Method and system for semantic segmentation in laparoscopic and endoscopic 2d/2.5d image data
Номер патента: EP3289562A1
Опубликовано: 07-03-2018
Автор(ы): Ali Kamen, Stefan Kluckner, Terrence Chen
Принадлежит: SIEMENS AG
Опубликовано: 07-03-2018
Автор(ы): Ali Kamen, Stefan Kluckner, Terrence Chen
Принадлежит: SIEMENS AG
Реферат: A method and system for semantic segmentation laparoscopic and endoscopic 2D/2.5D image data is disclosed. Statistical image features that integrate a 2D image channel and a 2.5D depth channel of a 2D/2.5 laparoscopic or endoscopic image are extracted for each pixel in the image. Semantic segmentation of the laparoscopic or endoscopic image is then performed using a trained classifier to classify each pixel in the image with respect to a semantic object class of a target organ based on the extracted statistical image features. Segmented image masks resulting from the semantic segmentation of multiple frames of a laparoscopic or endoscopic image sequence can be used to guide organ specific 3D stitching of the frames to generate a 3D model of the target organ.
Method and system for semantic segmentation in laparoscopic and endoscopic 2d/2.5d image data
Номер патента: US20180108138A1. Автор: Terrence Chen,Ali Kamen,Stefan Kluckner. Владелец: SIEMENS AG. Дата публикации: 2018-04-19.