AI Medical Compendium Topic

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Imaging, Three-Dimensional

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Machine learning-based 3D segmentation of mitochondria in polarized epithelial cells.

Mitochondrion
Mitochondria are dynamic organelles that alter their morphological characteristics in response to functional needs. Therefore, mitochondrial morphology is an important indicator of mitochondrial function and cellular health. Reliable segmentation of ...

Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) a...

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

International journal of computer assisted radiology and surgery
PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol...

Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.

Pediatric cardiology
Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediatric heart transplant that may increase overall utilization of available grafts. TCV requires manual ...

Hybrid-supervised deep learning for domain transfer 3D protoacoustic image reconstruction.

Physics in medicine and biology
. Protoacoustic imaging showed great promise in providing real-time 3D dose verification of proton therapy. However, the limited acquisition angle in protoacoustic imaging induces severe artifacts, which impairs its accuracy for dose verification. In...

3D auto-segmentation of biliary structure of living liver donors using magnetic resonance cholangiopancreatography for enhanced preoperative planning.

International journal of surgery (London, England)
BACKGROUND: This study aimed to develop an automated segmentation system for biliary structures using a deep learning model, based on data from magnetic resonance cholangiopancreatography (MRCP).

AI-assisted automatic MRI-based tongue volume evaluation in motor neuron disease (MND).

International journal of computer assisted radiology and surgery
PURPOSE: Motor neuron disease (MND) causes damage to the upper and lower motor neurons including the motor cranial nerves, the latter resulting in bulbar involvement with atrophy of the tongue muscle. To measure tongue atrophy, an operator independen...

Convolutional neural network for identifying common bile duct stones based on magnetic resonance cholangiopancreatography.

Clinical radiology
AIMS: To develop an auto-categorization system based on machine learning for three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) to detect choledocholithiasis from healthy and symptomatic individuals.

Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI.

International journal of computer assisted radiology and surgery
PURPOSE: Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions. The current workflow requires manual needle localization on 3D MRI, which is time-consuming and cumbersome. ...

Constantly optimized mean teacher for semi-supervised 3D MRI image segmentation.

Medical & biological engineering & computing
The mean teacher model and its variants, as important methods in semi-supervised learning, have demonstrated promising performance in magnetic resonance imaging (MRI) data segmentation. However, the superior performance of teacher model through expon...