Options for Camera Raw in the Digital Workflow

2014 ◽  
Author(s):  
Keith Hogan
Keyword(s):  
Digital Workflow

A Full Digital Workflow for the Duplication of an Existing Implant Retained Overdenture Prosthesis: A Novel Approach

2021 ◽  
Author(s):  
Theodoros Tasopoulos ◽  
George Kouveliotis ◽  
Ioannis Karoussis ◽  
Nelson Rfa Silva ◽  
Panagiotis Zoidis
Keyword(s):  
Digital Workflow ◽  
Novel Approach

scholarly journals Accuracy, Labor-Time and Patient-Reported Outcomes with Partially versus Fully Digital Workflow for Flapless Guided Dental Implants Insertion—A Randomized Clinical Trial with One-Year Follow-Up

2021 ◽  
Vol 10 (5) ◽  
pp. 1102
Author(s):  
Corina Marilena Cristache ◽  
Mihai Burlibasa ◽  
Ioana Tudor ◽  
Eugenia Eftimie Totu ◽  
Fabrizio Di Francesco ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Randomized Clinical Trial ◽  
Dental Implants ◽  
Entry Point ◽  
Angular Deviation ◽  
Digital Workflow ◽  
Position Information ◽  
Patient Reported ◽  
The Mean ◽  
Edentulous Patients

(1) Background: Prosthetically-driven implant positioning is a prerequisite for long-term successful treatment. Transferring the planned implant position information to the clinical setting could be done using either static or dynamic guided techniques. The 3D model of the bone and surrounding structures is obtained via cone beam computed tomography (CBCT) and the patient’s oral condition can be acquired conventionally and then digitalized using a desktop scanner, partially digital workflow (PDW) or digitally with the aid of an intraoral scanner (FDW). The aim of the present randomized clinical trial (RCT) was to compare the accuracy of flapless dental implants insertion in partially edentulous patients with a static surgical template obtained through PDW and FDW. Patient outcome and time spent from data collection to template manufacturing were also compared. (2) Methods: 66 partially edentulous sites (at 49 patients) were randomly assigned to a PDW or FDW for guided implant insertion. Planned and placed implants position were compared by assessing four deviation parameters: 3D error at the entry point, 3D error at the apex, angular deviation, and vertical deviation at entry point. (3) Results: A total of 111 implants were inserted. No implant loss during osseointegration or mechanical and technical complications occurred during the first-year post-implants loading. The mean error at the entry point was 0.44 mm (FDW) and 0.85 (PDW), p ≤ 0.00; at implant apex, 1.03 (FDW) and 1.48 (PDW), p ≤ 0.00; the mean angular deviation, 2.12° (FDW) and 2.48° (PDW), p = 0.03 and the mean depth deviation, 0.45 mm (FDW) and 0.68 mm (PDW), p ≤ 0.00; (4) Conclusions: Despite the statistically significant differences between the groups, and in the limits of the present study, full digital workflow as well as partially digital workflow are predictable methods for accurate prosthetically driven guided implants insertion.

scholarly journals Digital Workflow to Fabricate Complete Dentures for Edentulous Patients Using a Reversing and Superimposing Technique

2021 ◽  
Vol 11 (13) ◽  
pp. 5786
Author(s):  
Hwa-Jung Lee ◽  
Jeongho Jeon ◽  
Hong Seok Moon ◽  
Kyung Chul Oh
Keyword(s):  
Additive Manufacturing ◽  
Computer Aided Design ◽  
Digital Data ◽  
Complete Dentures ◽  
Intraoral Scanner ◽  
Digital Workflow ◽  
Denture Base ◽  
Scan Data ◽  
Edentulous Patients ◽  
Aided Design

This technical procedure demonstrates a 4-step completely digital workflow for the fabrication of complete dentures in edentulous patients. The digital scan data of the edentulous arches were obtained using an intraoral scanner, followed by the fabrication of modeless trial denture bases using additive manufacturing. Using the trial denture base and a wax rim assembly, the interarch relationship was recorded. This record was digitized using an intraoral scanner and reversed for each maxillary and mandibular section individually. The digital scan data directly obtained using the intraoral scanner were superimposed over the reversed data, establishing a proper interarch relationship. The artificial teeth were arranged virtually and try-in dentures were additively manufactured. Subsequently, the gingival and tooth sections were additively manufactured individually and characterized. Thus, fabrication of digital complete dentures can be accomplished using digital data characteristics. The workflow includes data acquisition using an intraoral scanner, data processing using reverse engineering and computer-aided design software programs, and additive manufacturing.

Digital Workflow to Enhance Reservoir Management Strategies for A Complex Oil Field Through Real Time and Advanced Engineering Monitoring Solution

2021 ◽  
Author(s):  
Julieta Alvarez ◽  
Oswaldo Espinola ◽  
Luis Rodrigo Diaz ◽  
Lilith Cruces
Keyword(s):  
Real Time ◽  
Reservoir Characterization ◽  
Management Strategies ◽  
Reservoir Management ◽  
Gas Production ◽  
Oil Field ◽  
Oil Reservoirs ◽  
Production Operation ◽  
Digital Workflow ◽  
Operational Decisions

Abstract Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.

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