AIMC Topic: Imaging, Three-Dimensional

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Learning Pose Controllable Human Reconstruction With Dynamic Implicit Fields From a Single Image.

IEEE transactions on visualization and computer graphics Jan 6, 2025
Recovering a user-special and controllable human model from a single RGB image is a nontrivial challenge. Existing methods usually generate static results with an image consistent subject's pose. Our work aspires to achieve pose-controllable human re...
Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted Computer Graphics Humans Machine Learning
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Feasibility of reconstructingpatient 3D dose distributions from 2D EPID image data using convolutional neural networks.

Physics in medicine and biology Jan 6, 2025
. The primary purpose of this work is to demonstrate the feasibility of a deep convolutional neural network (dCNN) based algorithm that uses two-dimensional (2D) electronic portal imaging device (EPID) images and CT images as input to reconstruct 3D ...
Humans Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted Radiotherapy Dosage Feasibility Studies Monte Carlo Method Radiotherapy Planning, Computer-Assisted Electrical Equipment and Supplies Radiation Dosage
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Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients.

Orthodontics & craniofacial research Jan 4, 2025
OBJECTIVE: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analysed with ...
Mandibular Condyle Female Young Adult Adult Male Humans Imaging, Three-Dimensional Bone Remodeling Deep Learning Retrospective Studies Orthognathic Surgical Procedures Cone-Beam Computed Tomography Malocclusion, Angle Class III
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Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.

Medical & biological engineering & computing Jan 4, 2025
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employ...
Heart Defects, Congenital Imaging, Three-Dimensional Image Processing, Computer-Assisted Heart Humans Deep Learning
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Deep learning-based pelvimetry in pelvic MRI volumes for pre-operative difficulty assessment of total mesorectal excision.

Surgical endoscopy Jan 3, 2025
BACKGROUND: Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, manual measurement of these dimensions (pelvimetry) is labor intensive and thus, anatomic criteria are...
Anatomic Landmarks Rectum Rectal Neoplasms Preoperative Care Pelvimetry Imaging, Three-Dimensional Female Magnetic Resonance Imaging Male Aged Pelvic Bones Middle Aged Humans Deep Learning
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Assessment of choroidal vessels in healthy eyes using 3-dimensional vascular maps and a semi-automated deep learning approach.

Scientific reports Jan 3, 2025
To assess the choroidal vessels in healthy eyes using a novel three-dimensional (3D) deep learning approach. In this cross-sectional retrospective study, swept-source OCT 6 × 6 mm scans on Plex Elite 9000 device were obtained. Automated segmentation ...
Humans Retrospective Studies Female Aged Young Adult Imaging, Three-Dimensional Choroid Tomography, Optical Coherence Middle Aged Adult Healthy Volunteers Deep Learning Cross-Sectional Studies Adolescent Male
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A deep learning-based multi-view approach to automatic 3D landmarking and deformity assessment of lower limb.

Scientific reports Jan 2, 2025
Anatomical Landmark detection in CT-Scan images is widely used in the identification of skeletal disorders. However, the traditional process of manually detecting anatomical landmarks, especially in three dimensions, is both time-consuming and prone ...
Adult Male Deep Learning Neural Networks, Computer Tomography, X-Ray Computed Female Imaging, Three-Dimensional Lower Extremity Anatomic Landmarks Humans
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AutoSamp: Autoencoding k-Space Sampling via Variational Information Maximization for 3D MRI.

IEEE transactions on medical imaging Jan 2, 2025
Accelerated MRI protocols routinely involve a predefined sampling pattern that undersamples the k-space. Finding an optimal pattern can enhance the reconstruction quality, however this optimization is a challenging task. To address this challenge, we...
Fourier Analysis Humans Algorithms Brain Deep Learning Imaging, Three-Dimensional Magnetic Resonance Imaging
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CADS: A Self-Supervised Learner via Cross-Modal Alignment and Deep Self-Distillation for CT Volume Segmentation.

IEEE transactions on medical imaging Jan 2, 2025
Self-supervised learning (SSL) has long had great success in advancing the field of annotation-efficient learning. However, when applied to CT volume segmentation, most SSL methods suffer from two limitations, including rarely using the information a...
Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Humans Algorithms Supervised Machine Learning
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Detection of focal cortical dysplasia: Development and multicentric evaluation of artificial intelligence models.

Epilepsia Dec 31, 2024
OBJECTIVE: Focal cortical dysplasia (FCD) is a common cause of drug-resistant focal epilepsy but can be challenging to detect visually on magnetic resonance imaging. Three artificial intelligence models for automated FCD detection are publicly availa...
Male Focal Cortical Dysplasia Female Adolescent Young Adult Humans Child Imaging, Three-Dimensional Adult Artificial Intelligence Magnetic Resonance Imaging Retrospective Studies Malformations of Cortical Development
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