CERVICAL SPINE FRACTURE DETECTION USING DEEP NEURAL NETWORKS.

CERVICAL SPINE FRACTURE DETECTION USING DEEP NEURAL NETWORKS.

Registration ID: IJNRD_221787

Published ID: IJNRD2405413

DOI: Click Here to Get

NUCHU MANIKANTA YADAV , KURUVA MANOJ , ANUSURI KARTHEEK , YESHWANTH REDDY , PASHAPU SAI KRISHNA,Dr. M.K. Jayanthi Kannan

DNN, U-NET, InceptionResNetV2, CNN, DICOM, ENCODER ADN DECODER, FLASK FRAMEWORK, GOOGLE-NET, PYTHON, COMPUTED TOMOGRAPHY (CT), CERVICAL VERTEBRAE, SEMANTIC SEGMENTATION

Detecting cervical spine fractures, especially in elderly individuals with underlying degenerative conditions, poses challenges. To address this, a study introduces a pioneering method employing deep neural networks (DNNs), specifically the U-Net architecture, to automate fracture detection in computed tomography (CT) scans. The approach focuses on accurately identifying and localizing cervical vertebrae, vital for precise fracture assessment. Utilizing U-Net's adeptness in semantic segmentation, the model accurately delineates cervical vertebrae boundaries, capturing intricate details and spatial relationships within the images. Moreover, by integrating multi-class classification layers, the framework extends U- Net's capabilities for fracture detection, distinguishing between fractured and intact regions within segmented cervical vertebrae, thus enhancing diagnostic accuracy. Trained on a diverse dataset of cervical spine injuries, the proposed methodology offers significant clinical advantages, including real-time fracture assessment, enabling prompt diagnosis and timely intervention to improve patient outcomes. Leveraging the potency of deep learning, this approach holds promise for enhancing the efficiency and accuracy of cervical spine fracture detection, ultimately contributing to enhanced patient care and treatment outcomes.

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"CERVICAL SPINE FRACTURE DETECTION USING DEEP NEURAL NETWORKS.", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 5, page no.e105-e112, May-2024, Available :https://ijnrd.org/papers/IJNRD2405413.pdf

Volume 9 Issue 5, May-2024

Pages : e105-e112

Paper Reg. ID: IJNRD_221787

Published Paper Id: IJNRD2405413

Downloads: 000121127

Research Area: Computer Science & Technology 

Country: Hyderabad, Telangana, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405413.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405413

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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