Clinical Anatomy in Imaging: Leveraging Structural Data for Enhanced Pathological Precision
Year: 2025
Type: article
Abstract: IntroductionMedical imaging plays a crucial role in modern medicine, providing visual representations of the body's interior for clinical analysis, medical intervention, and establishing baselines for detecting subtle abnormalities [1][2][3][4].The field is constantly evolving, driven by advancements in technology and a growing need for more precise and personalized approaches to healthcare [5][6][7].One of the most promising avenues for improvement lies in leveraging structural data from clinical anatomy within medical imaging to enhance pathological precision, ultimately leading to better diagnoses, treatment planning, and patient outcomes [8][9][10][11].This article will explore how integrating anatomical knowledge with advanced imaging techniques can lead to a more comprehensive understanding of disease processes.The integration of clinical anatomy with advanced imaging techniques is pivotal for enhancing pathological precision in medical diagnostics and treatment planning [12][13][14].Recent literature highlights various methodologies and technologies that leverage structural data to improve clinical outcomes across different medical fields.One significant advancement is the use of three-dimensional (3D) models derived from imaging data, which has been shown to enhance surgical navigation and preoperative planning.For instance, Liawrungrueang et al. [15] developed highresolution 3D models of the C1 and C2 vertebrae, enabling comprehensive morphometric analysis that aids in identifying gender differences and assessing bilateral symmetry, ultimately enhancing surgical accuracy.Similarly, Miyoshi [16] emphasizes the construction of 3D models from preoperative imaging data to support surgical simulations and navigation, showcasing the potential of these models in perioperative care.AI plays a crucial role in refining diagnostic imaging processes.Luvhengo et al. [17] discuss how AI-driven precision oncology can significantly
Authors: Aishwarya Tummala, Anshul Yadav, Jahnavi Kudapa, Ahmed Shaik
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412757487