With profound effects on patient care, the role of artificial intelligence (AI) in radiomics has
become a disruptive force in contemporary medicine. Radiomics, the quantitative feature …

Magnetic resonance imaging (MRI) is crucial for its superior soft tissue contrast and high
spatial resolution. Integrating deep learning algorithms into MRI reconstruction has …

Precise and fast diagnosis of COVID-19 cases play a vital role in early stage of medical
treatment and prevention. Automatic detection of COVID-19 cases using the chest X-ray …

The advent of large models, also known as foundation models, has significantly transformed
the AI research landscape, with models like Segment Anything (SAM) achieving notable …

Simple Summary Leukemia is a type of cancer that affects white blood cells and can lead to
serious health problems and death. Diagnosing leukemia is currently performed through a …

Rice leaf diseases have an important impact on modern farming, threatening crop health
and yield. Accurate semantic segmentation techniques are crucial for segmenting diseased …

Recently, transformers have been widely used in medical image segmentation to capture
long-range and global dependencies using self-attention. However, they often struggle to …

Histopathological examination holds a crucial role in cancer grading and serves as a
significant reference for devising individualized patient treatment plans in clinical practice …

Abstract Even though the Vision Transformer leverages the self-attention mechanism to
capture long-range dependencies, showing significant potential in medical image …

The early detection of liver fibrosis is of significant importance. Deep learning analysis of
ultrasound backscattered radiofrequency (RF) signals is emerging for tissue characterization …