A deep learning approach on cervical spine fracture detection

Registration ID: IJNRD_199600

Published ID: IJNRD2306377

DOI: Click Here to Get

Gayathri M , shobha A , Ifthika K

CAD, C1, C2, C3, C4, C5, C6, C7, C8, Efficienetv2s, LSTM, CNN

Cervical spine fractures need time-consuming study by skilled radiologists, which might present problems for institutions with limited resources. They are a major concern in the area of radiology. Computer-aided diagnosis (CAD), which employs the cutting-edge imaging method of multi-detector CT, has grown in favor for identifying cervical spine fractures as a solution to this problem. To avoid neurologic degeneration and paralysis brought on by trauma, early detection of vertebral fractures is essential. In this study, we design and train a deep learning model to identify fractures in the cervical spine, both at the patient's overall level and at the level of specific vertebrae, using CT scan pictures. Our goal is to improve the model's performance in correctly diagnosing cervical spine fractures. The suggested deep learning model analyzes CT images and offers automated aid in fracture detection by utilizing cutting-edge methods and developments in computer vision. We demonstrate the efficiency of our model in localizing cervical spine fractures through thorough training and assessment on a variety of datasets, which can help radiologists with their diagnosis and expedite treatment planning. Reduced interpretation times, higher accuracy, and expanded accessibility to high-quality treatment are all possible advantages of this strategy, particularly in healthcare institutions with limited resources.

Published Paper   E-Certificate

Gayathri M, shobha A, & Ifthika K (June-2023). A deep learning approach on cervical spine fracture detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(6), d746-d751. https://ijnrd.org/papers/IJNRD2306377.pdf

Volume 8 Issue 6, June-2023

Pages : d746-d751

Paper Reg. ID: IJNRD_199600

Published Paper Id: IJNRD2306377

Downloads: 000121992

Research Area: Engineering

Country: Coimbatore, tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306377.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2306377

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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