AIMC Journal:
BMC medical imaging

Showing 231 to 240 of 252 articles

Hahn-PCNN-CNN: an end-to-end multi-modal brain medical image fusion framework useful for clinical diagnosis.

BMC medical imaging Jul 14, 2021
BACKGROUND: In medical diagnosis of brain, the role of multi-modal medical image fusion is becoming more prominent. Among them, there is no lack of filtering layered fusion and newly emerging deep learning algorithms. The former has a fast fusion spe...
Deep Learning Image Processing, Computer-Assisted Glioma Magnetic Resonance Imaging Neural Networks, Computer Brain Brain Neoplasms Diagnosis, Computer-Assisted Alzheimer Disease Tomography, Emission-Computed, Single-Photon Huntington Disease Carcinoma, Bronchogenic Humans
View on PubMed DOI

Aggregation-and-Attention Network for brain tumor segmentation.

BMC medical imaging Jul 9, 2021
BACKGROUND: Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted d...
Humans Neural Networks, Computer Algorithms Brain Neoplasms Supervised Machine Learning Diagnosis, Computer-Assisted Glioma Magnetic Resonance Imaging
View on PubMed DOI

Lesion probability mapping in MS patients using a regression network on MR fingerprinting.

BMC medical imaging Jul 8, 2021
BACKGROUND: To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula: see text], [Formula: see text], NAWM, and GM- proba...
Brain Mapping Probability Multiple Sclerosis White Matter Echo-Planar Imaging Humans Leukoencephalopathies Neural Networks, Computer Deep Learning
View on PubMed DOI

Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection.

BMC medical imaging Jul 8, 2021
BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and lesion detection with 0.625 mm thin-slice images.
Male Infant Deep Learning Adolescent Brain Humans Retrospective Studies Algorithms Female Child, Preschool Signal-To-Noise Ratio Infant, Newborn Child Multidetector Computed Tomography Brain Injuries Radiation Exposure Brain Diseases Craniocerebral Trauma
View on PubMed DOI

Detecting neonatal acute bilirubin encephalopathy based on T1-weighted MRI images and learning-based approaches.

BMC medical imaging Jun 22, 2021
BACKGROUND: Neonatal hyperbilirubinemia is a common clinical condition that requires medical attention in newborns, which may develop into acute bilirubin encephalopathy with a significant risk of long-term neurological deficits. The current clinical...
Retrospective Studies Female Infant, Newborn Male Deep Learning Magnetic Resonance Imaging Humans Diagnosis, Differential Kernicterus Acute Disease Chi-Square Distribution Subthalamic Nucleus Globus Pallidus Hyperbilirubinemia, Neonatal
View on PubMed DOI

Weighing features of lung and heart regions for thoracic disease classification.

BMC medical imaging Jun 10, 2021
BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for screening thoracic diseases. According to the domain knowledge of screening chest X-rays, the pathological information usually lay on the lung and he...
ROC Curve Heart Lung Diseases Heart Diseases Radiography, Thoracic Humans Thoracic Diseases Lung Deep Learning
View on PubMed DOI

Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.

BMC medical imaging Jun 7, 2021
BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measu...
Deep Learning Adolescent Bias Cardiomegaly Observer Variation Radiography, Thoracic Thoracic Cavity Humans Artificial Intelligence Young Adult Adult Female Male Aged Middle Aged Aged, 80 and over
View on PubMed DOI

A deep learning approach for dental implant planning in cone-beam computed tomography images.

BMC medical imaging May 19, 2021
BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.
Humans Deep Learning Nasal Cavity Neural Networks, Computer Cone-Beam Computed Tomography Alveolar Process Mandibular Canal Dental Implantation Bone Density Mandible Jaw, Edentulous, Partially Dental Implants Patient Care Planning Radiography, Dental Maxilla
View on PubMed DOI

Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.

BMC medical imaging May 8, 2021
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...
Case-Control Studies Deep Learning Lung Neoplasms Magnetic Resonance Imaging Humans Pneumonia Neural Networks, Computer Cystic Fibrosis Lung Respiration
View on PubMed DOI

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification.

BMC medical imaging May 8, 2021
BACKGROUND: One challenge to train deep convolutional neural network (CNNs) models with whole slide images (WSIs) is providing the required large number of costly, manually annotated image regions. Strategies to alleviate the scarcity of annotated da...
Datasets as Topic Prostatectomy Tissue Array Analysis Neoplasm Grading Prostate Supervised Machine Learning Neural Networks, Computer Male Diagnosis, Computer-Assisted Prostatic Neoplasms Humans
View on PubMed DOI
Popular Topics
Popular Journals