公开(公告)号：US20210113146A1

公开(公告)日：2021-04-22

申请号：US17076788

申请日：2020-10-21

Applicant: THE TRUSTEES OF DARTMOUTH COLLEGE

Inventor： Brian Pogue ,  Samuel Streeter ,  Benjamin Maloney ,  Keith Paulsen

IPC: A61B5/00 ,  G06N20/00 ,  G06T7/00 ,  A61B6/03 ,  A61B6/00

Abstract: A surgical specimen imaging system includes a micro-X-ray computed tomography (CT) unit for CT imaging of the specimen and a structured light imaging (SLI) unit for optical imaging at multiple wavelengths, multiple phase offsets, and multiple structured-light pattern periods including unstructured light. The system's image processing unit receives CT and optical images and is configured by firmware in memory to co-register the images and process the optical images to determine texture at multiple subimages of the optical images, determined textures forming a texture map. The texture map is processed by a machine-learning-based classifier to determine a tissue type map of the specimen, and the tissue type map is processed with the CT images to give a 3D tissue-type map. In embodiments, the firmware extracts optical properties including scattering and absorption at multiple wavelengths and the classifier also uses these properties in generating the tissue type map.

公开(公告)号：US11633145B2

公开(公告)日：2023-04-25

申请号：US17076788

申请日：2020-10-21

Applicant: THE TRUSTEES OF DARTMOUTH COLLEGE

Inventor： Brian Pogue ,  Samuel Streeter ,  Benjamin Maloney ,  Keith Paulsen

IPC: A61B5/00 ,  G06N20/00 ,  G06T7/00 ,  A61B6/00 ,  A61B6/03

Abstract: A surgical specimen imaging system includes a micro-X-ray computed tomography (CT) unit for CT imaging of the specimen and a structured light imaging (SLI) unit for optical imaging at multiple wavelengths, multiple phase offsets, and multiple structured-light pattern periods including unstructured light. The system's image processing unit receives CT and optical images and is configured by firmware in memory to co-register the images and process the optical images to determine texture at multiple subimages of the optical images, determined textures forming a texture map. The texture map is processed by a machine-learning-based classifier to determine a tissue type map of the specimen, and the tissue type map is processed with the CT images to give a 3D tissue-type map. In embodiments, the firmware extracts optical properties including scattering and absorption at multiple wavelengths and the classifier also uses these properties in generating the tissue type map.