Operational Research and Reconstruction Methods in Medical Imaging DOI Open Access
PremaLatha Velagapalli, Nikhat Parveen,

Velagapudi Sreenivas

et al.

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(2)

Published: April 15, 2025

With the widespread availability of 3D printing technology, there's potential to address issue replacement parts for broken objects. Traditional methods Printing will face a Challenge replicate accurately pieces, specifically fracture lines that can be complex geometry. In this paper we discuss about novel approach: Neural Network system which is optimized in Hybrid designed reconstructing objects automatically such as toys, vessels, pots and medical related images. This process includes several key stages like acquisition image, preprocessing, extraction features, recognition, alignment matching fragments. First eliminate noise from they are scanned by using preprocessing so data clean input forwarded next step. To identify quantify geometric feature use feature, texture characteristics, fragments boundaries edges also extracted. stage try determine placement within object match accordingly. A function fitness hybrid uses techniques optimization align fit improve accuracy.

Language: Английский

Operational Research and Reconstruction Methods in Medical Imaging DOI Open Access
PremaLatha Velagapalli, Nikhat Parveen,

Velagapudi Sreenivas

et al.

International Journal of Computational and Experimental Science and Engineering, Journal Year: 2025, Volume and Issue: 11(2)

Published: April 15, 2025

With the widespread availability of 3D printing technology, there's potential to address issue replacement parts for broken objects. Traditional methods Printing will face a Challenge replicate accurately pieces, specifically fracture lines that can be complex geometry. In this paper we discuss about novel approach: Neural Network system which is optimized in Hybrid designed reconstructing objects automatically such as toys, vessels, pots and medical related images. This process includes several key stages like acquisition image, preprocessing, extraction features, recognition, alignment matching fragments. First eliminate noise from they are scanned by using preprocessing so data clean input forwarded next step. To identify quantify geometric feature use feature, texture characteristics, fragments boundaries edges also extracted. stage try determine placement within object match accordingly. A function fitness hybrid uses techniques optimization align fit improve accuracy.

Language: Английский

Citations

1