This paper presents CoSummary, an adaptive video fast-forwarding technique for browsing surgical videos recorded by wearable cameras. Current wearable technologies allow us to record complex surgical skills, however, an efficient browsing technique for these videos is not well established. In order to assist browsing surgical videos, our study focuses on adaptively changing playback speeds through the learning and detecting collaborative scenes based on surgeon hand placement and gaze information. Our evaluation shows that the proposed method is able to highlight important collaborative scenes and skip less important scenes during surgical procedures. We have also performed a subjective study with surgeons in order to have professional feedback. The results confirmed the effectiveness of the proposed method in comparison to uniform video fast-forwarding.

This paper introduces a registration and projection method for directly projecting the tumor region for breast cancer surgery assistance based on the breast procedure of our collaborating doctor. We investigated the steps of the breast cancer procedure of our collaborating doctor and how it can be applied for tumor region projection. We propose a novel way of MRI acquisition so we may correlate the MRI coordinates to the patient in the real world. By calculating the transformation matrix from the MRI coordinates and the coordinates from the markers that is on the patient, we are able to register the acquired MRI data to the patient. Our registration and presentation method of the tumor region was then evaluated by medical doctors.

In this paper we propose an augmented reality system that superimposes MRI onto the patient model. We use a half-silvered mirror and a handheld device to superimpose the MRI onto the patient model. By tracking the coordinates of the patient model and the handheld device using optical markers, we are able to transform the images to the correlated position. Voxel data of the MRI are made so that the user is able to view the MRI from many different angles.

This paper proposes an interface that helps understanding the correspondence between the patient and medical images. In our proposed method, we have developed an interactive visualizer for tomographic images based on the relative position and orientation of the handheld device and the patient.