Abstract: Systems, methods, and instrumentalities are disclosed for computer vision-based surgical workflow recognition using natural language processing (NLP) techniques. Surgical video of surgical procedures may be processed and analyzed, for example, to achieve workflow recognition. Surgical phases may be determined based on the surgical video and segmented to generate an annotated video representation. The annotated video representation of the surgical video may provide information associated with the surgical procedure. For example, the annotated video representation may provide information on surgical phases, surgical events, surgical tool usage, and/or the like.

Abstract: A Cross-Enhancement Causal Transformer or simply a Cross-Enhancement Transformer (C-ECT) is described as a modification of previous transformer architectures that is suitable for online surgical phase recognition. Additionally, a Cross-Attention Feature Fusion (CAFF) is described that better integrates the global and location information in the C-ECT. This can achieve better performance on the Cholec80 dataset than the current state-of-the-art methods in accuracy and precision, recall, and in the Jaccard score. Other aspects are also described and claimed.

Abstract: A machine learning model has two stages. In a first stage, features from one or more frames of a surgical video are extracted, wherein the features include presence of a surgical instrument and type of the surgical instrument. A second stage analyzes the surgical video based on the extracted features to recognize a video segment, wherein the recognized video segment includes a detected presence of the surgical instrument, and where the video segment is recognized by a multi-stage temporal convolution network (MS-TCN) or a vision transformer. Other aspects are also described and claimed.

Abstract: Systems, methods, and instrumentalities are disclosed for computer vision-based surgical workflow recognition using natural language processing (NLP) techniques. Surgical video of surgical procedures may be processed and analyzed, for example, to achieve workflow recognition. Surgical phases may be determined based on the surgical video and segmented to generate an annotated video representation. The annotated video representation of the surgical video may provide information associated with the surgical procedure. For example, the annotated video representation may provide information on surgical phases, surgical events, surgical tool usage, and/or the like.