AIMC Topic: Imaging, Three-Dimensional

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Label refinement network from synthetic error augmentation for medical image segmentation.

Medical image analysis Sep 27, 2024
Deep convolutional neural networks for image segmentation do not learn the label structure explicitly and may produce segmentations with an incorrect structure, e.g., with disconnected cylindrical structures in the segmentation of tree-like structure...
Image Processing, Computer-Assisted Humans Radiography, Thoracic Neural Networks, Computer Computed Tomography Angiography Brain Algorithms Tomography, X-Ray Computed Imaging, Three-Dimensional
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Using 3D point cloud and graph-based neural networks to improve the estimation of pulmonary function tests from chest CT.

Computers in biology and medicine Sep 27, 2024
Pulmonary function tests (PFTs) are important clinical metrics to measure the severity of interstitial lung disease for systemic sclerosis patients. However, PFTs cannot always be performed by spirometry if there is a risk of disease transmission or ...
Respiratory Function Tests Middle Aged Lung Imaging, Three-Dimensional Female Adult Male Humans Neural Networks, Computer Tomography, X-Ray Computed
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Detection of breast cancer in digital breast tomosynthesis with vision transformers.

Scientific reports Sep 27, 2024
Digital Breast Tomosynthesis (DBT) has revolutionized more traditional breast imaging through its three-dimensional (3D) visualization capability that significantly enhances lesion discernibility, reduces tissue overlap, and improves diagnostic preci...
Imaging, Three-Dimensional Mammography Radiographic Image Interpretation, Computer-Assisted Breast Algorithms Female Breast Neoplasms Humans Neural Networks, Computer
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Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet.

Physics in medicine and biology Sep 27, 2024
To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined with 3D nnUNet for rapid and consistent autosegmentation of high-risk clinical target volume (HRCTV) and organ at risk (OAR) in high-dose-rate brachyther...
Female Uterine Cervical Neoplasms Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Organs at Risk Radiotherapy Dosage Humans Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Radiation Dosage Brachytherapy
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DELR-Net: a network for 3D multimodal medical image registration in more lightweight application scenarios.

Abdominal radiology (New York) Sep 26, 2024
PURPOSE: 3D multimodal medical image deformable registration plays a significant role in medical image analysis and diagnosis. However, due to the substantial differences between images of different modalities, registration is challenging and require...
Magnetic Resonance Imaging Tomography, X-Ray Computed Multimodal Imaging Deep Learning Image Interpretation, Computer-Assisted Humans Imaging, Three-Dimensional Neural Networks, Computer Brain
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Real-world application of a 3D deep learning model for detecting and localizing cerebral microbleeds.

Acta neurochirurgica Sep 26, 2024
BACKGROUND: Detection and localization of cerebral microbleeds (CMBs) is crucial for disease diagnosis and treatment planning. However, CMB detection is labor-intensive, time-consuming, and challenging owing to its visual similarity to mimics. This s...
Imaging, Three-Dimensional Magnetic Resonance Imaging Cerebral Hemorrhage Male Middle Aged Deep Learning Female Humans Aged
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Cross-site Validation of AI Segmentation and Harmonization in Breast MRI.

Journal of imaging informatics in medicine Sep 25, 2024
This work aims to perform a cross-site validation of automated segmentation for breast cancers in MRI and to compare the performance to radiologists. A three-dimensional (3D) U-Net was trained to segment cancers in dynamic contrast-enhanced axial MRI...
Humans Artificial Intelligence Imaging, Three-Dimensional Magnetic Resonance Imaging Breast Image Interpretation, Computer-Assisted Female Reproducibility of Results Breast Neoplasms
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Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction.

Neuroradiology Sep 24, 2024
PURPOSE: The time-intensive nature of acquiring 3D T1-weighted MRI and analyzing brain volumetry limits quantitative evaluation of brain atrophy. We explore the feasibility and reliability of deep learning-based accelerated MRI scans for brain volume...
Brain Retrospective Studies Female Humans Middle Aged Deep Learning Imaging, Three-Dimensional Reproducibility of Results Adult Male Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Organ Size Feasibility Studies
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No-reference stereoscopic image quality assessment based on binocular collaboration.

Neural networks : the official journal of the International Neural Network Society Sep 24, 2024
Stereoscopic images typically consist of left and right views along with depth information. Assessing the quality of stereoscopic/3D images (SIQA) is often more complex than that of 2D images due to scene disparities between the left and right views ...
Algorithms Databases, Factual Imaging, Three-Dimensional Image Processing, Computer-Assisted Vision, Binocular Humans Visual Cortex Neural Networks, Computer Depth Perception
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A flexible 2.5D medical image segmentation approach with in-slice and cross-slice attention.

Computers in biology and medicine Sep 23, 2024
Deep learning has become the de facto method for medical image segmentation, with 3D segmentation models excelling in capturing complex 3D structures and 2D models offering high computational efficiency. However, segmenting 2.5D images, characterized...
Magnetic Resonance Imaging Prostate Humans Brain Male Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted
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