Prior art — US Patent 10755409

To identify the most relevant prior art for US Patent 10755409, I will examine the patent citations. The patent itself mentions two key prior art documents: US 2009/0291417 and WO 2016/066651.

Based on the patent text, here's an analysis of the cited prior art:

1. US 2009/0291417

Full Citation: US 2009/0291417 A1 (or US '417)
Publication/Filing Date: The patent states "US 2009/0291417 describes a method making it possible to create, then modify, three-dimensional models, particularly for the manufacture of orthodontic appliances." The publication number indicates a publication date in 2009.
Brief Description: This prior art describes a method for creating and modifying three-dimensional models, specifically for the manufacture of orthodontic appliances.
Potential Anticipation (35 U.S.C. § 102): US 2009/0291417 generally teaches the creation and modification of 3D dental models. This broadly covers aspects related to the "updated reference model" and "initial reference model" in US10755409, particularly in the context of orthodontic treatment planning. It could potentially anticipate the fundamental concept of generating and manipulating 3D models of dental arches for orthodontic purposes, as described in Step A) and A') of the learning base enrichment method in US10755409. Specifically, the introductory statement in US10755409 that "The most recent orthodontic treatments use images to assess the therapeutic situations" and its subsequent aim to address the need for simplifying image analysis, imply that the underlying use of models and images for assessment was known. Therefore, claims related to the initial creation and modification of 3D models as a preliminary step to the image analysis, without the specific deep learning or automated image acquisition and feedback mechanisms, might be anticipated.

2. WO 2016/066651

Full Citation: WO 2016/066651 A1 (or WO '651)
Publication/Filing Date: The patent consistently refers to it as "WO 2016/066651," indicating a publication year of 2016. The priority date of US10755409 is July 21, 2017, meaning WO 2016/066651 is indeed prior art.
Brief Description: WO 2016/066651 describes a method for checking the positioning, shape, and/or appearance of a patient's teeth. This method involves creating an initial reference model, then at a later "updated instant," creating an updated reference model by deforming the initial model. This deformation is guided by "updated images" (e.g., photos or videos taken by the patient). The patent also mentions that WO 2016/066651 requires an appointment with an orthodontist to create the initial reference model.
Potential Anticipation (35 U.S.C. § 102): WO 2016/066651 is explicitly cited as closely related and forms a significant basis upon which US10755409 builds and differentiates itself. US10755409 states that its enrichment method (steps A'-C') can comprise "one or more of the features of the steps c), d) and e) of WO 2016 066651." It also mentions that "each execution of the method described in WO 2016/066651 preferably generates more than three...updated images which, by an automated processing by means of the updated reference model, may produce as many historical images."

Therefore, WO 2016/066651 directly anticipates several aspects of US10755409, particularly in the methods for enriching a learning base (steps A-F and A'-C') and methods for acquiring images.
- Generation of updated reference models by deformation of an initial model: The core concept of taking an initial model and deforming it based on subsequent images (updated images) to create an updated reference model, as described in WO 2016/066651, is directly carried over into steps A' and C' of US10755409's enrichment method.
- Acquisition of updated images by the patient: WO 2016/066651 describes patients acquiring their own "updated images," which is a key aspect of US10755409's methods.
- Searching for virtual acquisition conditions: The process of comparing updated images with views of a reference model to find "virtual acquisition conditions" that exhibit a maximal match, including the use of metaheuristic methods (like simulated annealing), is explicitly described as being part of WO 2016/066651 and is directly incorporated or built upon in step C) and C') of US10755409.
- Image processing for discriminating information: The extraction of discriminating information items (e.g., contours) and their representation as "maps" for comparison between images, as detailed in US10755409 (e.g., step C3), is also described as being part of WO 2016/066651.
US10755409 primarily distinguishes itself by applying deep learning to these existing image and model processing techniques, particularly for automated analysis, attribute determination, and feedback during image acquisition. The invention in US10755409 focuses on using a deep learning device for the analysis of dental arch images to determine tooth attributes or image attributes, and the subsequent actions based on these determinations (e.g., sending messages or assessing aligner suitability). Therefore, the underlying image acquisition, model generation, and comparison techniques themselves, without the integration of deep learning for automated attribute determination and feedback, would likely be anticipated by WO 2016/066651.

Claims related to the methods of enriching a learning base (steps A-F and A'-C') that do not explicitly involve the training and application of a deep learning device to determine attributes from images for the purpose of the learning base creation, but rather focus on the creation of segmented models and matching images, could be anticipated by WO 2016/066651. Similarly, any claim that solely covers acquiring and comparing images to models for deformation without specifying the deep learning component for attribute determination for that purpose might be anticipated.

It's important to note that the patent text for US10755409 explicitly states that WO 2016/066651 "does however require an appointment with the orthodontist in order to create the initial reference model. This appointment constitutes a brake to prevention." This highlights a problem that US10755409 aims to solve, suggesting that aspects of the new patent providing a solution to this problem (e.g., by enabling remote monitoring and feedback via deep learning analysis without requiring a new scan) would be novel over WO 2016/066651.

For a precise assessment of anticipation under 35 U.S.C. § 102, a detailed claim-by-claim analysis against the full text of both prior art documents would be necessary. This summary focuses on the explicit connections and descriptions provided within US10755409 itself.