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Second Opinion® CS is a computer aided detection ("CADe") software to aid in the detection and segmentation of caries in periapical radiographs. It is designed to aid dental health professionals to review periapical radiographs of permanent teeth in patients 12 years of age or older as a second reader.

Second Opinion CS detects suspected carious lesions and presents them as an overlay of segmented contours. The software highlights detected caries with an overlay and provides a detailed analysis of the lesion's overlap with dentine and enamel, presented as a percentage. The output of Second Opinion CS is a visual overlay of regions of the input radiograph which have been detected as potentially containing caries. The user can hover over the caries detection to see the segmentation analysis. Second Opinion PC consists of three parts: - Application Programing Interface ("API") - Machine Learning Modules ("ML Modules") - Client User Interface ("Client") The processing sequence for an image is as follows: 1. Images are sent for processing via the API 2. The API routes images to the ML modules 3. The ML modules produce detection output 4. The UI renders the detection output The API serves as a conduit for passing imagery and metadata between the user interface and the machine learning modules. The API sends imagery to the machine learning modules for processing and subsequently receives metadata generated by the machine learning modules which is passed to the interface for rendering. Second Opinion CS uses machine learning to detect and segment caries. Images received by the ML modules are processed yielding detections which are represented as metadata. The final output is made accessible to the API for the purpose of sending to the UI for visualization. Detected carious lesions are displayed as overlays atop the original radiograph which indicate to the practitioner which teeth contain which detected carious lesions that may require clinical review. The clinician can toggle over the image to highlight a potential condition for viewing. Further, the clinician can hover over the detected caries to show a hover information box containing the segmentation of the caries in the form of percentages.

Second Opinion® BLE is a radiological automated image processing software device intended to identify and display bone level measurements in bitewing and periapical radiographs. It should not be used in lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older as a concurrent and second reader.

Second Opinion BLE is a radiological automated image processing software device intended to identify and display bone level measurements in bitewing and periapical radiographs. It should not be used in lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older as a concurrent and second reader. Second Opinion BLE consists of three parts: - Application Programing Interface ("API") - Machine Learning Modules ("ML Modules") - Client User Interface (UI) ("Client") The processing sequence for an image is as follows: 1. Images are sent for processing via the API 2. The API routes images to the ML modules 3. The ML modules produce detection output 4. The UI renders the detection output The API serves as a conduit for passing imagery and metadata between the user interface and the machine learning modules. The API sends imagery to the machine learning modules for processing and subsequently receives metadata generated by the machine learning modules which is passed to the interface for rendering. Second Opinion BLE uses machine learning to detect bone level measurements. Images received by the ML modules are processed yielding detections which are represented as metadata. The final output is made accessible to the API for the purpose of sending to the UI for visualization. Detected bone level measurements are displayed as linear overlays atop the original radiograph which indicate to the practitioner which regions contain which detected potential conditions that may require clinical review. The clinician can toggle over the image to highlight a potential condition for viewing.

Second Opinion PC is a computer aided detection ("CADe") software to aid dentists in the detection of periapical radiolucencies by drawing bounding polygons to highlight the suspected region of interest. It is designed to aid dental health professionals to review periapical radiographs of permanent teeth in patients 12 years of age or older as a second reader.

Second Opinion PC (Periapical Radiolucency Contouring) is a radiological, automated, computer-assisted detection (CADe) software intended to aid in the detection of periapical radiolucencies on periapical radiographs using polygonal contours. The device is not intended as a replacement for a complete dentist's review or their clinical judgment which considers other relevant information from the image, patient history, or actual in vivo clinical assessment. Second Opinion PC consists of three parts: - Application Programing Interface ("API") - Machine Learning Modules ("ML Modules") - Client User Interface ("Client") The processing sequence for an image is as follows: 1. Images are sent for processing via the API 2. The API routes images to the ML modules 3. The ML modules produce detection output 4. The UI renders the detection output The API serves as a conduit for passing imagery and metadata between the user interface and the machine learning modules. The API sends imagery to the machine learning modules for processing and subsequently receives metadata generated by the machine learning modules which is passed to the interface for rendering. Second Opinion PC uses machine learning to detect periapical radiolucencies. Images received by the ML modules are processed yielding detections which are represented as metadata. The final output is made accessible to the API for the purpose of sending to the UI for visualization. Detected periapical radiolucencies are displayed as polygonal overlays atop the original radiograph which indicate to the practitioner which teeth contain which detected periapical radiolucencies that may require clinical review. The clinician can toggle over the image to highlight a potential condition for viewing.

Second Opinion® CC is a computer aided detection ("CADe") software to aid dentists in the detection of caries by drawing bounding polygons to highlight the suspected region of interest. It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 19 years of age or older as a second reader.

Second Opinion CC (Caries Contouring) is a radiological, automated, computer-assisted detection (CADe) software intended to aid in the detection of caries on bitewing and periapical radiographs using polygonal contours. The device is not intended as a replacement for a complete dentist's review or their clinical judgment which considers other relevant information from the image, patient history, or actual in vivo clinical assessment. Second Opinion CC consists of three parts: - · Application Programing Interface ("API") - · Machine Learning Modules ("ML Modules") - · Client User Interface ("Client") The processing sequence for an image is as follows: - Images are sent for processing via the API 1. - 2. The API routes images to the ML modules - 3. The ML modules produce detection output - 4. The UI renders the detection output The API serves as a conduit for passing imagery and metadata between the user interface and the machine learning modules. The API sends imagery to the machine learning modules for processing and subsequently receives metadata generated by the machine learning modules which is passed to the interface for rendering. Second Opinion CC uses machine learning to detect caries. Images received by the ML modules are processed yielding detections which are represented as metadata. The final output is made accessible to the API for the purpose of sending to the UI for visualization. Detected carious lesions are displayed as polygonal overlays atop the original radiograph which indicate to the practitioner which teeth contain which detected carious lesions that may require clinical review. The clinician can toggle over the image to highlight a potential condition for viewing. In addition, the clinician has the ability to edit the detections as they see fit to align with their diagnosis.

Second Opinion® is a computer aided detection ("CADe") software to identify and mark regions in relation to suspected dental findings which include Caries, Discrepancy at the margin of an existing restoration, Calculus, Periapical radiolucency, Crown (metal, including zirconia & non-metal), Filling (metal & non-metal), Root canal, Bridge and Implants. It is designed to aid dental health professionals to review bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older as a second reader.

Second Opinion®is a computer aided detection ("CADe") software device indicated for use by dental health professionals as an aid in their assessment of bitewing and periapical radiographs of permanent teeth in patients 12 years of age or older. Second Opinion® employs computer vision technology, developed using machine learning techniques, to detect and draw attention as second reader to regions on bitewing and periapical radiographs where distinct pathologic and/or nonpathologic dental features may appear. Second Opinion® consists of three parts: - In-office application or Client User Interface ("Client") - Application Programing Interface ("API") - Computer Vision Models ("CV Model", "CV Models") The Client resides in the clinician's office. The API and CV Models reside in a cloud computing platform, where image processing takes place. The CV Models create and append to a metadata file information denoting pixel regions and other associated properties of each radiograph. Those associated properties include: - Normal anatomy (e.g., Teeth) - Nine radiological dental findings, which include five restorations (crowns, bridges, implants, root canals, fillings) and four pathologies (caries, marqin discrepancy -MD, calculus, periapical radiolucency - PR) The API delivers the metadata back to Second Opinion® via the cloud. The metadata information is displayed in graphical form to clinical users by way of the Second Opinion® Client's user interface.