- Tytuł:
- Classification and segmentation of periodontal cystfor digital dental diagnosis using deep learning
- Autorzy:
-
Lakshmi, T. K.
Dheeba, J. - Powiązania:
- https://bibliotekanauki.pl/articles/38700996.pdf
- Data publikacji:
- 2023
- Wydawca:
- Instytut Podstawowych Problemów Techniki PAN
- Tematy:
-
CNN
dental radiograph
deep learning
health care
machine transfer learning
periodontal cyst
predictive analytics
segmentation
U-Net
VGG16
rentgenowskie zdjęcie zębów
uczenie głębokie
opieka zdrowotna
uczenie się z transferu maszynowego
torbiel przyzębia
analityka predykcyjna
segmentacja - Opis:
- The digital revolution is changing every aspect of life by simulating the ways humansthink, learn and make decisions. Dentistry is one of the major fields where subsets ofartificial intelligence are extensively used for disease predictions. Periodontitis, the mostprevalent oral disease, is the main focus of this study. We propose methods for classifyingand segmenting periodontal cysts on dental radiographs using CNN, VGG16, and U-Net.Accuracy of 77.78% is obtained using CNN, and enhanced accuracy of 98.48% is obtainedthrough transfer learning with VGG16. The U-Net model also gives encouraging results.This study presents promising results, and in the future, the work can be extended withother pre-trained models and compared. Researchers working in this field can develop novelmethods and approaches to support dental practitioners and periodontists in decision-making and diagnosis and use artificial intelligence to bridge the gap between humansand machines.
- Źródło:
-
Computer Assisted Methods in Engineering and Science; 2023, 30, 2; 131-149
2299-3649 - Pojawia się w:
- Computer Assisted Methods in Engineering and Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł