DeepAI AI Chat
Log In Sign Up

3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training

06/10/2021
by   Yaqub Jonmohamadi, et al.
The University of Adelaide
0

Minimally invasive surgery (MIS) has many documented advantages, but the surgeon's limited visual contact with the scene can be problematic. Hence, systems that can help surgeons navigate, such as a method that can produce a 3D semantic map, can compensate for the limitation above. In theory, we can borrow 3D semantic mapping techniques developed for robotics, but this requires finding solutions to the following challenges in MIS: 1) semantic segmentation, 2) depth estimation, and 3) pose estimation. In this paper, we propose the first 3D semantic mapping system from knee arthroscopy that solves the three challenges above. Using out-of-distribution non-human datasets, where pose could be labeled, we jointly train depth+pose estimators using selfsupervised and supervised losses. Using an in-distribution human knee dataset, we train a fully-supervised semantic segmentation system to label arthroscopic image pixels into femur, ACL, and meniscus. Taking testing images from human knees, we combine the results from these two systems to automatically create 3D semantic maps of the human knee. The result of this work opens the pathway to the generation of intraoperative 3D semantic mapping, registration with pre-operative data, and robotic-assisted arthroscopy

READ FULL TEXT
07/05/2020

Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy

Intra-operative automatic semantic segmentation of knee joint structures...
09/16/2021

Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM

Recent Semantic SLAM methods combine classical geometry-based estimation...
10/15/2019

Explainable Semantic Mapping for First Responders

One of the key challenges in the semantic mapping problem in postdisaste...
09/04/2015

Semantic Amodal Segmentation

Common visual recognition tasks such as classification, object detection...
09/30/2016

A CNN Cascade for Landmark Guided Semantic Part Segmentation

This paper proposes a CNN cascade for semantic part segmentation guided ...
08/10/2017

Joint Multi-Person Pose Estimation and Semantic Part Segmentation

Human pose estimation and semantic part segmentation are two complementa...
03/15/2019

SceneCode: Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations

Systems which incrementally create 3D semantic maps from image sequences...