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Article ; Online: Evaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network

Seulgi Lee / Jong-Eun Kim

Journal of Clinical Medicine, Vol 11, Iss 852, p

2022 Volume 852

Abstract: Digital smile design (DSD) technology, which takes pictures of patients’ faces together with anterior dentition and uses them for prosthesis design, has been recently introduced. However, the limitation of DSD is that it evaluates a patient with only one ...

Abstract	Digital smile design (DSD) technology, which takes pictures of patients’ faces together with anterior dentition and uses them for prosthesis design, has been recently introduced. However, the limitation of DSD is that it evaluates a patient with only one photograph taken in a still state, and the patient’s profile cannot be observed from various viewpoints. Therefore, this study aims to segment the patient’s anterior teeth, gingiva and facial landmarks using YOLACT++. We trained YOLACT++ on the annotated data of the teeth, lips and gingiva from the Flickr-Faces-HQ (FFHQ) data. We evaluated that the model trained by 2D candid facial images for the detection and segmentation of smile characteristics. The results show the possibility of an automated smile characteristic identification system for the automatic and accurate quantitative assessment of a patient’s smile.
Keywords	deep learning ; digital smile design ; digital dentistry ; YOLACT++ ; detection ; segmentation ; Medicine ; R
Subject code	006
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Effects of surface glazing on the mechanical and biological properties of 3D printed permanent dental resin materials.

Nam, Na-Eun / Hwangbo, Na-Kyung / Kim, Jong-Eun

Journal of prosthodontic research

2023 Volume 68, Issue 2, Page(s) 273–282

Abstract: Purpose This study aimed to determine the surface glazing effect on the mechanical and biological properties of three-dimensional printed dental permanent resins.Methods Specimens were prepared using Formlabs, Graphy Tera Harz permanent, and NextDent C&B ...

Abstract	Purpose This study aimed to determine the surface glazing effect on the mechanical and biological properties of three-dimensional printed dental permanent resins.Methods Specimens were prepared using Formlabs, Graphy Tera Harz permanent, and NextDent C&B temporary crown resins. Specimens were divided into three groups: samples with untreated surfaces, glazed surfaces, and sand-glazed surfaces. The flexural strength, Vickers hardness, color stability, and surface roughness of the samples were analyzed to identify their mechanical properties. Their cell viability and protein adsorption were analyzed to identify their biological properties.Results The flexural strength and Vickers hardness of the samples with sand glazed and glazed surfaces were significantly increased. The color change was higher for surface untreated samples than that for the samples with sand-glazed and glazed surfaces. The surface roughness of the samples with sand-glazed and glazed surfaces was low. The samples with sand-glazed and glazed surfaces have low protein adsorption ability and high cell viability.Conclusions Surface glazing increased the mechanical strength, color stability, and cell compatibility, while reducing the Ra and protein adsorption of 3D-printed dental resins. Thus, a glazed surface exhibited a positive effect on the mechanical and biological properties of 3D-printed resins.
MeSH term(s)	Materials Testing ; Sand ; Surface Properties ; Printing, Three-Dimensional ; Resins, Synthetic ; Dental Materials
Chemical Substances	Sand ; Resins, Synthetic ; Dental Materials
Language	English
Publishing date	2023-06-22
Publishing country	Japan
Document type	Journal Article
ZDB-ID	2470657-7
ISSN	2212-4632 ; 1883-1958
ISSN (online)	2212-4632
ISSN	1883-1958
DOI	10.2186/jpr.JPR_D_22_00261
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Article: Evaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network.

Lee, Seulgi / Kim, Jong-Eun

Journal of clinical medicine

2022 Volume 11, Issue 3

Abstract: Digital smile design (DSD) technology, which takes pictures of patients' faces together with anterior dentition and uses them for prosthesis design, has been recently introduced. However, the limitation of DSD is that it evaluates a patient with only one ...

