ஜர்னல் ஆஃப் ஸ்பைன்

Scoliosis, a complex spinal deformity characterized by abnormal curvature, affects millions of people worldwide. Managing scoliosis requires regular monitoring, exercise, and sometimes bracing or surgical intervention. In recent years, the advancement of technology has led to the development of software and mobile applications that aim to empower patients in managing their scoliosis effectively. In this article, we will explore the utilization of software and apps in scoliosis management, their benefits, and how they enhance patient engagement, monitoring, exercise, and treatment outcomes.

Dendritic spines are small protrusions on the branches of neurons that play a critical role in synaptic connectivity and neuronal communication. Neurofilaments, a type of intermediate filament protein, are essential components of dendritic spines that provide structural stability and support. The levels of neurofilaments within dendritic spines have emerged as a significant area of research, as they are believed to be implicated in neuronal plasticity and neurodegenerative disorders. In this article, we will explore the importance of dendritic spine neurofilament levels, their functional significance, their involvement in neurodegenerative processes and their potential as biomarkers for disease progression.

Lumbar spine X-ray images are commonly used for diagnosing and evaluating spinal disorders. Accurate identification and labelling of vertebral landmarks on these images play a crucial role in clinical assessments, surgical planning, and research studies. However, the manual process of landmark labelling is prone to inter-observer variability, which can affect the reliability and validity of the measurements. This article explores the importance of reliable vertebral landmark labelling on lumbar spine X-ray images and discusses the methods and challenges associated with achieving consistency.

The human cervical vertebra plays a crucial role in supporting the weight of the head and facilitating various movements of the neck. However, due to poor posture, sedentary lifestyles, and other factors, many individuals suffer from cervical spine disorders, leading to discomfort, pain, and reduced quality of life. To address this issue, the development of intelligent evaluation methods for cervical vertebra rehabilitation has become increasingly important. This article explores the potential of computer vision-based techniques in assessing and improving cervical vertebra rehabilitation.