Boston Scientific Scimed, Inc.

Longquan Chen

Niraj Prasad Rauniyar

Evan Gyllenhaal

Andrea Cahill

Aaron Silva

Robert J Riker

Mussie Teshome Demisse

Jeffrey A Meganck

Judith Fusman

Nathan S Fettinger

Steven Carlson

Thomas Zappia

Thomas Michael Zappia, Jr

Eric Lent

Phillip C Dingman

Leroy Jackson Longworth

Matthew J Strong

Matthew Protas

Systems and methods related to combing multiple images are disclosed. An example method of combining multiple images of a body structure includes capturing a first input image with a digital camera positioned at a first location at a first time point, representing the first image with a first plurality of pixels, capturing a second input image with the digital camera positioned at a second location at a second time point, representing the second image with a second plurality of pixels, generating a first feature distance map of the first input image, generating a second feature distance map of the second input image, calculating the positional change of the digital camera between the first time point and the second time point and utilizing the first feature distance map, the second feature distance map and the positional change of the digital camera to generate a three-dimensional surface approximation the body structure.

Method of multiple image reconstruction and registration

Systems and methods for modifying the luminance value of at least one image are discussed, e.g., including receiving a request to modify the luminance value of at least one image, determining a weighted frame luminance of the at least one image based on an imbalance factor, modifying the luminance value of the at least one image by changing at least one setting of the camera and/or the light source automatically or manually based on the determined weighted frame luminance, and causing to output to a graphical user interface a visualization of the at least one image with the modified luminance value.

Systems and methods for dynamic light control

Methods and devices are provided for determining anatomical distance and/or position measurements during an endoscopic procedure. Markings are placed either physically or superimposed on a distal end of an elongate tool, such that the markings are viewable in an imaging field of view of the endoscope. Anatomic distances may be determined by measurements performed with the tool. The size and/or position of anatomical structures or unknown objects may also be determined using the marked tool.

Measurement markings in distal tip imaging field of view

Systems and methods related to estimating the distance of a body structure from a medical device are disclosed. An example method includes illuminating the body structure with a light source of a medical device, capturing a first input image of the body structure with a digital camera positioned on the medical device, representing the first image with a first plurality of pixels, wherein the first plurality of pixels includes one or more pixels displaying a local intensity maxima, defining a first pixel group from the one or more pixels displaying a local intensity maxima, wherein the first pixel group corresponds to a plurality of surface points of the body structure and wherein the first pixel group further includes a first image intensity. The method further includes calculating a relative distance from the digital camera to a first surface point of the plurality of surface points.

Method of robust surface and depth estimation

Systems and methods related to combing multiple images are disclosed. An example method of combining multiple images obtained by an endoscope includes obtaining a first input image formed from a first plurality of pixels, wherein a first pixel of the plurality of pixels includes a first characteristic having a first value. The method also includes obtaining a second input image formed from a second plurality of pixels, wherein a second pixel of the second plurality of pixels includes a second characteristic having a second value. The method also includes subtracting the first value from the second value to generate a motion metric and generating a weighted metric map of the second input image using the motion metric.

Method of image enhancement for distraction deduction

Systems and methods for processing electronic images from a medical device comprise receiving an image frame from the medical device, and determining a first color channel and a second color channel in the image frame. A location of an electromagnetic beam halo may be identified by comparing the first color channel and second color channel. Edges of an electromagnetic beam may be determined based on the electromagnetic beam halo, and size metrics of the electromagnetic beam may be determined based on the edges of the electromagnetic beam. A visual indicator on the image frame may be displayed based on the size metrics of the electromagnetic beam.

Systems and methods for processing electronic medical images to determine object size

Systems and methods for processing electronic images from a medical device comprise receiving a first image frame and a second image frame from a medical device, and determining a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. Image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest, and the first image frame and/or second image frame may be provided for display to a user.

Systems and methods for processing electronic medical images to determine enhanced electronic medical images

A medical system includes a shaft having a proximal end and a distal end, an imaging device at the distal end of the shaft, and a controller, the controller receives image data comprising pixel data from the imaging device, the pixel data including a plurality of individual pixel values, converts the pixel data from a RGB format to a YCCformat, and forms adjusted pixel data by applying a gain to the pixel data, wherein the gain is based on a Y value, a Cvalue, and a Cvalue of the individual pixel values of the converted pixel data.

Growing community of inventors

Andover, MA, United States of America

Longquan Chen