Abstract	Digital smile design (DSD) technology, which takes pictures of patients' faces together with anterior dentition and uses them for prosthesis design, has been recently introduced. However, the limitation of DSD is that it evaluates a patient with only one photograph taken in a still state, and the patient's profile cannot be observed from various viewpoints. Therefore, this study aims to segment the patient's anterior teeth, gingiva and facial landmarks using YOLACT++. We trained YOLACT++ on the annotated data of the teeth, lips and gingiva from the Flickr-Faces-HQ (FFHQ) data. We evaluated that the model trained by 2D candid facial images for the detection and segmentation of smile characteristics. The results show the possibility of an automated smile characteristic identification system for the automatic and accurate quantitative assessment of a patient's smile.
Language	English
Publishing date	2022-02-06
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662592-1
ISSN	2077-0383
ISSN	2077-0383
DOI	10.3390/jcm11030852
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Article ; Online: Evaluation metric of smile classification by peri-oral tissue segmentation for the automation of digital smile design.

Lee, Seulgi / Jin, Gan / Park, Ji-Hyun / Jung, Hoi-In / Kim, Jong-Eun

Journal of dentistry

2024 Volume 145, Page(s) 104871

Abstract: Objectives: This study aimed to develop and validate evaluation metric for an automated smile classification model termed the "smile index." This innovative model uses computational methods to numerically classify and analyze conventional smile types.!## ...

Abstract	Objectives: This study aimed to develop and validate evaluation metric for an automated smile classification model termed the "smile index." This innovative model uses computational methods to numerically classify and analyze conventional smile types. Methods: The datasets used in this study consisted of 300 images to verify, 150 images to validate, and 9 images to test the evaluation metric. Images were annotated using Labelme. Computational techniques were used to calculate smile index values for the study datasets, and the resulting values were evaluated in three stages. Results: The smile index successfully classified smile types using cutoff values of 0.0285 and 0.193. High accuracy (0.933) was achieved, along with an F1 score greater than 0.09. The smile index successfully reclassified smiles into six types (low, low-to-medium, medium, medium-to-high, high, and extremely high smiles), thereby providing a clear distinction among different smile characteristics. Conclusion: The smile index is a novel dimensionless parameter for classifying smile types. The index acts as a robust evaluation tool for artificial intelligence models that automatically classify smile types, thereby providing a scientific basis for largely subjective aesthetic elements. Clinical significance: The computational approach employed by the smile index enables quantitative numerical classification of smile types. This fosters the application of computerized methods in quantifying and analyzing real smile characteristics observed in clinical practice, paving the way for a more objective evidence-based approach to aesthetic dentistry.
Language	English
Publishing date	2024-02-01
Publishing country	England
Document type	Journal Article
ZDB-ID	186068-9
ISSN	1879-176X ; 0300-5712
ISSN (online)	1879-176X
ISSN	0300-5712
DOI	10.1016/j.jdent.2024.104871
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Article ; Online: Sulforaphene Attenuates

Hwang, Hwan Ju / Kim, Jong-Eun / Lee, Ki Won

Journal of microbiology and biotechnology

2022 Volume 32, Issue 11, Page(s) 1390–1395

Abstract: Acne is a chronic inflammatory disease of the sebaceous gland attached to the hair follicles. ...

Abstract	Acne is a chronic inflammatory disease of the sebaceous gland attached to the hair follicles.
MeSH term(s)	Humans ; Propionibacterium acnes ; Inflammation/drug therapy ; Acne Vulgaris/drug therapy ; Acne Vulgaris/microbiology ; Anti-Bacterial Agents/metabolism
Chemical Substances	sulphoraphene (NCO9MC39IO) ; Anti-Bacterial Agents
Language	English
Publishing date	2022-10-30
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2412195-2
ISSN	1738-8872 ; 1738-8872
ISSN (online)	1738-8872
ISSN	1738-8872
DOI	10.4014/jmb.2209.09051
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Article: Inhibitory Effect of Lotusine on Solar UV-Induced Matrix Metalloproteinase-1 Expression.

Ryu, Tae-Kyeong / Roh, Eunmiri / Shin, Han-Seung / Kim, Jong-Eun

Plants (Basel, Switzerland)

2022 Volume 11, Issue 6

Abstract: Solar ultraviolet (sUV) radiation remains a major cause of skin aging. ...

Abstract	Solar ultraviolet (sUV) radiation remains a major cause of skin aging.
Language	English
Publishing date	2022-03-14
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2704341-1
ISSN	2223-7747
ISSN	2223-7747
DOI	10.3390/plants11060773
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Article ; Online: Effect of air abrasion, acid etching, and aging on the shear bond strength with resin cement to 3Y-TZP zirconia.

