Source: IPWatchdog

The U.S. Court of Appeals for the Federal Circuit affirmed a district court ruling in Dental Monitoring SAS v. Align Technology, Inc., holding several patent claims covering deep learning–based dental image analysis ineligible under 35 U.S.C. § 101. Dental Monitoring owns U.S. Patents 11,049,248 and 10,755,409, which the opinion describes as claiming methods for assessing an orthodontic aligner and for acquiring and analyzing dental arch images using a “deep learning device.” The underlying lawsuit was filed in November 2022 in the U.S. District Court for the Northern District of California before Judge William Alsup; the district court framed a July 2023 “patent showdown” and resolved cross-motions on representative claims.

Applying the Supreme Court’s Alice two-step test, the Federal Circuit, in an opinion by Judge Lourie, concluded at step one that the challenged claims are directed to abstract ideas—collecting and analyzing image information and generating guidance messages—and relied on Electric Power Group to place them in a familiar class of ineligible claims. At step two the court found no inventive concept: the claims used generic hardware and selectable, widely available neural networks, training on a dataset of more than 1,000 images was deemed “incident to the very nature of machine learning,” and prior CAFC precedent (Recentive Analytics, Broadband iTV, BSG Tech) supported that applying generic machine learning to a field of use does not confer eligibility. The court affirmed summary judgment that claims 1 and 14 of the ’248 patent and claims 1, 7, and 12 of the ’409 patent are ineligible under Section 101 and therefore invalid, and it did not address Align’s alternative Section 112 argument.