公开(公告)号：US20240324849A1

公开(公告)日：2024-10-03

申请号：US18614771

申请日：2024-03-25

申请人： FUJIFILM Corporation

发明人： Haruto CHIBA

IPC分类号： A61B1/00 ,  A61B1/05 ,  A61B1/267

CPC分类号： A61B1/00009 ,  A61B1/00045 ,  A61B1/05 ,  A61B1/2676

摘要： An information processing apparatus including at least one processor, wherein the processor is configured to: use at least one of a real image, which represents an interior wall of a tubular structure, or a first depth image, which represents a distance for each pixel from a viewpoint of the real image to the interior wall, and at least one of a virtual image, which represents, in a pseudo manner, the interior wall as viewed from a virtual viewpoint predetermined in a three-dimensional image, or a second depth image, which represents a distance for each pixel from the virtual viewpoint to the interior wall, to perform viewpoint difference estimation processing of estimating a viewpoint difference between the viewpoint of the real image and the virtual viewpoint; and use at least one of the first depth image or the second depth image in the viewpoint difference estimation processing.

公开(公告)号：US20240324848A1

公开(公告)日：2024-10-03

申请号：US18614770

申请日：2024-03-25

申请人： FUJIFILM Corporation

发明人： Haruto CHIBA

IPC分类号： A61B1/00 ,  A61B1/267

CPC分类号： A61B1/00009 ,  A61B1/00045 ,  A61B1/2676

摘要： An information processing apparatus including at least one processor, wherein the processor is configured to: acquire an input image including a real image, which represents an interior wall of a tubular structure, or a virtual image, which represents, in a pseudo manner, the interior wall as viewed from a virtual viewpoint; use a transformation model to transform the input image into a transformed image having an image style that is not included in the input image; acquire an input depth image, which represents a distance for each pixel from a viewpoint of the input image to the interior wall, and a transformed depth image, which represents a distance for each pixel from a viewpoint of the transformed image to the interior wall; and train the transformation model by using a loss function including a degree of similarity between the input depth image and the transformed depth image.