Innovations in detecting skull fractures: A review of computer-aided techniques in CT imaging.
Phys Med
; 124: 103400, 2024 Aug.
Article
en En
| MEDLINE
| ID: mdl-38996627
ABSTRACT
BACKGROUND/INTRODUCTION:
Traumatic brain injury (TBI) remains a leading cause of disability and mortality, with skull fractures being a frequent and serious consequence. Accurate and rapid diagnosis of these fractures is crucial, yet current manual methods via cranial CT scans are time-consuming and prone to error.METHODS:
This review paper focuses on the evolution of computer-aided diagnosis (CAD) systems for detecting skull fractures in TBI patients. It critically assesses advancements from feature-based algorithms to modern machine learning and deep learning techniques. We examine current approaches to data acquisition, the use of public datasets, algorithmic strategies, and performance metricsRESULTS:
The review highlights the potential of CAD systems to provide quick and reliable diagnostics, particularly outside regular clinical hours and in under-resourced settings. Our discussion encapsulates the challenges inherent in automated skull fracture assessment and suggests directions for future research to enhance diagnostic accuracy and patient care.CONCLUSION:
With CAD systems, we stand on the cusp of significantly improving TBI management, underscoring the need for continued innovation in this field.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Fracturas Craneales
/
Tomografía Computarizada por Rayos X
Límite:
Humans
Idioma:
En
Revista:
Phys Med
/
Phys. medica (Testo stamp.)
/
Physica medica
Asunto de la revista:
BIOFISICA
/
BIOLOGIA
/
MEDICINA
Año:
2024
Tipo del documento:
Article