Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography

Original Article

First Online:

Abstract

Objectives

To apply a deep-learning system for diagnosis of maxillary sinusitis on panoramic radiography, and to clarify its diagnostic performance.

Methods

Training data for 400 healthy and 400 inflamed maxillary sinuses were enhanced to 6000 samples in each category by data augmentation. Image patches were input into a deep-learning system, the learning process was repeated for 200 epochs, and a learning model was created. Newly-prepared testing image patches from 60 healthy and 60 inflamed sinuses were input into the learning model, and the diagnostic performance was calculated. Receiver-operating characteristic (ROC) curves were drawn, and the area under the curve (AUC) values were obtained. The results were compared with those of two experienced radiologists and two dental residents.

Results

The diagnostic performance of the deep-learning system for maxillary sinusitis on panoramic radiographs was high, with accuracy of 87.5%, sensitivity of 86.7%, specificity of 88.3%, and AUC of 0.875. These values showed no significant differences compared with those of the radiologists and were higher than those of the dental residents.

Conclusions

The diagnostic performance of the deep-learning system for maxillary sinusitis on panoramic radiographs was sufficiently high. Results from the deep-learning system are expected to provide diagnostic support for inexperienced dentists.
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Five Key Questions To Ask Your Dental Imaging Vendor

Five Key Questions to Ask Your Imaging Vendor?
Tis the time of year when you may be looking to invest in your practice and take advantage of the Section 179 Election to reduce 2018 taxes.  Here are five things to ask your potential vendor before purchasing crucial imaging hardware or software as part of a holiday shopping spree:
1.Is your solution designed to be plug and play?
Vendors are in two camps today.  Those that sell closed proprietary systems and those that provideopen platforms.  You may be buying new hardware or upgrading your imaging software. In either case, you need to know if the new software system integrates with your existing hardware or will that new piece of hardware play nicely with your existing imaging software.  
This is especially important because high-quality hardware solutions are now available at significantly reduced costs . . . but only if you’re not locked into expensive premium brands. This trend will continue, and you want to be positioned to take advantage of new products, with advanced features, at the best value.  Ask “Do you integrate with everybody or only a select set of products?
2.Can you convert my existing data?
You don’t want to maintain two different imaging software systems for any significant period of time. Be sure that your potential vendor has expertise in merging x-rays, scans, photos, and templates from your legacy system, so you can manage all your images from a single database. A good database conversion service will maintain image quality and embedded information such as patient demographic data, tooth numbers and acquisition dates. Ask about the cost of conversion services, the time the conversion will require, and what steps the vendor takes to ensure that the conversion will not disrupt to office productivity.
3What is your warranty or replacement policy?
Some companies sell hardware and some sell service.  It’s not uncommon to find two-yearwarranties included in hardware purchases – I’ve even seen three years offered in some cases. Be sure to find out if there are on-going monthly or yearly fees that come along with a specific imaging hardware purchase.
4.How does your technical support work?
When your team needs support, you need to know they can pick up the phone and get timely and effective resolution.  In some cases, the company selling you hardware is reselling someone else’s software. That may be okay, but you should know if you’ll be working with someone else for support. Be sure you’ll have access to high quality first, second, and third level technical support from people that know the system top to bottom.  Also ask what associated fees for support will be – if you shop smartly you may be able to get six months to year of support free of charge.
5.What additional capabilities do I get with your hardware or software?
It’s one thing to have a platform that will take and store your images. It’s entirely another matter as to whether that platform supports or improves your practice workflowHow easy is it to work with the data once it’s been acquired?  Is submitting images to insurance companies or running reportsstraight forwardCan information be easily forwarded to a specialist? If working with CBCT scans,is 3D viewing supported?  If you’re on vacation and somebody needs a referral how easily can you access that data? If universal remote access is important a cloud-based solution may be of interest.  
The major imaging suppliers typically offer attractive year end specials. Here’s one (Holiday Sensor Special) that appears to check all the boxes, from Apteryx – the company that has developed about half of all the imaging software in the market (sold under 15 brand names including Xrayvision, Prof Suniand Cliniview).
Shop Wisely and Have A Happy Holiday! 
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Cyclic fatigue resistance of three rotary file systems in a dynamic model after immersion in sodium hypochlorite

Odontology

pp 1–9 | Cite as

Original Article

First Online:

Abstract

To evaluate the effect of immersion in 3% sodium hypochlorite solution in the resistance to cyclic fatigue of three nickel–titanium (NiTi) rotary file systems, ProTaper Next (PTN), Hyflex CM (CM), and Hyflex EDM (EDM), in a mechanical model featuring axial movement. Ninety instruments of three different NiTi rotary file systems, PTN (size 25, 0.06 taper), CM (25, 0.06), and EDM (25/~, variable taper), were randomly divided according to a 3 × 3 factorial design and tested under dynamic immersion in a 3% NaOCl solution (1 or 5 min) or without immersion, making a total of 9 groups (n = 10). Files were tested in an artificial root canal with 45° angle and 5 mm radius apical curvature being submitted to back-and-forth movements until fracture. Statistical analysis was performed using two-way factorial ANOVA with Bonferroni post-hoc tests, at a significance level of 5%. Instruments were evaluated for reliability using a Weilbull approach. Regardless of the immersion treatment, PTN had on average 1200 ± 178 cycles to fracture, CM had 1949 ± 362, and EDM had 5573 ± 853, which was a significantly different (P < 0.01). The NaOCl immersion promoted a significant reduction in the mean number of cycles to fracture (P = 0.01), and was reflected in a significant reduction of the characteristic life of the instruments of the CM end EDM groups. Within this study conditions, EDM instruments performed better to cyclic fatigue followed by CM and then PTN. Immersion in NaOCl decreased the resistance to cyclic fatigue of all tested instruments, but affected more those manufactured from CM wire.
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Effect of diode laser irradiation on the bond strength of polymerized non-simplified adhesive systems after 12 months of water storage

