AIMC Topic: Deep Learning

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Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

European journal of nuclear medicine and molecular imaging
BACKGROUND: For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. However, subject motion between the consecutive scans can cause problems for the PET reconstruction. A method to match the CT to the PET would...

Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives.

Neuroinformatics
Deep learning algorithms have a huge influence on tackling research issues in the field of medical image processing. It acts as a vital aid for the radiologists in producing accurate results toward effective disease diagnosis. The objective of this r...

IoT and Deep Learning-Based Farmer Safety System.

Sensors (Basel, Switzerland)
Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, re...

Can a Deep Learning Algorithm Improve Detection of Occult Scaphoid Fractures in Plain Radiographs? A Clinical Validation Study.

Clinical orthopaedics and related research
BACKGROUND: Occult scaphoid fractures on initial radiographs of an injury are a diagnostic challenge to physicians. Although artificial intelligence models based on the principles of deep convolutional neural networks (CNN) offer a potential method o...

Deep Learning for Head and Neck CT Angiography: Stenosis and Plaque Classification.

Radiology
Background Studies have rarely investigated stenosis detection from head and neck CT angiography scans because accurate interpretation is time consuming and labor intensive. Purpose To develop an automated convolutional neural network-based method fo...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

mSystems
Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large portion of human gut microbial proteins lack functional annotation. Here, we have developed a new m...

Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.

Korean journal of radiology
OBJECTIVE: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction met...

Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning.

Tomography (Ann Arbor, Mich.)
A murine model of myelofibrosis in tibia was used in a co-clinical trial to evaluate segmentation methods for application of image-based biomarkers to assess disease status. The dataset (32 mice with 157 3D MRI scans including 49 test-retest pairs sc...

Stimulus classification with electrical potential and impedance of living plants: comparing discriminant analysis and deep-learning methods.

Bioinspiration & biomimetics
The physiology of living organisms, such as living plants, is complex and particularly difficult to understand on a macroscopic, organism-holistic level. Among the many options for studying plant physiology, electrical potential and tissue impedance ...

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.

Biomedical physics & engineering express
Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour motions. Fast and accurate fiducial marker segmentation is a Requirement of real-time marker-based ve...