Seo, Song-Hee / Kim, Jong-Eun / Nam, Na-Eun / Moon, Hong-Seok

Journal of the mechanical behavior of biomedical materials

2022 Volume 134, Page(s) 105348

Abstract: This study investigates the effect of acid etching treatment on the surface microstructure, surface roughness, and surface contact angle of zirconia and compares the effects of air abrasion, different etching times, and aging on the shear bond strength ( ... ...

Abstract	This study investigates the effect of acid etching treatment on the surface microstructure, surface roughness, and surface contact angle of zirconia and compares the effects of air abrasion, different etching times, and aging on the shear bond strength (SBS) of resin cement on the zirconia surface. 480 specimens (9 × 10 × 10 mm) were divided into as-sintered and air-abraded groups, and each group was further subdivided into six groups based on etching time (0, 3, 5, 10, 20, and 30 min). The etching solution comprised hydrofluoric acid 25%, sulfuric acid 16%, hydrogen peroxide, methyl alcohol, and purified water. The shear bond strength (SBS), scanning electron microscopy, surface roughness, contact angle, and failure mode were measured. The results indicated that the mean SBS values increased and decreased significantly when the etching times increased to 20 min and 30 min, respectively, in both groups. Further, SBS after aging was lower than that before aging in all groups. Sandblasting, etching time, and aging all showed significant effects (p < 0.001) in the three-way analysis of variance. In addition, the surface roughness increased and the contact angle decreased significantly with an increase in etching time. Thus, the acid-etching treatment induced significant changes on the zirconia surface and increased the SBS of the resin cement. The results of this in vitro study suggest that acid etching is a promising alternative for zirconia surface treatment.
MeSH term(s)	Ceramics/chemistry ; Dental Bonding ; Materials Testing ; Microscopy, Electron, Scanning ; Resin Cements/chemistry ; Shear Strength ; Surface Properties ; Yttrium/chemistry ; Zirconium/chemistry
Chemical Substances	Resin Cements ; Yttrium (58784XQC3Y) ; Zirconium (C6V6S92N3C) ; zirconium oxide (S38N85C5G0)
Language	English
Publishing date	2022-06-30
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2378381-3
ISSN	1878-0180 ; 1751-6161
ISSN (online)	1878-0180
ISSN	1751-6161
DOI	10.1016/j.jmbbm.2022.105348
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Article ; Online: Guided Bone Regeneration with a Nitric-Oxide Releasing Polymer Inducing Angiogenesis and Osteogenesis in Critical-Sized Bone Defects.

Won, Jong-Eun / Kim, Won Jong / Shim, Ji Suk / Ryu, Jae Jun

Macromolecular bioscience

2022 Volume 22, Issue 10, Page(s) e2200162

Abstract: Synthetic scaffolds, as bone grafts, provide a favorable environment for the repair and growth of new bone tissue at defect sites. However, the lack of angio- and osteo-induction limits the usefulness of artificial scaffolds for bone regeneration. Nitric ...

Abstract	Synthetic scaffolds, as bone grafts, provide a favorable environment for the repair and growth of new bone tissue at defect sites. However, the lack of angio- and osteo-induction limits the usefulness of artificial scaffolds for bone regeneration. Nitric oxide (NO) performs essential roles in healing processes, such as regulating inflammation and addressing incomplete revascularization. In this study, a polymer capable of controlled NO release is developed to promote the osteogenic capacity in artificial scaffolds. The biological efficiency of the NO compound is assessed by its effect on pre-osteoblasts and macrophages in vitro and the extent of vascularization and bone formation in the calvaria defect model in vivo. The compound does not inhibit cell adhesion or proliferation. NO treatment significantly increases both alkaline phosphatase activity and mineralization in pre-osteoblasts. Macrophages treated with NO secrete high levels of anti-inflammatory factors and adopt the pro-regenerative phenotype. In the critical-sized defect model, the collagen scaffold containing the NO compound enhances neovascularization and bone formation. The developed NO-releasing system promotes osteogenesis and regeneration of damaged bone tissue. As the multiple functions of NO involve macrophage modulation and angiogenesis, such release systems may be valuable for guiding bone regeneration in critical-sized defects.
MeSH term(s)	Alkaline Phosphatase/metabolism ; Bone Regeneration ; Cell Differentiation ; Collagen/metabolism ; Mesenchymal Stem Cells ; Nitric Oxide/metabolism ; Osteogenesis/genetics ; Polymers/metabolism ; Polymers/pharmacology ; Tissue Scaffolds
Chemical Substances	Polymers ; Nitric Oxide (31C4KY9ESH) ; Collagen (9007-34-5) ; Alkaline Phosphatase (EC 3.1.3.1)
Language	English
Publishing date	2022-08-03
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2039130-4
ISSN	1616-5195 ; 1616-5187
ISSN (online)	1616-5195
ISSN	1616-5187
DOI	10.1002/mabi.202200162
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Article: Higenamine Reduces Fine-Dust-Induced Matrix Metalloproteinase (MMP)-1 in Human Keratinocytes.

