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Found 15 papers, 7 papers with code
An Endoscopic Chisel: Intraoperative Imaging Carves 3D Anatomical Models
Purpose: Preoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to complement endoscopy imaging.
A Quantitative Evaluation of Dense 3D Reconstruction of Sinus Anatomy from Monocular Endoscopic Video
In this work, we perform a quantitative analysis of a self-supervised approach for sinus reconstruction using endoscopic sequences paired with optical tracking and high-resolution computed tomography acquired from nine ex-vivo specimens.
SAGE: SLAM with Appearance and Geometry Prior for Endoscopy
In endoscopy, many applications (e. g., surgical navigation) would benefit from a real-time method that can simultaneously track the endoscope and reconstruct the dense 3D geometry of the observed anatomy from a monocular endoscopic video.
Neighborhood Normalization for Robust Geometric Feature Learning
Extracting geometric features from 3D models is a common first step in applications such as 3D registration, tracking, and scene flow estimation.
Learning Representations of Endoscopic Videos to Detect Tool Presence Without Supervision
We use three different methods to manipulate these latent representations in order to predict tool presence in each frame.
Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment
Reconstructing accurate 3D surface models of sinus anatomy directly from an endoscopic video is a promising avenue for cross-sectional and longitudinal analysis to better understand the relationship between sinus anatomy and surgical outcomes.
Extremely Dense Point Correspondences using a Learned Feature Descriptor
In direct comparison to recent local and dense descriptors on an in-house sinus endoscopy dataset, we demonstrate that our proposed dense descriptor can generalize to unseen patients and scopes, thereby largely improving the performance of Structure from Motion (SfM) in terms of model density and completeness.
Self-supervised Dense 3D Reconstruction from Monocular Endoscopic Video
We present a self-supervised learning-based pipeline for dense 3D reconstruction from full-length monocular endoscopic videos without a priori modeling of anatomy or shading.
Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning Methods
We present a self-supervised approach to training convolutional neural networks for dense depth estimation from monocular endoscopy data without a priori modeling of anatomy or shading.
Towards automatic initialization of registration algorithms using simulated endoscopy images
Several registration algorithms have been developed, many of which achieve high accuracy.
Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy
We present a self-supervised approach to training convolutional neural networks for dense depth estimation from monocular endoscopy data without a priori modeling of anatomy or shading.
Endoscopic navigation in the absence of CT imaging
Clinical examinations that involve endoscopic exploration of the nasal cavity and sinuses often do not have a reference image to provide structural context to the clinician.
Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles
Recent advances in cancer research largely rely on new developments in microscopic or molecular profiling techniques offering high level of detail with respect to either spatial or molecular features, but usually not both.
Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm
Functional endoscopic sinus surgery (FESS) is a surgical procedure used to treat acute cases of sinusitis and other sinus diseases.
Automated Objective Surgical Skill Assessment in the Operating Room Using Unstructured Tool Motion
Previous work on surgical skill assessment using intraoperative tool motion in the operating room (OR) has focused on highly-structured surgical tasks such as cholecystectomy.
