Abstract: An adjunct configured for use with an end effector of a surgical stapler includes a tissue-effecting portion comprising a first material, and at least one movable attachment feature coupled to the tissue-effecting portion and comprising a second material different from the first material. The at least one movable attachment feature is configured to releasably attach the tissue-effecting portion to a stapling surface of the end effector. The tissue-effecting portion is configured to contact tissue clamped by the end effector during closure thereof. The tissue-effecting portion is further configured to be pierced and captured by staples ejected from the end effector into the clamped tissue and thereby reinforce the engagement between the ejected staples and the clamped tissue.

Abstract: Systems and techniques that facilitate automated localization of large vessel occlusions are provided. In various embodiments, an input component can receive computed tomography angiogram (CTA) images of a patient's brain. In various embodiments, a localization component can determine, via a machine learning algorithm, a location of a large vessel occlusion (LVO) in the patient's brain based on the CTA images. In various instances, the location of the LVO can comprise a laterality and an occlusion site. In various aspects, the laterality can indicate a right side or a left side of the patient's brain, and the occlusion site can indicate an internal carotid artery (ICA), an M1 segment of a middle cerebral artery (MCA) or an M2 segment of an MCA. In various cases, a visualization component can generate and display to a user a three-dimensional maximum intensity projection (MIP) reconstruction of the patient's brain based on the CTA images to facilitate visual verification of the LVO by the user.

Abstract: Systems and techniques that facilitate automated localization of large vessel occlusions are provided. In various embodiments, an input component can receive computed tomography angiogram (CTA) images of a patient's brain. In various embodiments, a localization component can determine, via a machine learning algorithm, a location of a large vessel occlusion (LVO) in the patient's brain based on the CTA images. In various instances, the location of the LVO can comprise a laterality and an occlusion site. In various aspects, the laterality can indicate a right side or a left side of the patient's brain, and the occlusion site can indicate an internal carotid artery (ICA), an M1 segment of a middle cerebral artery (MCA) or an M2 segment of an MCA. In various cases, a visualization component can generate and display to a user a three-dimensional maximum intensity projection (MIP) reconstruction of the patient's brain based on the CTA images to facilitate visual verification of the LVO by the user.