Automatic caries detection in bitewing radiographs-Part II: experimental comparison

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064165%3A_____%2F24%3A10469921" target="_blank" >RIV/00064165:_____/24:10469921 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/24:00373356 RIV/00216208:11110/24:10469921

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=bOrgQJEgP-" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=bOrgQJEgP-</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00784-024-05528-2" target="_blank" >10.1007/s00784-024-05528-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic caries detection in bitewing radiographs-Part II: experimental comparison

Popis výsledku v původním jazyce

Objective: The objective of this study was to compare the detection of caries in bitewing radiographs by multiple dentists with an automatic method and to evaluate the detection performance in the absence of reliable ground truth.Materials and Methods: Four experts and three novices marked caries using bounding boxes in 100 bitewing radiographs. The same dataset was processed by an automatic object detection deep learning method. All annotators were compared in terms of the number of errors and intersection over union (IoU) using pairwise comparisons, with respect to the consensus standard, and with respect to the annotator of the training dataset of the automatic method.Results: The number of lesions marked by experts in 100 images varied between 241 and 425. Pair- wise comparisons showed that the automatic method outperformed all dentists except the original annotator in the mean number of errors, while being among the best in terms of IoU. With respect to a consensus standard, the performance of the automatic method was best in terms of the num- ber of errors and slightly below average in terms of IoU. Compared with the original annotator, the automatic method had the highest IoU and only one expert made fewer errors.Conclusions: Caries detection is challenging even for humans. The automatic method consistently outperformed less experienced dentists and performed as well as highly experienced dentists. Clinical Significance: The consensus in caries detection between experts is low. An automatic method can improve both the accuracy and repeatability of caries detection, providing a useful second opinion even for very experienced dentists.

Název v anglickém jazyce

Automatic caries detection in bitewing radiographs-Part II: experimental comparison

Popis výsledku anglicky

Objective: The objective of this study was to compare the detection of caries in bitewing radiographs by multiple dentists with an automatic method and to evaluate the detection performance in the absence of reliable ground truth.Materials and Methods: Four experts and three novices marked caries using bounding boxes in 100 bitewing radiographs. The same dataset was processed by an automatic object detection deep learning method. All annotators were compared in terms of the number of errors and intersection over union (IoU) using pairwise comparisons, with respect to the consensus standard, and with respect to the annotator of the training dataset of the automatic method.Results: The number of lesions marked by experts in 100 images varied between 241 and 425. Pair- wise comparisons showed that the automatic method outperformed all dentists except the original annotator in the mean number of errors, while being among the best in terms of IoU. With respect to a consensus standard, the performance of the automatic method was best in terms of the num- ber of errors and slightly below average in terms of IoU. Compared with the original annotator, the automatic method had the highest IoU and only one expert made fewer errors.Conclusions: Caries detection is challenging even for humans. The automatic method consistently outperformed less experienced dentists and performed as well as highly experienced dentists. Clinical Significance: The consensus in caries detection between experts is low. An automatic method can improve both the accuracy and repeatability of caries detection, providing a useful second opinion even for very experienced dentists.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30208 - Dentistry, oral surgery and medicine

Projekt

<a href="/cs/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Clinical Oral Investigations

ISSN

1432-6981

e-ISSN

1436-3771

Svazek periodika

28

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

10

Strana od-do

133

Kód UT WoS článku

001156150200002

EID výsledku v databázi Scopus

2-s2.0-85184407305