UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 10 Issue 3
March-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2303804


Registration ID:
510699

Page Number

i25-i28

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Title

3D Reconstruction of Leg Bones from X-Ray Images using CNN-based Feature Analysis

Abstract

The problem of 3D reconstruction of subject-specific bones from X-ray scans is crucial in several medical applications, such as diagnosis. Using feature analysis, we offer a method for rebuilding 3D leg bones from 2D X-Ray images. However, bounding boxes are identified using Convolutional Neural Networks (CNN). They are employed to extract feature ellipses and points. These qualities match the feature data of the 3D bone model. The aligned border of the 3D model is then used to determine the X-ray boundary. To optimize the 3D model, apply the statistical shape model parameter. For planning surgeries or making diagnoses, three-dimensional (3D) models of the human anatomy have been available for a while. While reconstructing the 3D module, the various picture modalities often rely on a series of sequential two-dimensional (2D) scans. Therefore, such purchases are costly, time-consuming, and frequently expose the patient to too much radiation. Due to this, studies have been presented in recent years that infer 3D anatomical elements from 2D tests like x-rays for implant templating in total knee or hip arthroplasty. The current study demonstrated a novel deep learning-based method for reconstructing 3D medical picture volumes from a single x-ray image.

Key Words

2-D to 3-D, CNN, x-ray images

Cite This Article

"3D Reconstruction of Leg Bones from X-Ray Images using CNN-based Feature Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.i25-i28, March-2023, Available :http://www.jetir.org/papers/JETIR2303804.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"3D Reconstruction of Leg Bones from X-Ray Images using CNN-based Feature Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppi25-i28, March-2023, Available at : http://www.jetir.org/papers/JETIR2303804.pdf

Publication Details

Published Paper ID: JETIR2303804
Registration ID: 510699
Published In: Volume 10 | Issue 3 | Year March-2023
DOI (Digital Object Identifier):
Page No: i25-i28
Country: Pune, Maharashtra, India .
Area: Medical Science
ISSN Number: 2349-5162
Publisher: IJ Publication


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