AIMC Topic:
Image Interpretation, Computer-Assisted
Clear Filters Showing 1291 to 1300 of 2720 articles
Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.
Radiology
Nov 3, 2020
Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive deep learning-based algorithm that assists in the detection of cerebral a...
Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting.
Radiology
Nov 3, 2020
Background Achieving high-spatial-resolution pituitary MRI is challenging because of the trade-off between image noise and spatial resolution. Deep learning-based MRI reconstruction enables image denoising with sharp edges and reduced artifacts, whic...
Challenges Developing Deep Learning Algorithms in Cytology.
Acta cytologica
Nov 2, 2020
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...
The detection of lung cancer using massive artificial neural network based on soft tissue technique.
BMC medical informatics and decision making
Oct 31, 2020
BACKGROUND: A proposed computer aided detection (CAD) scheme faces major issues during subtle nodule recognition. However, radiologists have not noticed subtle nodules in beginning stage of lung cancer while a proposed CAD scheme recognizes non subtl...
Automated analysis and detection of abnormalities in transaxial anatomical cardiovascular magnetic resonance images: a proof of concept study with potential to optimize image acquisition.
The international journal of cardiovascular imaging
Oct 29, 2020
The large number of available MRI sequences means patients cannot realistically undergo them all, so the range of sequences to be acquired during a scan are protocolled based on clinical details. Adapting this to unexpected findings identified early ...
Thyroid Nodule Classification for Physician Decision Support Using Machine Learning-Evaluated Geometric and Morphological Features.
Sensors (Basel, Switzerland)
Oct 27, 2020
The classification of thyroid nodules using ultrasound (US) imaging is done using the Thyroid Imaging Reporting and Data System (TIRADS) guidelines that classify nodules based on visual and textural characteristics. These are composition, shape, size...
Tumor segmentation in automated whole breast ultrasound using bidirectional LSTM neural network and attention mechanism.
Ultrasonics
Oct 22, 2020
Accurate breast mass segmentation of automated breast ultrasound (ABUS) is a great help to breast cancer diagnosis and treatment. However, the lack of clear boundary and significant variation in mass shapes make the automatic segmentation very challe...
Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.
Gastroenterology
Oct 21, 2020
BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is required in clinical trials, where it is expensive and slow because human central readers are needed. A ma...
Image Interpretation, Computer-Assisted
Observer Variation
Humans
Prospective Studies
Female
Aged
Adolescent
Young Adult
Treatment Outcome
Antibodies, Monoclonal, Humanized
Colon
Colitis, Ulcerative
Colonoscopy
Adult
Severity of Illness Index
Intestinal Mucosa
Male
Deep Learning
Predictive Value of Tests
Middle Aged
Feasibility Studies
Video Recording
Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.
Radiology
Oct 20, 2020
Background Recognition of salient MRI morphologic and kinetic features of various malignant tumor subtypes and benign diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patient tr...
PyHIST: A Histological Image Segmentation Tool.
PLoS computational biology
Oct 19, 2020
The development of increasingly sophisticated methods to acquire high-resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods th...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30108
- Neural Networks, Computer 29270
- Algorithms 26255
- Deep Learning 25773
- Artificial Intelligence 23797
- Robotics 13262
- Image Processing, Computer-Assisted 9270
- Retrospective Studies 8829
- Magnetic Resonance Imaging 5972
- Reproducibility of Results 5496
- Tomography, X-Ray Computed 4619
- Support Vector Machine 4604
- Computational Biology 4124
- Brain 3916
- Computer Simulation 3823
Recent Journals
- Scientific reports 5092
- Sensors (Basel, Switzerland) 4729
- PloS one 3860
- Neural networks : the official journal of the International Neural Network Society 2842
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1779
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1224
- IEEE journal of biomedical and health informatics 1081
- Journal of chemical information and modeling 934
- Nature communications 854
- Briefings in bioinformatics 849
- Bioinformatics (Oxford, England) 847
- Computer methods and programs in biomedicine 844
- IEEE transactions on neural networks and learning systems 780