Automatic medical image segmentation is a crucial topic in the medical domain and
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …

The advancement of medical imaging has profoundly impacted our understanding of the
human body and various diseases. It has led to the continuous refinement of related …

In modern healthcare, the precision of medical image segmentation holds immense
significance for diagnosis and treatment planning. Deep learning techniques, such as …

Scoliosis is a complicated spinal deformity, and millions of people are suffering from this
disease worldwide. Early detection and accurate scoliosis assessment are vital for effective …

Plantar pressure distribution offers insights into foot function, gait mechanics, and foot-
related issues. This systematic review presents an analysis of the use of artificial neural …

The current clinical gold standard for evaluating adolescent idiopathic scoliosis (AIS) is X-
ray radiography, specifically through Cobb angle measurement. However, frequent …

A 3-D ultrasound (US) imaging technique has been studied to facilitate the diagnosis of
spinal deformity without radiation. The objective of this article is to propose an assessment …

Extracting vascular structures from retinal fundus images plays a critical role in the early
diagnosis and long-term treatment of ophthalmic diseases. Traditional manual segmentation …

Objective Scoliosis is a spinal deformation in which the spine takes a lateral curvature,
generating an angle in the coronal plane. The conventional method for detecting scoliosis is …

In addressing the challenges of medical image segmentation, particularly the elusiveness of
global context and limitations in leveraging both global and local context simultaneously, we …