AIMC Topic: Imaging, Three-Dimensional

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Pushing the limits of low-cost ultra-low-field MRI by dual-acquisition deep learning 3D superresolution.

Magnetic resonance in medicine
PURPOSE: Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power, shielding-free, and portable clinical applications at a fraction of the cost. However, its performance remains limited by poor image quality. Here, a compu...

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.

Development (Cambridge, England)
Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms a...

Evaluating the accuracy of automated cephalometric analysis based on artificial intelligence.

BMC oral health
BACKGROUND: The purpose of this study was to evaluate the accuracy of automatic cephalometric landmark localization and measurements using cephalometric analysis via artificial intelligence (AI) compared with computer-assisted manual analysis.

Transformer guided progressive fusion network for 3D pancreas and pancreatic mass segmentation.

Medical image analysis
Pancreatic masses are diverse in type, often making their clinical management challenging. This study aims to address the task of various types of pancreatic mass segmentation and detection while accurately segmenting the pancreas. Although convoluti...

Synthesis of large scale 3D microscopic images of 3D cell cultures for training and benchmarking.

PloS one
The analysis of 3D microscopic cell culture images plays a vital role in the development of new therapeutics. While 3D cell cultures offer a greater similarity to the human organism than adherent cell cultures, they introduce new challenges for autom...

Memory efficient model based deep learning reconstructions for high spatial resolution 3D non-cartesian acquisitions.

Physics in medicine and biology
. Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Cartesian MRI due to GPU memory demand because the entire volume is needed for data-consistency steps embedded in the model. This requirement makes holdi...

Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery.

European urology
Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instrume...

2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System.

Sensors (Basel, Switzerland)
Chronic wounds, are a worldwide health problem affecting populations and economies as a whole. With the increase in age-related diseases, obesity, and diabetes, the costs of chronic wound healing will further increase. Wound assessment should be fast...

A feasibility study of enhanced prompt gamma imaging for range verification in proton therapy using deep learning.

Physics in medicine and biology
. Range uncertainty is a major concern affecting the delivery precision in proton therapy. The Compton camera (CC)-based prompt-gamma (PG) imaging is a promising technique to provide 3Drange verification. However, the conventional back-projected PG i...

Prediction of orthognathic surgery plan from 3D cephalometric analysis via deep learning.

BMC oral health
BACKGROUND: Preoperative planning of orthognathic surgery is indispensable for achieving ideal surgical outcome regarding the occlusion and jaws' position. However, orthognathic surgery planning is sophisticated and highly experience-dependent, which...