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001-es BibID:	BIBFORM112171
035-os BibID:	(cikkazonosító)3861 (WoS)000997603500001 (Scopus)85160404373
Első szerző:	Kovács Ágnes Éva (mérnök)
Cím:	Comparative Analysis of Bone Ingrowth in 3D-Printed Titanium Lattice Structures with Different Patterns / Ágnes Éva Kovács, Zoltán Csernátony, Loránd Csámer, Gábor Méhes, Dániel Szabó, Mihály Veres, Mihály Braun, Balázs Harangi, Norbert Serbán, Lei Zhang, György Falk, Hajnalka Soósné Horváth, Sándor Manó
Dátum:	2023
ISSN:	1996-1944
Megjegyzések:	In this study, metal 3D printing technology was used to create lattice-shaped test specimens of orthopedic implants to determine the effect of different lattice shapes on bone ingrowth. Six different lattice shapes were used: gyroid, cube, cylinder, tetrahedron, double pyramid, and Voronoi. The lattice-structured implants were produced from Ti6Al4V alloy using direct metal laser sintering 3D printing technology with an EOS M290 printer. The implants were implanted into the femoral condyles of sheep, and the animals were euthanized 8 and 12 weeks after surgery. To determine the degree of bone ingrowth for different lattice-shaped implants, mechanical, histological, and image processing tests on ground samples and optical microscopic images were performed. In the mechanical test, the force required to compress the different lattice-shaped implants and the force required for a solid implant were compared, and significant differences were found in several instances. Statistically evaluating the results of our image processing algorithm, it was found that the digitally segmented areas clearly consisted of ingrown bone tissue; this finding is also supported by the results of classical histological processing. Our main goal was realized, so the bone ingrowth efficiencies of the six lattice shapes were ranked. It was found that the gyroid, double pyramid, and cube-shaped lattice implants had the highest degree of bone tissue growth per unit time. This ranking of the three lattice shapes remained the same at both 8 and 12 weeks after euthanasia. In accordance with the study, as a side project, a new image processing algorithm was developed that proved suitable for determining the degree of bone ingrowth in lattice implants from optical microscopic images. Along with the cube lattice shape, whose high bone ingrowth values have been previously reported in many studies, it was found that the gyroid and double pyramid lattice shapes produced similarly good results.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	Materials. - 16 : 10 (2023), p. 1-16. -
További szerzők:	Csernátony Zoltán (1959-2023) (ortopéd sebész, traumatológus) Csámer Lóránd (1983-) (mérnök) Méhes Gábor (1966-) (patológus) Szabó Dániel (1988-) (ortopéd sebész, traumatológus) Veres Mihály (fizikus) Braun Mihály (1966-) (vegyész, analitikus) Harangi Balázs (1986-) (programtervező matematikus) Serban Norbert Zhang, Lei (1988-) (orvos) Falk György Soósné Horváth Hajnalka (1982-) (mérnök) Manó Sándor (1977-) (gépészmérnök, számítógépes tervezőmérnök)
Pályázati támogatás:	GINOP-2.2.1-15-2017-00055 GINOP PD 137775 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM118112
035-os BibID:	(WoS)001037777900124 (Scopus)85166480507
Első szerző:	Serban Norbert
Cím:	Localization-Enhanced Voting-based Ensemble of Semantic Segmentation Models for Cervical Polyp Segmentation / Norbert Serban, Balazs Harangi
Dátum:	2023
Megjegyzések:	In this paper, we propose an automated cervical polyp detection method based on semantic segmentation and ensemble learning. As polyps may cause cancer both in the colon and cervical area, it is crucial to detect them at an early stage. Our solution combines U-Net, DeeplabV3+, and PSPNet segmentation models using the combination of the predicted regions to enhance the segmentation accuracy of the polyp and its boundaries. To evaluate the proposed ensemble-based system, we measured the accuracy performance compared to standard ensemble methods and other state-of-the-art segmentation techniques as our solution outperforms them both measured by the Jaccard and Dice scores.
ISBN:	9798350312249
Tárgyszavak:	előadáskivonat könyvrészlet cervical polyp semantic segmentation ensemble model
Megjelenés:	36th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2023 / ed. Sicilia R., Kane B., Almeida J. R.. - p. 712-715. -
További szerzők:	Harangi Balázs (1986-) (programtervező matematikus)
Internet cím:	DOI Intézményi repozitóriumban (DEA) tárolt változat
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