Caries Detection with Near-Infrared Transillumination Using Deep Learning

Caries Detection Using Near-Infrared Transillumination: Adding Objectivity to Diagnosis to Save Tooth Structure.

Caries detection and diagnostics with near-infrared light transillumination: clinical experiences.

OBJECTIVE The aim of this paper was to present the function and potential of diagnosing caries lesions using a recently introduced near-infrared (NIR) transillumination technique (DIAGNOcam, KaVo). METHOD AND MATERIALS The study included 130 adolescents and adults with complete permanent dentition (age > 12). All patients underwent visual examination and, if necessary, bitewing radiographs. P...

Comparison of diagnostic methods for early interproximal caries detection with near-infrared light transillumination: an in vivo study

BACKGROUND Although numerous studies have used digital intraoral imaging, only a few studies have used photo-optical methods for the diagnosis of caries. Moreover, several limitations exist in terms of observers (experience and specialty) and the caries lesion itself. Hence, the aims of this study were to evaluate the diagnostic capability of near-infrared light transillumination (NILT) and PSP...

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Detection of Tooth caries in Bitewing Radiographs using Deep Learning

We develop a Computer Aided Diagnosis (CAD) system, which enhances the performance of dentists in detecting wide range of dental caries. The CAD System achieves this by acting as a second opinion for the dentists with way higher sensitivity on the task of detecting cavities than the dentists themselves. We develop annotated dataset of more than 3000 bitewing radiographs and utilize it for devel...