AIMC Topic: Deep Learning

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Thin-slice 2D MR Imaging of the Shoulder Joint Using Denoising Deep Learning Reconstruction Provides Higher Image Quality Than 3D MR Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: This study was conducted to evaluate whether thin-slice 2D fat-saturated proton density-weighted images of the shoulder joint in three imaging planes combined with parallel imaging, partial Fourier technique, and denoising approach with deep...

Prediction of vitreomacular traction syndrome outcomes with deep learning: A pilot study.

European journal of ophthalmology
PURPOSE: To investigate the potential of an Optical Coherence Tomography (OCT) based Deep-Learning (DL) model in the prediction of Vitreomacular Traction (VMT) syndrome outcomes.

Deep-learning-based motion correction using multichannel MRI data: a study using simulated artifacts in the fastMRI dataset.

NMR in biomedicine
Deep learning presents a generalizable solution for motion correction requiring no pulse sequence modifications or additional hardware, but previous networks have all been applied to coil-combined data. Multichannel MRI data provide a degree of spati...

Identification of Root Canal Morphology in Fused-rooted Mandibular Second Molars From X-ray Images Based on Deep Learning.

Journal of endodontics
INTRODUCTION: Understanding the intricate anatomical morphology of fused-rooted mandibular second molars (MSMs) is essential for root canal treatment. The present study utilized a deep learning approach to identify the three-dimensional root canal mo...

UmamiPreDL: Deep learning model for umami taste prediction of peptides using BERT and CNN.

Computational biology and chemistry
Taste is crucial in driving food choice and preference. Umami is one of the basic tastes defined by characteristic deliciousness and mouthfulness that it imparts to foods. Identification of ingredients to enhance umami taste is of significant value t...

A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit.

Computers in biology and medicine
Intracranial pressure (ICP) is commonly monitored to guide treatment in patients with serious brain disorders such as traumatic brain injury and stroke. Established methods to assess ICP are resource intensive and highly invasive. We hypothesized tha...

Deep Learning-Based Facial and Skeletal Transformations for Surgical Planning.

Journal of dental research
The increasing application of virtual surgical planning (VSP) in orthognathic surgery implies a critical need for accurate prediction of facial and skeletal shapes. The craniofacial relationship in patients with dentofacial deformities is still not u...

Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy.

Analytical chemistry
The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operat...

Is deep learning-enabled real-time personalized CT dosimetry feasible using only patient images as input?

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To propose a novel deep-learning based dosimetry method that allows quick and accurate estimation of organ doses for individual patients, using only their computed tomography (CT) images as input.