paper-with-me

홈 › Papers

Efficient and high accuracy 3-D OCT angiography motion correction in pathology

2020-10-14 · Stefan B. Ploner, Martin F. Kraus, Eric M. Moult, Lennart Husvogt, Julia Schottenhamml, A. Yasin Alibhai, Nadia K. Waheed, Jay S. Duker, James G. Fujimoto, Andreas K. Maier

We propose a novel method for non-rigid 3-D motion correction of orthogonally raster-scanned optical coherence tomography angiography volumes. This is the first approach that aligns predominantly axial structural features like retinal layers and transverse angiographic vascular features in a joint optimization. Combined with the use of orthogonal scans and favorization of kinematically more plausible displacements, the approach allows subpixel alignment and micrometer-scale distortion correction in all 3 dimensions. As no specific structures or layers are segmented, the approach is by design robust to pathologic changes. It is furthermore designed for highly parallel implementation and brief runtime, allowing its integration in clinical routine even for high density or wide-field scans. We evaluated the algorithm with metrics related to clinically relevant features in a large-scale quantitative evaluation based on 204 volumetric scans of 17 subjects including both a wide range of pathologies and healthy controls. Using this method, we achieve state-of-the-art axial performance and show significant advances in both transverse co-alignment and distortion correction, especially in the pathologic subgroup.

📄 PDF Abstract BibTeX arXiv:2010.06931

Code (0)

등록된 구현이 없습니다.

Tasks

distortion correction

Methods 이 논문이 사용한 방법론

Axial Attention 설명 없음

Similar Papers 제목 키워드 기반

A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT

2022-09-15 · Stefan Ploner, Siyu Chen, Jungeun Won, Lennart Husvogt 외

Optical coherence tomography (OCT) is a micrometer-scale, volumetric imaging modality that has become a clinical standard in ophthalmology. OCT instruments image by raster-scanning a focused light spot across the retina,…

parameter estimationSuper-Resolution

AngioMoCo: Learning-based Motion Correction in Cerebral Digital Subtraction Angiography

2023-10-09 · Ruisheng Su, Matthijs van der Sluijs, Sandra Cornelissen, Wim van Zwam 외

Cerebral X-ray digital subtraction angiography (DSA) is the standard imaging technique for visualizing blood flow and guiding endovascular treatments. The quality of DSA is often negatively impacted by body motion during…

Diagnostic

Blind deblurring for microscopic pathology images using deep learning networks

2020-11-24 · Cheng Jiang, Jun Liao, Pei Dong, Zhaoxuan Ma 외

Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency. However, defocus and motion blur can ob…

DeblurringDecoderDeep Learning

Motion Compensated Whole-Heart Coronary Magnetic Resonance Angiography using Focused Navigation (fNAV)

2020-10-27

Background: RSN whole-heart CMRA is a technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory…

Image Registration

Reconstruction of Undersampled 3D Non-Cartesian Image-Based Navigators for Coronary MRA Using an Unrolled Deep Learning Model

2019-10-24 · Mario O. Malavé, Corey A. Baron, Srivathsan P. Koundinyan, Christopher M. Sandino 외

Purpose: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using an unrolled deep learning (DL) model for non-rigid motion correction in coronary magnetic resonance angiography (CMRA). M…

CPUGPU