems. In particular, airborne hyperspectral remote sensing has an advantage in …

Cytokine storm, known as an exaggerated hyperactive immune response characterized by
elevated release of cytokines, has been described as a feature associated with life …

Feature extraction is a fundamental step when mammography image analysis is addressed
using learning based approaches. Traditionally, problem dependent handcrafted features …

In the field of medical image analysis within deep learning (DL), the importance of
employing advanced DL techniques cannot be overstated. DL has achieved impressive …

Simple Summary The incidence of thyroid pathologies has been increasing worldwide.
Historically, the detection of thyroid neoplasms relies on medical imaging analysis …

Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical
interventions and has therefore become an increasingly popular treatment modality in …