Journal of Applied Oral Science
J. Appl. Oral Sci. vol.27  Bauru  2019  Epub Dec 10, 2018

http://dx.doi.org/10.1590/1678-7757-2018-0126 

Objectives:

The aim of this in vitro study was to evaluate the bonding strength of non-simplified dentin bonding systems (DBS) to dentin irradiated with a diode laser (970 nm) immediately and after 12 months of water storage following either primer or bond application.

Material and methods:

The experimental design included three different factors: DBS type [AdperTM Scotchbond Multipurpose (MP) and Clearfil™ SE Bond (CSE)], irradiation [without irradiation – control (C), irradiation after primer application (AP), and irradiation after bond application (AB)], and time [initial (I) and after 12 months of water storage (12 m)]. Sixty sound human third molars (n = 10) were obtained, and their flat occlusal dentin areas were prepared and standardized. Laser irradiation was performed in the contact mode perpendicular to the dental surface over an automatically selected scanning area at a pulse energy of 0.8 W, frequency of 10 Hz, and energy density of 66.67 J/cm2. After 7 days of treatment, the specimens were cut, and half of them were subjected to microtensile testing (500 N/0.05 mm/min), whereas the remaining sticks were examined after 12 months of water storage. The obtained data were analyzed by three-way analysis of variance (ANOVA) followed by a Tukey test (p<0 .05="" 40x.="" a="" digital="" fracture="" investigated="" magnification="" microscope="" modes="" observed="" of="" p="" portable="" the="" using="" were="" with="">

Results:

Among the utilized DBS, MP generally exhibited higher bond strengths, but did not always differ from CSE under similar conditions. The irradiation factor was statistically significant only for the MP/AB groups. After 12 months of storage, all groups demonstrated a significant reduction in the bond strength, whereas the results of fracture analysis showed a predominance of the adhesive type.

Conclusions:

The laser treatment of non-simplified DBS was not able to stabilize their bonding characteristics after 12 months.

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Effects of in-office bleaching agent combined with different desensitizing agents on enamel

Journal of Applied Oral Science
J. Appl. Oral Sci. vol.27  Bauru  2019  Epub Nov 08, 2018

http://dx.doi.org/10.1590/1678-7757-2018-0233 

Objective:

To analyze color change, microhardness and chemical composition of enamel bleached with in-office bleaching agent with different desensitizing application protocols.

Materials and Methods:

One hundred and seventeen polished anterior human enamel surfaces were obtained and randomly divided into nine groups (n = 13). After recording initial color, microhardness and chemical composition, the bleaching treatments were performed as G1: Signal Professional White Now POWDER&LIQUID FAST 38% Hydrogen peroxide(S); G2: S+Flor Opal/0.5% fluoride ion(F); G3: S+GC Tooth Mousse/Casein Phosphopeptide-Amorphous Calcium Phosphate (CPP-ACP) paste(TM); G4: S+UltraEZ/3% potassium nitrate&0.11% fluoride(U); G5: S+Signal Professional SENSITIVE PHASE 1/30% Nano-Hydroxyapatite (n-HAP) suspension(SP); G6: S-F mixture; G7: S-TM mixture; G8: S-U mixture; G9: S-SP mixture. Color, microhardness and chemical composition measurements were repeated after 1 and 14 days. The percentage of microhardness loss (PML) was calculated 1 and 14 days after bleaching. Data were analyzed with ANOVA, Welch ANOVA, Tukey and Dunnett T3 tests (p<0 .05="" p="">

Results:

Color change was observed in all groups. The highest ΔE was observed at G7 after 1 day, and ΔE at G8 was the highest after 14 days (p<0 .05="" 14="" 1="" a="" after="" all="" and="" bleaching="" comparison="" day.="" day="" days="" decrease="" except="" g6="" g7="" groups="" in="" increased="" microhardness="" observed="" of="" p="" the="" was="" with="">0.05). PML was observed in all groups except G6 and G7 after bleaching and none of the groups showed PML after 14 days. No significant changes were observed after bleaching at Ca and P levels and Ca/P ratios at 1 or 14 days after bleaching (p>0.05). F mass increased only in G2 and G6, 1 day after bleaching (p<0 .05="" p="">

Conclusions:

The use of desensitizing agents containing fluoride, CPP-ACP, potassium nitrate or n-HAP after in-office bleaching or mixed in bleaching agent did not inhibit the bleaching effect. However, they all recovered microhardness of enamel 14 days after in-office bleaching.

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