Kim, DongHyeon / Yun, JeaHyeok / Roh, Eunmiri / Shin, Han-Seung / Kim, Jong-Eun

Plants (Basel, Switzerland)

2023 Volume 12, Issue 13

Abstract: Environmental pollutants such as fine dust are increasingly linked to premature skin aging. In this study, we investigated the protective effects of higenamine, a natural plant alkaloid, against fine-dust-induced skin aging in human keratinocytes (HaCaT ... ...

Abstract	Environmental pollutants such as fine dust are increasingly linked to premature skin aging. In this study, we investigated the protective effects of higenamine, a natural plant alkaloid, against fine-dust-induced skin aging in human keratinocytes (HaCaT cells). We found that higenamine significantly attenuated fine-dust-induced expression of matrix metalloproteinase-1 (MMP-1), a key enzyme involved in collagen degradation. Furthermore, higenamine was found to modulate fine-dust-induced AP-1 and NF-κB transactivation, which are crucial factors for MMP-1 transcription. Higenamine also impeded fine-dust-induced phosphorylation in specific pathways related to AP-1 and NF-κB activation, and effectively alleviated reactive oxygen species (ROS) production, a key factor in oxidative stress caused by fine dust exposure. These results suggest that higenamine exerts protective effects against fine-dust-induced skin aging, primarily through its MMP-1 inhibitory properties and ability to mitigate ROS-induced oxidative damage. Our data highlight the potential of higenamine as an effective ingredient in skincare products designed to combat environmental skin damage.
Language	English
Publishing date	2023-06-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2704341-1
ISSN	2223-7747
ISSN	2223-7747
DOI	10.3390/plants12132479
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Article ; Online: Foreground Objects Detection by U-Net with Multiple Difference Images

Jae-Yeul Kim / Jong-Eun Ha

Applied Sciences, Vol 11, Iss 4, p

2021 Volume 1807

Abstract: In video surveillance, robust detection of foreground objects is usually done by subtracting a background model from the current image. Most traditional approaches use a statistical method to model the background image. Recently, deep learning has also ... ...

Abstract	In video surveillance, robust detection of foreground objects is usually done by subtracting a background model from the current image. Most traditional approaches use a statistical method to model the background image. Recently, deep learning has also been widely used to detect foreground objects in video surveillance. It shows dramatic improvement compared to the traditional approaches. It is trained through supervised learning, which requires training samples with pixel-level assignment. It requires a huge amount of time and is high cost, while traditional algorithms operate unsupervised and do not require training samples. Additionally, deep learning-based algorithms lack generalization power. They operate well on scenes that are similar to the training conditions, but they do not operate well on scenes that deviate from the training conditions. In this paper, we present a new method to detect foreground objects in video surveillance using multiple difference images as the input of convolutional neural networks, which guarantees improved generalization power compared to current deep learning-based methods. First, we adjust U-Net to use multiple difference images as input. Second, we show that training using all scenes in the CDnet 2014 dataset can improve the generalization power. Hyper-parameters such as the number of difference images and the interval between images in difference image computation are chosen by analyzing experimental results. We demonstrate that the proposed algorithm achieves improved performance in scenes that are not used in training compared to state-of-the-art deep learning and traditional unsupervised algorithms. Diverse experiments using various open datasets and real images show the feasibility of the proposed method.
Keywords	visual surveillance ; deep learning ; object detection ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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