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Automated Human Bone Age Assessment using Image Processing Methods - Survey

by Rajitha Bakthula, Suneeta Agarwal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 13
Year of Publication: 2014
Authors: Rajitha Bakthula, Suneeta Agarwal
10.5120/18265-9259

Rajitha Bakthula, Suneeta Agarwal . Automated Human Bone Age Assessment using Image Processing Methods - Survey. International Journal of Computer Applications. 104, 13 ( October 2014), 33-42. DOI=10.5120/18265-9259

@article{ 10.5120/18265-9259,
author = { Rajitha Bakthula, Suneeta Agarwal },
title = { Automated Human Bone Age Assessment using Image Processing Methods - Survey },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 13 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number13/18265-9259/ },
doi = { 10.5120/18265-9259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:36:05.884953+05:30
%A Rajitha Bakthula
%A Suneeta Agarwal
%T Automated Human Bone Age Assessment using Image Processing Methods - Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 13
%P 33-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Computers have been widely used in the field of medical research over the past few decades. One of the emerging researches in medical imaging is to estimate age of the live or dead human being. Bone Age Assessment (BAA) is directly proportional to Skeletal (Bone) growth assessment. The study for Age Estimation (AE) has been categorized into two: one from live human where the AE is analysed through radiograph images such as X-ray, MRI, CT and DICOM and another from dead human body remains, where the AE can be performed manually (Forensic Study). AE is purely based on the measuring the length and shape of various bones, so radiographic images are must for live human. These radiographic medical images must be well processed for better assessment using various Image Processing Methods. Therefore, this paper present's an overview of various image processing methods applied for automated bone age estimation of live human and discuss some major challenges in storing the medical image datasets.

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Index Terms

Computer Science
Information Sciences

Keywords

Bone Age Assessment Image Processing Automated Bone Growth Assessment Medical Diagnosis Statistical Analysis Computer PACS Fuzzy Logic Neural Network

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