  Medical imaging technologies have undergone extensive development, enabling
non-invasive visualization of clinical information. The traditional review of
medical images by clinicians remains subjective, time-consuming, and prone to
human error. With the recent availability of medical imaging data,
quantification have become important goals in the field. Radiomics, a
methodology aimed at extracting quantitative information from imaging data, has
emerged as a promising approach to uncover hidden biological information and
support decision-making in clinical practice. This paper presents a review of
the radiomic pipeline from the clinical neuroimaging perspective, providing a
detailed overview of each step with practical advice. It discusses the
application of handcrafted and deep radiomics in neuroimaging, stratified by
neurological diagnosis. Although radiomics shows great potential for increasing
diagnostic precision and improving treatment quality in neurology, several
limitations hinder its clinical implementation. Addressing these challenges
requires collaborative efforts, advancements in image harmonization methods,
and the establishment of reproducible and standardized pipelines with
transparent reporting. By overcoming these obstacles, radiomics can
significantly impact clinical neurology and enhance patient care.
