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

• URL: http://arxiv.org/abs/2209.07232v1
• Date: Thu, 15 Sep 2022 11:48:53 GMT
• Title: A Spatiotemporal Model for Precise and Efficient Fully-automatic 3D Motion Correction in OCT
• Authors: Stefan Ploner, Siyu Chen, Jungeun Won, Lennart Husvogt, Katharina Breininger, Julia Schottenhamml, James Fujimoto, Andreas Maier
• Abstract summary: OCT instruments image by-scanning a focused light spot across the retina, acquiring cross-sectional images to generate data. Patient eye motion during the acquisition poses unique challenges: non-rigid, distorted distortions occur, leading to gaps in data. We present a new distortion model and a corresponding fully-automatic, reference-free optimization strategy for computational robustness.
• Score: 10.550562752812894
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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, acquiring sequential cross-sectional images to generate volumetric data. Patient eye motion during the acquisition poses unique challenges: Non-rigid, discontinuous distortions can occur, leading to gaps in data and distorted topographic measurements. We present a new distortion model and a corresponding fully-automatic, reference-free optimization strategy for computational motion correction in orthogonally raster-scanned, retinal OCT volumes. Using a novel, domain-specific spatiotemporal parametrization of forward-warping displacements, eye motion can be corrected continuously for the first time. Parameter estimation with temporal regularization improves robustness and accuracy over previous spatial approaches. We correct each A-scan individually in 3D in a single mapping, including repeated acquisitions used in OCT angiography protocols. Specialized 3D forward image warping reduces median runtime to < 9 s, fast enough for clinical use. We present a quantitative evaluation on 18 subjects with ocular pathology and demonstrate accurate correction during microsaccades. Transverse correction is limited only by ocular tremor, whereas submicron repeatability is achieved axially (0.51 um median of medians), representing a dramatic improvement over previous work. This allows assessing longitudinal changes in focal retinal pathologies as a marker of disease progression or treatment response, and promises to enable multiple new capabilities such as supersampled/super-resolution volume reconstruction and analysis of pathological eye motion occuring in neurological diseases.

Related papers

• A Spatiotemporal Illumination Model for 3D Image Fusion in Optical Coherence Tomography [2.8532140618225337]
  Optical-scanning standard tomography ( OCT) is a non-invasive, micrometer-scale imaging modality in ophthalmology. We present a novel parametrization that exploits continuity in sequentially-scanned volume data. In 68 volumes from eyes with pathology showed reduction of illumination artifacts in 88% of the data, and only 6% moderate illumination artifacts.
  arXiv  Detail & Related papers  (2024-02-19T13:08:31Z)
• INeAT: Iterative Neural Adaptive Tomography [34.84974955073465]
  Iterative Neural Adaptive Tomography (INeAT) incorporates posture optimization to counteract the influence of posture perturbations in data. We demonstrate that INeAT achieves artifact-suppressed and resolution-enhanced reconstruction in scenarios with significant pose disturbances.
  arXiv  Detail & Related papers  (2023-11-03T01:00:36Z)
• AiAReSeg: Catheter Detection and Segmentation in Interventional Ultrasound using Transformers [75.20925220246689]
  endovascular surgeries are performed using the golden standard of Fluoroscopy, which uses ionising radiation to visualise catheters and vasculature. This work proposes a solution using an adaptation of a state-of-the-art machine learning transformer architecture to detect and segment catheters in axial interventional Ultrasound image sequences.
  arXiv  Detail & Related papers  (2023-09-25T19:34:12Z)
• Deep learning network to correct axial and coronal eye motion in 3D OCT retinal imaging [65.47834983591957]
  We propose deep learning based neural networks to correct axial and coronal motion artifacts in OCT based on a single scan. The experimental result shows that the proposed method can effectively correct motion artifacts and achieve smaller error than other methods.
  arXiv  Detail & Related papers  (2023-05-27T03:55:19Z)
• Neural Computed Tomography [1.7188280334580197]
  Motion during acquisition of a set of projections can lead to significant motion artifacts in computed tomography reconstructions. We propose a novel reconstruction framework, NeuralCT, to generate time-resolved images free from motion artifacts.
  arXiv  Detail & Related papers  (2022-01-17T18:50:58Z)
• Explainable multiple abnormality classification of chest CT volumes with AxialNet and HiResCAM [89.2175350956813]
  We introduce the challenging new task of explainable multiple abnormality classification in volumetric medical images. We propose a multiple instance learning convolutional neural network, AxialNet, that allows identification of top slices for each abnormality. We then aim to improve the model's learning through a novel mask loss that leverages HiResCAM and 3D allowed regions.
  arXiv  Detail & Related papers  (2021-11-24T01:14:33Z)
• Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices [48.85784310158493]
  We propose a Modified Pseudo-3D Feature Pyramid Network (MP3D FPN) to efficiently extract 3D context enhanced 2D features for universal lesion detection in CT slices. With the novel pre-training method, the proposed MP3D FPN achieves state-of-the-art detection performance on the DeepLesion dataset. The proposed 3D pre-trained weights can potentially be used to boost the performance of other 3D medical image analysis tasks.
  arXiv  Detail & Related papers  (2020-12-16T07:11:16Z)
• Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern [49.240017254888336]
  Photoacoustic tomography (PAT) is a novel imaging technique that can resolve both morphological and functional tissue properties. A current drawback is the limited field-of-view provided by the conventionally applied 2D probes. We present a novel approach to 3D reconstruction of PAT data that does not require an external tracking system.
  arXiv  Detail & Related papers  (2020-11-10T09:27:56Z)
• Efficient and high accuracy 3-D OCT angiography motion correction in pathology [6.875092432376952]
  We propose a novel method for non-rigid 3-D motion correction of optical coherence tomography angiography volumes. This is the first approach that aligns predominantly axial structural features in a joint optimization. We show significant advances in both transverse co-alignment and distortion correction, especially in the pathologic subgroup.
  arXiv  Detail & Related papers  (2020-10-14T10:20:17Z)
• Probabilistic 3D surface reconstruction from sparse MRI information [58.14653650521129]
  We present a novel probabilistic deep learning approach for concurrent 3D surface reconstruction from sparse 2D MR image data and aleatoric uncertainty prediction. Our method is capable of reconstructing large surface meshes from three quasi-orthogonal MR imaging slices from limited training sets.
  arXiv  Detail & Related papers  (2020-10-05T14:18:52Z)
• Robust Self-Supervised Learning of Deterministic Errors in Single-Plane (Monoplanar) and Dual-Plane (Biplanar) X-ray Fluoroscopy [2.7528170226206443]
  Fluoroscopic imaging that captures X-ray images at video framerates is advantageous for guiding catheter insertions by vascular surgeons and interventional radiologists. Visualizing the dynamical movements non-invasively allows complex surgical procedures to be performed with less trauma to the patient. This paper presents a robust self-calibration algorithm suitable for single-plane and dual-plane fluoroscopy.
  arXiv  Detail & Related papers  (2020-01-03T01:56:21Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.