Abstract: A system for adding an external function to a webpage includes: one or more processors; and memory communicably connected to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to: receive code associated with the webpage from a remote server; identify a plurality of images in the code; filter the plurality of images to identify a first type of image different from other images of the plurality of images; and append the external function to the first type of image to display a modified webpage including the external function on a display device of a first user.

Abstract: A system for adding an external function to a webpage includes: one or more processors; and memory communicably connected to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to: receive code associated with the webpage from a remote server; identify a plurality of images in the code; filter the plurality of images to identify a first type of image different from other images of the plurality of images; and append the external function to the first type of image to display a modified webpage including the external function on a display device of a first user.

Abstract: A system for adding an external function to a webpage includes: one or more processors; and memory communicably connected to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to: receive code associated with the webpage from a remote server; identify a plurality of images in the code; filter the plurality of images to identify a first type of image different from other images of the plurality of images; and append the external function to the first type of image to display a modified webpage including the external function on a display device of a first user.

Abstract: Disclosed is the automated rapid advancement of a guide wire through a guide catheter using x-ray markers. The procedure involves providing a guide wire with a marker at or adjacent its tip, providing a guide catheter with a marker at or adjacent its distal terminus, rapidly advancing the guide wire through the guide catheter from its proximal end to its distal end under the control of an automated apparatus, and terminating the automated rapid advancement when the guide wire tip marker becomes adjacent to the guide catheter distal end marker. Fluoroscopic images may be taken of the of the guide wire as it rapidly advances through the guide catheter and image processing software used to determine when to terminate the rapid advancement. This software may use either the position or the velocity of the guide wire to make this determination.

Abstract: This disclosure involves the use of X-ray markers that appear in fluoroscopic images and are detected by image processing software to partially or fully automate or assist in the performance of one or more of the steps of a percutaneous interventional procedure typically involving a catheter device.

Abstract: Disclosed is the automated rapid advancement of a guide wire through a guide catheter using x-ray markers. The procedure involves providing a guide wire with a marker at or adjacent its tip, providing a guide catheter with a marker at or adjacent its distal terminus, rapidly advancing the guide wire through the guide catheter from its proximal end to its distal end under the control of an automated apparatus, and terminating the automated rapid advancement when the guide wire tip marker becomes adjacent to the guide catheter distal end marker. Fluoroscopic images may be taken of the of the guide wire as it rapidly advances through the guide catheter and image processing software used to determine when to terminate the rapid advancement. This software may use either the position or the velocity of the guide wire to make this determination.

Abstract: The present disclosure involves a process for guiding the distal end of a guide wire or working catheter as it emerges from the distal end of a guide catheter into a blood vessel. The distal end of the guide wire or working catheter is provided with an X-ray marker, a determination is made that this distal end has emerged from the distal end of the guide catheter and a fluoroscopic image of the distal end of a guide wire or working catheter is taken. This image is correlated with the length of guide wire or working catheter inserted into the guide catheter. After further advancement of the guide wire or working catheter, another fluoroscopic image of the distal end of a guide wire or working catheter is taken and this image is correlated with the length of guide wire or working catheter which has been inserted into the guide catheter.

Abstract: Authentication of an unknown party in a secure computer communication may be performed even without consulting a public whitelist of trusted parties. A digital certificate from an unknown party not authenticated by a trusted certificate authority may be locally processed to determine if the digital certificate is a trusted, non-trusted, or unknown digital certificate. For example, a model may be created by training a support vector machine to classify a digital certificate. The model may be provided to a computer involved in secure computer communication. The computer may receive an incoming digital certificate, extract fields from the incoming digital certificate, and take a hash of the extracted fields perform input data that may be employed by the model to determine if the incoming digital certificate is a trusted, non-trusted, or unknown digital certificate.

Abstract: Authentication of an unknown party in a secure computer communication may be performed even without consulting a public whitelist of trusted parties. A digital certificate from an unknown party not authenticated by a trusted certificate authority may be locally processed to determine if the digital certificate is a trusted, non-trusted, or unknown digital certificate. For example, a model may be created by training a support vector machine to classify a digital certificate. The model may be provided to a computer involved in secure computer communication. The computer may receive an incoming digital certificate, extract fields from the incoming digital certificate, and take a hash of the extracted fields perform input data that may be employed by the model to determine if the incoming digital certificate is a trusted, non-trusted, or unknown digital certificate.