AIMC Topic: Deep Learning

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4D-CT deformable image registration using multiscale unsupervised deep learning.

Physics in medicine and biology
Deformable image registration (DIR) of 4D-CT images is important in multiple radiation therapy applications including motion tracking of soft tissue or fiducial markers, target definition, image fusion, dose accumulation and treatment response evalua...

Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic cholecystectomy.

Surgical endoscopy
BACKGROUND: The occurrence of bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is an important medical issue. Expert surgeons prevent intraoperative BDI by identifying four landmarks. The present study aimed to develop a system that ou...

A morphology based deep learning model for atrial fibrillation detection using single cycle electrocardiographic samples.

International journal of cardiology
BACKGROUND: Deep learning (DL) has shown promising results in improving atrial fibrillation (AF) detection algorithms. However, these models are often criticized because of their "black box" nature.

Micro-cracks detection of solar cells surface via combining short-term and long-term deep features.

Neural networks : the official journal of the International Neural Network Society
The machine vision based methods for micro-cracks detection of solar cells surface have become one of the main research directions with its efficiency and convenience. The existed methods are roughly classified into two categories: current viewing in...

Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks.

International journal of neural systems
Deep learning models for MRI classification face two recurring problems: they are typically limited by low sample size, and are abstracted by their own complexity (the "black box problem"). In this paper, we train a convolutional neural network (CNN)...

Automatic assessment of Alzheimer's disease diagnosis based on deep learning techniques.

Computers in biology and medicine
Early detection is crucial to prevent the progression of Alzheimer's disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis of AD in the earliest and hardest to det...

Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions.

Annals of clinical and translational neurology
OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterog...

Accelerating GluCEST imaging using deep learning for B correction.

Magnetic resonance in medicine
PURPOSE: Glutamate weighted Chemical Exchange Saturation Transfer (GluCEST) MRI is a noninvasive technique for mapping parenchymal glutamate in the brain. Because of the sensitivity to field (B ) inhomogeneity, the total acquisition time is prolonged...

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes.

ACS nano
Lung cancer has a high mortality rate, but an early diagnosis can contribute to a favorable prognosis. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for early-stage diagnosis. Exosomes, nanosize...

Deep learning detection and quantification of pneumothorax in heterogeneous routine chest computed tomography.

European radiology experimental
BACKGROUND: Automatically detecting and quantifying pneumothorax on chest computed tomography (CT) may impact clinical decision-making. Machine learning methods published so far struggle with the heterogeneity of technical parameters and the presence...