Converting 2D-Medical Image Files “DICOM” into 3D- Models, Based on Image Processing, and Analysing Their Results with Python Programming

Author:

Mamdouh Rafeek1,El-Bakry Hazem M.2,Riad Alaa2,El-Khamisy Nashaat2

Affiliation:

1. Faculty of Comp and Inf. System, Mansoura Univ., EGYPT

2. Information Systems Dept., Faculty of Computer & Information Sciences, Mansoura University, EGYPT

Abstract

This paper presents the possibility of converting (2D) medical image data (Digital Imaging and Communications in Medicine (DICOM) files) to 3D model. Medical data and image processing software’s, namely Seg3D2 and ImageVis3D, were used to analyze images, create 3D models of the liver and export them in OBJ images for performing a range of surgical procedures, and measure the accuracy of the size and weight of the liver, kidneys and arteries with their conformity to DICOM file. It is compared to the image processing before and after the conversion stage of medical image using the Python language program to ensure the integrity of the images after the conversion process is identical to the original pictures of DICOM without causing any distortions or changes to it. We reduce file size while maintaining the model’s highest quality, while employing mixed reality techniques, applied on Liver Surgical Operation [living donor liver Transplantation (LDLT)].

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

General Computer Science

Reference21 articles.

1. P. Haripriya and Dr.R. Porkodi, "An Efficient Storage and Retrieval of DICOM Objects using Big Data Technologies," International Journal of Advanced Research in Computer Science, pp. 271-274, 3 March 2017.

2. Eva Hnatkova, Petr Kratky and Zdenek Dvorak , "Conversion of 2D medical scan data into 3D printed models," Advances in Environmental Sciences, Development and Chemistry, p. 315–318, 2014.

3. Wikipedia, "https://en.wikipedia.org/wiki/DICOM," 29 https://en.wikipedia.org/wiki/DICOM 2018. [Online]. Available: https://en.wikipedia.org/wiki/DICOM.

4. DICOM and DICOMWeb, "Scope and Field of Application," in DICOM Part 1: Introduction and Overview , USA, the National Electrical Manufacturers Association, https://www.dicomstandard.org/current/, 2018, pp. 7-9.

5. Thomas Tolxdorff, Michal Vossberg and Dagmar Krefting, "DICOM Image Communication in Globus-Based Medical Grids," IEEE Transactions on Information Technology in Biomedicine, pp. 145 - 153, 2008.

Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DICOM: A Revolution in Facet of Maxillofacial Imaging;JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH;2024

2. Fabrication of Patient Specific Distal Femur with Additive Manufacturing;Smart Innovation, Systems and Technologies;2024

3. Tumor Visualization Model for Determining Pathway in Radiotherapy;Algorithms for Intelligent Systems;2023

4. Classification of Brain Tumors Using Hybridized Convolutional Neural Network in Brain MRI images;International Journal of Circuits, Systems and Signal Processing;2022-01-14

5. A Sensing Method of Network Security Situation Based on Markov Game Model;International Journal of Circuits, Systems and Signal Processing;2022-01-14

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3